Information Quality and Integrity – European Approaches – WS 02 2026

27 May 2026 07:30h - 08:30h

Information Quality and Integrity – European Approaches – WS 02 2026

Session at a glanceSummary, keypoints, and speakers overview

Summary

The discussion focused on information quality and integrity in Europe, especially how AI-generated and synthetic content should be labeled, governed, and understood by users.[13-14][18][157-162] It built on a previous YouthDig message that called for visible markers on AI content, stronger youth involvement in AI transparency regulation, AI literacy in schools, and impact and risk assessments for AI systems.[10-11][18][82-90]


Speakers stressed that Europe approaches these issues through a people-centric, rights- and safety-based model, supported by instruments such as the GDPR, Digital Services Act, Digital Markets Act, AI Act, and the Council of Europe’s AI Framework Convention.[24-27][51-69] Janice Richardson argued that young people and users also need to understand regulation and build resilience through “seven C’s,” including control, community, connectedness, confidence, and co-regulation.[21-24][69-79] She added that young people want not only help detecting AI-generated content, but also deeper knowledge of how AI works, how to manage their own content, and how to address algorithmic bias and the attention economy.[82-90]


Pascal Schneiders reviewed research showing that the prevalence and effects of deceptive synthetic content are still poorly understood, while users’ AI knowledge and ability to distinguish information types remain limited.[108-117] He argued that labels can reduce trust in AI-marked content, are noticed selectively, can lose effectiveness over time, and may create unintended effects such as implied truth for unlabeled material.[118-145] He therefore recommended combining literacy and “inoculation” strategies with stronger visibility for verified, trustworthy sources rather than trying to label all deceptive AI content.[145-154]


Participants reinforced these concerns with examples from elections in Portugal and Kosovo, where AI-generated or manipulated political content, fake interviews, and pseudo-media pages were used to mislead voters.[215-217][225-242] Several speakers argued that responsibility should not rest mainly on users; states, platforms, media, and other actors need public-interest rules, oversight, and remedies, while cross-border cooperation is necessary because AI-generated content spreads globally and regulations differ by country.[245-261][268-273] Others emphasized that labeling alone cannot solve the problem, since emotionally manipulative or discriminatory content may still spread even when marked as AI-generated, making education, human sense-making, and stronger news and information ecosystems essential.[180-182][190-203][259-260][292-301][335-350]


By the end, the group broadly agreed on draft messages stating that AI increasingly threatens information integrity in political campaigns, responsibility must be shared beyond users, labeling has important limits, technological approaches are currently fragmented, and more aligned cooperation between states is needed.[361-374][405-418][419-424]


Keypoints

The overall purpose of the discussion was to examine how Europe should address information quality and integrity in the age of AI-generated content, building on prior YouthDig messages about visible markers, AI transparency, literacy, and youth involvement in regulation. The session aimed to evaluate whether labeling and watermarking are sufficient, how regulation and governance should evolve, and what mix of technical, educational, and institutional responses is needed. [10-14][18][157-165]


– The session was framed around extending earlier YouthDig calls for visible markers on AI-generated content, youth participation in AI governance, AI literacy in education, and risk assessment of AI systems, with a particular focus here on synthetic media and transparency at the point of consumption. [10-11][18][19][82-90]


– A major discussion point was the limits of labeling and watermarking AI-generated content. Speakers noted that visible labels can support transparency, but they are not a complete solution, may be technically fragmented across platforms, can disappear through reposting or compression, and may create misleading assumptions that unlabeled content is trustworthy. [18][105-107][117-145][173-182][190]


– Another key theme was that resilience and literacy are essential complements to technical labeling. Participants emphasized AI literacy, digital competence, fact-checking, understanding algorithms and bias, and broader “user resilience” as necessary for people-especially young people-to navigate manipulated or synthetic content. [21-24][69-90][145-149][191-194][347-350]


– The discussion also focused on governance and regulation, especially the European approach. Janice contrasted Europe’s people-centric, rights-based, precautionary model with the more market-oriented U.S. approach and the state-control-oriented Chinese approach, while also highlighting relevant EU instruments such as the GDPR, DSA, DMA, AI Act, and Democracy Shield. Multiple participants argued that responsibility should not fall only on users, but also on states, platforms, media, and other actors through public-interest frameworks and oversight. [25-28][51-68][245-252][263][364-365]


– Participants highlighted the democratic and security risks of AI-enabled disinformation, especially during elections and political campaigning. Examples from Portugal and Kosovo showed how fake or AI-generated political content can manipulate voters, imitate news sources, and spread emotional disinformation, while others argued that information integrity should also be treated as a cybersecurity, defense, and cross-border governance issue requiring stronger cooperation between states. [217][225-242][271-273][283-287][306-327][329]


The overall tone was serious, policy-oriented, and collaborative. It began as a structured and somewhat formal panel discussion, briefly interrupted by technical difficulties, then became more analytical and urgent as speakers and audience members raised concerns about manipulation, democracy, discrimination, and security. By the end, the tone shifted toward consensus-building and practical message drafting, with participants negotiating shared conclusions and wording. [19][31-38][93-100][156-165][245-260][352-356][358-424]


Speakers

– Francesco Vecchi – Moderator of the session; CVKI Coordinator at Humanist and Pan-European Movement for Popular Initiative; former YouthDIG Organizing Team 2025; identified himself as “Youth League 2024.”


– Frances Douglas-Thompson – EuroDIG 2025 programme committee member; former YouthDIG participant (2024/2025 as referenced in the session); introduced YouthDIG messages and discussed AI transparency, watermarking, and labeling.


– Janice Richardson – Educator, researcher, and author; adviser to governments, international institutions, and social media companies on digital literacy, rights, and citizenship; formerly coordinator of large-scale European internet safety and anti-bullying networks; expertise in innovative learning resources and platform development for children and adults.


– Pascal Schneiders – Postdoctoral researcher, Department of Communication, Johannes Gutenberg University of Mainz, Germany; research interests include news use, opinion formation in digital information ecosystems, digital transformation of news media, and media/platform governance implications.


– Smee Cujic – Read out and consolidated the session messages.


– Co-moderator – Remote/chat moderator role; relayed online questions to the room. The general moderator role is consistent with standard conference co-moderation functions [S12].


– Gabija Skučaitė – Representing academia and a group of educational institutions from Lithuania; spoke on AI-saturated environments, human sense-making, and the educational role of academia.


– On-site participant – Multiple unnamed in-room participants who contributed interventions and questions.


Additional speakers:


– Inej – On-site participant; from YouthDIG/Ustick; spoke about misinformation in Portugal, elections, deepfakes, and political party responsibility.


– Hurya Mameti – On-site participant; from Action for Democratic Society and a hybrid info/fact-checking outlet in Kosovo; discussed AI-generated political content, fact-checking, and internal regulation/watermarking in media.


– It the Beckall – On-site participant; from the Council of Europe’s Anti-Discrimination Department; raised points about state positive obligations, public-interest frameworks, oversight, and human-rights-based transparency.


– Olga Martinez – Remote participant whose question was relayed by the co-moderator; asked whether transparency is being overestimated as a solution.


– Jessica – On-site participant; from YouthDIG/ETHDIC; spoke about European cooperation, the DSA, AI opportunities, and risk governance.


– Liliana – On-site participant; from North Macedonia, representing an NGO in the Balkan region; discussed information integrity as a cybersecurity/global security issue and civil society tooling.


– Pari Esfandiari – Remote/chat participant; contributed thoughts on social trust and trust in institutions/education, as acknowledged by the moderator.


– Sue Pinnim – Mentioned by Francesco Vecchi as remote moderator.


– Camino Rojo – Mentioned as an intended but absent speaker from Google; associated with discussion of C2PA and SynthID, but did not participate.


Full session reportComprehensive analysis and detailed insights

The session focused on how Europe should respond to declining information quality and integrity in an environment increasingly shaped by AI-generated and synthetic content. Francesco Vecchi opened by explaining that the discussion was designed as a continuation of one of the most relevant YouthDig messages from the previous year, which had called for visible markers on AI content and stronger youth involvement in AI transparency regulation. He noted that the session title had been broadened to “Information Quality and Integrity, European Approaches” in order to move beyond last year’s message and develop the discussion further. [7-14] Frances Douglas-Thompson placed the topic within the wider YouthDig process, stressing that the earlier message on “Everything AI” had become even more relevant a year later because the information environment keeps changing and policy ideas need to be revisited rather than treated as fixed. [18]


Frances summarised the key points of the earlier YouthDig message. It had called on digital services and platforms to use visible markers when AI is operating, asked for ethical guidance on AI applications to be developed with input from young people, urged that AI literacy be embedded in school curricula, and said that AI systems should undergo impact and risk assessment. She clarified that the present session would focus especially on synthetic media and transparency “at the point of consumption”, meaning what users actually see when they encounter content online. She also stressed that AI literacy should not be limited to use of tools, but should include understanding how AI works, how algorithms shape exposure, and where human oversight needs to remain. [18] A core tension was introduced early: technical transparency measures such as watermarking and labelling may help, but they are not sufficient on their own and need to be considered alongside literacy, resilience, governance, and changing user behaviour. [18]


Janice Richardson opened by saying that one important message was missing from the initial framing: young people, and users more broadly, also need to understand regulation, not only technology, if they are to navigate information quality and integrity. She linked this to the 2025 Democracy Shield, describing its core objective as quality and integrity, stopping interference from other countries in elections, and building the resilience of young people through digital literacy. [20-25] Janice’s intervention was briefly interrupted by technical issues before she resumed with her slides. [29-50]


When she continued, Janice contrasted European approaches with those of other regions. She described Europe as people-centric, grounded in safety, rights, and values, and oriented towards strategic autonomy and digital sovereignty through a precautionary, risk-averse approach. [25-28][51-54] She contrasted this with the US model, which she said is more competition- and innovation-driven, with a stronger role for private sector leadership and market dominance, and with China’s more state-centred model of territorial control over data, platforms, and networks integrated into industrial and national strategy. [55-59]


Janice then turned to concrete European legal instruments. She said Europeans should be more aware of the tools already available to protect users and data, naming the GDPR, the Digital Services Act, the Digital Markets Act, consumer protection rules, the AI Act, and the Council of Europe’s AI Framework Convention. She characterised these instruments as offering transparency, rights, protection against manipulative and harmful content, user choice, and safeguards for human rights, democracy, and the rule of law. [60-68]


A central part of Janice’s intervention was her emphasis on “user resilience”. She said resilience is essential and described it through “seven C’s”, explicitly mentioning control, community, connectedness, communication including reporting, confidence in institutions and regulation, and co-regulation involving industry and users. [69-79] She also said that in her work with young people and other learners, they consistently ask not only for tools to identify AI-generated content, but for broader understanding: how AI works, what large language models are, how self-generated content can be repurposed into fake news, how AI sycophancy may affect well-being, how the attention economy shapes incentives, and how algorithmic bias and discrimination operate. [80-90]


Pascal Schneiders then focused on visible, audience-facing disclosures such as labels and disclaimers, rather than invisible cryptographic watermarking, arguing that what matters at the point of consumption is what people can actually see. [103-107] He said one core governance question is how common deceptive synthetic images, audio, and video really are on social media and what effects they have on different groups. He noted that the evidence base remains limited because deceptive synthetic posts are hard to detect and study, and much current knowledge still relies on a small number of anecdotal high-profile cases. Even so, he said pressure to act is high because of the risks these materials pose to user autonomy, opinion formation, and informed decision-making. [108-111]


Pascal said current evidence suggests users’ AI knowledge is limited and their ability to distinguish information, opinion, and advertorials is generally low. He also said people’s video literacy is only moderately developed, including among younger users, even if many users can judge source familiarity and have some awareness of online risks. [112-116] In practice, he said, deceptive posts can more easily manipulate audiences when they imitate trusted journalistic formats or established sources. [116-117]


He then examined the effects of labels. Pascal said research still tells us relatively little about how effective labels are in helping people distinguish synthetic from non-synthetic deceptive content, especially because labels vary in format, scope, and placement. [117-118] What is known, he said, is that users pay selective attention to warning labels depending on design, context, prior attitudes, and media literacy. [118] He added that AI disclosures can have a generally negative effect on user judgements, producing an anti-AI bias. For example, news labelled as AI-generated may be seen as less trustworthy even when readers do not judge it differently on factual accuracy or bias. [119-123] He also noted that users are more likely to recognise disclosures when they are prominent and visually distinct, and that in journalism they care less about technical details of prompts or models than about whether institutions are being open and transparent. [123-128]


Pascal also stressed the behavioural limits and unintended effects of labels. He said users who already agree with the content of a synthetic post are unlikely to be dissuaded by a label because of confirmation bias. [129-131] He warned that people often forget whether content was labelled and that widespread use of warnings can create fatigue, reducing effectiveness over time. [132-134] Drawing from misinformation research, he mentioned the backfire effect, while noting it is not strongly robust empirically, and the “implied truth effect”, where content not carrying a warning may be wrongly treated as true simply because only some misinformation is labelled. [135-141] He recommended combining more detailed explanations, the “sandwich principle” of placing corrections around falsehoods, and inoculation approaches that expose people to weakened misinformation and teach them deceptive techniques. [142-149] He also recommended combining such approaches with “must-be-found” strategies for verified content from trusted sources, rather than trying to label all AI-generated or AI-assisted deceptive content. [149-155]


Francesco then linked these concerns to broader debates on media ecology and cognitive security. He said AI-generated content and algorithmic feeds affect how people understand reality and shape political beliefs, linking this to debates on the Rome Declaration on Media Ecology, the Khan Declaration, sovereignty of mind, and cognitive security. [157-162]


Mentimeter responses from participants reflected this normative framing. Frances reported that participants most strongly associated the topic with ideas such as control, security, autonomy, power, and protection, and noted that these concepts can sit in tension with one another. [167-171] She used these responses to reopen the question of whether watermarking actually empowers users and gives them meaningful control. [173-180]


Because Camino Rojo from Google could not attend, Frances briefly summarised the proposal herself, describing C2PA and SynthID as examples of current watermarking and provenance technologies and using them to illustrate how fragmented current approaches remain. [172-182] She explained that SynthID is harder to strip away than standard metadata-based approaches, but is limited to Google-generated AI content. [182] C2PA, by contrast, works through provenance metadata embedded in media, but this metadata can disappear when content is screenshotted, compressed, re-uploaded, or shared through social media. [182] She concluded that current labelling and provenance methods are fragmented and siloed across platforms and do not scale neatly across the wider information ecosystem. [173-182] She also sharpened one of the central questions raised earlier: if something is labelled as AI-generated, does that simply encourage users to assume that unlabelled content is trustworthy? [180-182][190] She explicitly asked whether too much responsibility is being placed on users and young people if resilience means they must constantly decide what is true and false online. [191-194]


The floor discussion gave these issues a strong democratic and electoral dimension. A participant from Portugal argued that AI and deepfakes make it easier to manipulate political images and spread misinformation during elections. She referred to a recent legislative election and said one party had allegedly been responsible for around 80 per cent of online misinformation about the campaign. She also argued that political parties themselves must bear responsibility if they use such tools while claiming to defend democracy. [213-217]


A participant from Kosovo, representing a fact-checking outlet, reinforced this election focus with examples from her own context. She said her organisation increasingly debunks AI-generated content around politically sensitive moments such as elections, including fake interviews, synthetic people who do not exist, manipulated branding that imitates real media logos, and AI-generated material used to create the false impression that news outlets or public figures support a particular candidate or party. [223-231] She said they were also seeing what she called “slopaganda”: low-quality, fully AI-generated content, often involving unrealistic or sensational videos of politicians, designed to trigger engagement. [232-235] She further identified pseudo-media accounts as a serious risk because they present themselves as news outlets while obscuring who is actually behind them. [239-242] Her organisation has tried to respond by convening media, academia, civil society, and public institutions in Kosovo to integrate AI rules into internal media regulations and require watermarking for AI-generated images, even when the images are used only illustratively, because audiences may still believe them. [236-238]


Another major intervention came from a participant from the Council of Europe’s anti-discrimination department. She argued that it may indeed be too much to place responsibility on individuals alone and that the burden should shift more strongly toward states’ positive obligations to ensure a safe online environment. [245] In her view, platforms also bear responsibility, but states cannot outsource media governance to private companies. [245-247] She argued that labelling, watermarking, and moderation are not enough unless they are situated within a public interest framework in which states define clear rules, conduct risk assessments, ensure transparency, create independent oversight, provide access to information for researchers and regulators, and guarantee remedies. [246-248] She further argued that transparency should not be treated as an isolated technical obligation or an end in itself, but as part of a human-rights framework oriented toward accountability, equality, researcher and regulator access, and remedies. [248-252]


She also pressed on what happens when technical systems fail. She asked whose content becomes less trusted when watermarking systems are manipulated or labels are missing, and whose voices are easiest to dismiss in those circumstances. [253-258] She illustrated this with an example from UK parliamentary research on AI-generated anti-immigration imagery that was clearly marked as synthetic but still amplified by platform algorithms and viewed by millions. [258-260]


Francesco picked up some of these governance questions by pointing to a definitional problem: in an era when many people use AI tools in ordinary work, where should regulators draw the line between AI-assisted and AI-generated content? [263] He also reminded the room that the Digital Services Act includes a Code of Practice on Disinformation, but that this was developed before the current phase of generative AI, raising questions about how such instruments may need to be updated. [263]


Several later interventions focused on cross-border and shared governance. A participant from Armenia argued that states do have a role, but must balance regulation carefully against freedom of information and human rights. She stressed that cooperation among states is essential because AI-generated content can originate anywhere, and fragmented national rules make control difficult. [266-274] Another participant, Jessica from YouthDig, agreed on the importance of European cooperation and pointed to existing examples such as the DSA and the European Board of Digital Services Coordinators as evidence that shared enforcement can work. [277-282] She also argued that the issue should not be framed as a trade-off between innovation and safety. Instead, she said governance should seek to maximise opportunities such as growth, education, productivity, and civic participation while preventing harms such as toxic algorithmic amplification, gender-based image abuse, and misinformation. [283-287]


A remote question from Olga Martinez asked whether transparency is being overestimated when emotionally manipulative content can remain effective even if users know it was AI-generated. [289-290] In response, Pascal argued for a more holistic governance approach that also strengthens the production and visibility of quality journalism, which he said research links to lower belief in misinformation. [292-301] He said AI systems affect not only individual judgement and public opinion, but also the production, visibility, and viability of high-quality public information. [292] He therefore argued that governance should support the future of journalism, including possible funding or subsidy mechanisms, because strong news media remain one of the best defences against misinformation. [293-296] Drawing on Reuters Institute research, he added that people who use news media are less likely to believe misinformation because journalism exposes them to other perspectives and supports resilience. [294-296] He also reiterated that oversight bodies should be pluralistic and independent, resembling in some respects the representative oversight structures used in German public service media. [297-301]


A participant from North Macedonia added a security perspective, asking whether information integrity is now becoming part of cybersecurity and cyber resilience. She argued that AI-generated content is lowering the cost of influence operations and is no longer just a media or misinformation issue, but also a regional and global security issue. [306-313] She also stressed that smaller states and weaker digital ecosystems often lack the institutional capacity to respond effectively, and asked what governance models and practical tools are available in such contexts. [313-327] Francesco broadly agreed, noting that these issues intersect with disinformation policy, foreign policy, defence, and questions of cognitive sovereignty, and that these perspectives need to be considered together if recommendations are to remain relevant. [329]


Gabija Skučaitė offered a reflective closing intervention. She described the current condition as a “time in between”, in which reality feels blurred and people struggle to distinguish true from false in an AI-saturated environment. [330-335] She stressed that context and source still matter deeply-how information is presented, in what setting, and by whom-and argued that education should focus on helping people make sense of reality in such an environment. [335-350] While labels may have some role, she said the more fundamental response is to return to human capacities for sense-making. She also argued that academia should play a major role in helping people distinguish the real from synthetic or manipulative virtual overlays. [347-350] Francesco reinforced this by referring to a written comment from Pari Esfandiari, who stressed that the deeper issue is social trust, especially trust in institutions and educational institutions, when societies no longer know how to distinguish fact from fiction. [352-353]


The session concluded with collaborative drafting of messages intended to reflect broad consensus. Francesco reminded participants that EuroDIG workshop messages must represent broad agreement rather than individual positions. [354-356] Smee Cujic then read out draft conclusions. The first stated that AI poses threats to information integrity and is increasingly being used during political campaigns. [361-363] The second said responsibility should not rest only on users, but also on states, media, and political parties, and that states have a positive obligation in this area. [364-366] A longer draft message said labeling must be situated within a broader framework because it does not by itself address discrimination, unjust interference, or social harm. It also warned that labeled AI content may not create clarity and that unlabeled content can be wrongly assumed to be truthful or high-quality. [367-374]


There was broad agreement that responsibility should not fall on users alone, but some discussion over wording. One participant wanted private or technology companies added explicitly, another asked to mention civil society organisations, while another suggested removing political parties. [377][382] Francesco opposed removing political parties, arguing that they are often direct spreaders of misinformation and are not always formally part of the state. [383] Another participant suggested keeping the wording more general and function-based so as not to exclude relevant actors whose legal status differs across countries. [385-398] Frances eventually suggested leaving the wording open for later refinement after the conference. [399-404]


The final two draft messages focused on fragmentation and cooperation. One stated that current technological approaches are fragmented across platforms and across countries, with Frances clarifying that systems like those discussed from Google do not yet exist in a coherent interoperable way across the whole ecosystem. [405-415] The last stressed that stronger cooperation between states is needed because AI-generated material circulates globally while legal and policy approaches vary across jurisdictions. [416-418] A participant proposed making this more explicit by referring to cooperation and regulatory frameworks between countries and the need for alignment. [419-421] Francesco responded that he preferred the language of interoperability rather than complete homogeneity, suggesting that aligned but not identical systems might be a more realistic goal. [422]


Overall, the discussion showed broad agreement on several points. Participants agreed that labels and watermarking may improve transparency but are not sufficient on their own; that literacy, resilience, journalism, trust, and human sense-making remain essential; and that responsibility should be shared across users, states, platforms, media, political actors, and other institutions. [18][69-90][117-155][157-162][191-194][213-260][292-301][361-374] The main unresolved questions concerned implementation: how to define AI-generated content, how to structure oversight, who should enforce transparency obligations, how to update existing rules such as the DSA’s anti-disinformation framework, and how far European cooperation should aim for alignment or interoperability across countries. [149-155][245-260][263][266-274][377-422]


Session transcriptComplete transcript of the session
Francesco Vecchi

I know it’s morning after a social event, so we appreciate even more your attendance to the room. Before starting, I would strongly encourage all of you to scan the QR code that you see on the slideshow. That will redirect you to Mentimeter, where there are a few questions that would help us navigate the discussion of today. Without further ado, I am extremely pleased to moderate this session. My name is Francesco Vecchi. I am Youth League 2024, former Youth League Organizing Team 2025, and currently I’m the CVKI Coordinator at Humanist and Pan -European Movement for Popular Initiative. This year, Frances, to whom I will leave the floor in a minute, decided to continue the conversation on one of the most relevant, probably, Youth League messages of last year.

And you probably might remember from yesterday’s session, every year at EuroDig there is a youth training program called YouthDig. It ends up with some messages that are supposed to inform the political conversations at EuroDig in the very same year and possibly also in the years to come. Last year, one of these focused on calling for visible markers on AI content and greater youth engagement in AI transparency regulation. This was the main starting point for the organization of this session. As you might notice, the title is slightly different. The session is titled Information Quality and Integrity, European Approaches. Of course, it built on the messages of last year, but we also came up with some more ideas to push the discussion further.

Again, I’m extremely happy to leave the floor to Frances Douglas -Thompson. She was YouthDig 2025, and this year she’s part of the EuroDig program committee. And she will give you an overview of what were the messages last year. please Frances

Frances Douglas-Thompson

perfect thanks so much Francesco yes so last year we designed some messages Francesco if you could go to the message slide perhaps so yeah I was part of Youth Dig last year and like every year Youth Dig messages covers a very very broad range of topics this one in particular I think has increased relevance today and a year post Eurodig last year and Youth Dig last year it was under the title Everything AI you can find these online they’re published alongside the Eurodig messages and so this one in particular talks about watermarking and transparency of AI synthetically generated material synthetic material online so that might be audio something visual images or videos etc so basically as a program uh committee member this year i was going through some of the proposals and i found that a lot of proposals were very relevant to this we had one from google talking about new technologies that have emerged that they are applying on their platforms that seek to basically tell users whether something is synthetic material or not and maybe what percentage of an image or a video is ai generated and this obviously is a step in the right direction to encouraging transparency in this area but of course we know that watermarking is probably not and labeling as synthetic material is probably not a catch -all sort of like a way to deal with this issue and i think that’s where this conversation can sit right so there’s obviously a tension that we also need something like increased digital literacy our information environment is rapidly changing and so the reason why i think the youth dig messages are highly relevant today is because the youth dig messages don’t just sit in a vacuum and they’re not static they should be constantly evaluated and come back to because um though we ask for things the environment changes so yeah i’m really very grateful that janice and pascal are joining us today and yeah I mean if you look at this message in particular that’s on the slide now we ask for a few things we ask that digital services and platforms use visible markers to inform when AI is operating and I want us to consider whether that’s always a good thing whether that necessarily means that we can trust material or not or whether this is able to convey harm secondly we said that ethical guidance on AI applications should be developed with input from young people third we said that AI literacy should be embedded in school curricula not just how to use AI but also how AI works how they function and what the algorithms behind it are also where human oversight must be maintained and lastly we said that AI systems should always undergo impact and risk assistance so that was basically what this message says I think today we’re going to be focusing on on the synthetic side of it and and transparency essentially at the point of consumption like what do users experience when they go to consume media and and what does that mean so I’m really excited for this conversation and I will pass back to Francisco thanks very much.

Francesco Vecchi

Thank you very much Frances um as Frances was mentioning we are going to continue the conversation with some extremely interesting speakers uh first of all let me welcome janice richardson janice is an educator researcher and author she advises governments international institutions and social media companies on digital literacy rights and citizenship she was formerly the coordinator of large -scale european internet safety and anti -bullying networks and she has extensive experience in innovative learning resource and platform development for children and adults i know that she has some slides to share so i will leave her the floor to start a conversation please janice the floor is yours janice i believe you’re still muted So, we see the slide, but I

Janice Richardson

Thank you. So, I think there is one message that I feel that you have missed. I feel that young people have a real responsibility, we all have a responsibility to also understand regulation. When we’re talking about information quality and integrity, there is one very important point. And that is, we have to be able to understand what is happening in the world. legal instrument that has come out very recently in 2025, and this is the democracy shield. The core objective is quality and integrity, stopping interference from other countries in our elections, but also building resilience of young people through digital literacy. In Europe, we have a people -centric approach, rather different than the other major regions in the world.

We believe in safety rights, values. We take a proportionate approach, which is risk -adverse, because the goal is strategic autonomy and digital sovereignty. Now, it’s very difficult to maintain such an approach when we have America on one side, the USA on the other side.

Francesco Vecchi

Excuse me, Janice.

Janice Richardson

Yes?

Francesco Vecchi

I’m asking. I’m asking you to stop for just a second, because we’re experimenting some technical hiccups in the room. So we heard the starting point of your conversation, of your intervention, but now the last few seconds were cut. maybe in the meanwhile, if you don’t mind, Janice, I will reshare the QR code for the Mentimeter so people can go on with answering those questions. Okay, Janice, while we’re covering up with the slide on the Mentimeter, we ask you to try and speak again. Janice, I have just lost you. I have just lost you. Okay, never mind. In the meanwhile, again, please, participants in the rules, can the QR code go on with answering the questions?

They will lead our conversation later on during the session of this morning. In the meanwhile, maybe I’ll ask if Janice is still hearing us or she lost us again?

Janice Richardson

No, I’m here and I can hear you.

Francesco Vecchi

Okay. Okay. Let’s go. I’ll ask Janice again.

Janice Richardson

Can you see my slides?

Francesco Vecchi

No, because I’m sharing now, but I will stop presenting my slides and then you can present yours again. Okay. Okay. Okay. Okay. Okay. Okay. Okay. Okay. Okay.

Janice Richardson

Now, can you see my phone?

Francesco Vecchi

Yes, now we can.

Janice Richardson

I’m not sure it’s recorded, but one of the very big challenges with digital integrity and quality, it’s the very different approaches across three regions. We, in Europe, have a people -centric approach, very much based on safety rights values. It’s precautionary, risk adverse. The goal being strategic autonomy, digital sovereignty. However, much of the content we receive comes from the United States, where the approach is more competition, innovation -oriented, with private sector leaders leading the field and really exposing enforcement rather than imposing regulation. The goal here is to restrict market assets, to maintain the dominance of the market and to shape global standards. Whereas in China, which is the upper third declared, I’m sure you’re all on TikTok, it is territorial control over data, over platforms, over networks.

The aim being to integrate AI governance with industrial policy and national strategy. And this poses, as we know, significant implications for data quality and integrity. But as Europeans, we should also be very much aware of the legal instruments, the regulation, the directives that will help us protect our data. GDPR, we all know about that, to give us control over our personal data, to ensure transparency and rights. Digital Services Act, which aims at tech companies. to avoid manipulative harmful content. The Digital Markets Act, which aims at freedom of choice and mainly cat -sack stores providers. We should also know about the Consumer Rights Directive, what you see is what you get, the 14 -day cancellation window when we’re online shopping.

And this, of course, brings us to the AI Act, which many countries see more as a charter than any form of legal instrument. The aim is to ban dangerous uses and high risk, and the table you see there actually rates risks and what to do in case of risks. There is also the AI Framework Convention, true to all conventions, or the… The Council. of Europe, the aim is to protect human rights, democracy and rule of law. But we also have to look at the user because it’s user resilience that counts and user resilience is also an objective of the democracy shield of the European Union. And we can say there are actually seven C’s to user resilience.

First of all, control. You have to know your tools and control where you are and this relies on digital competence. But then we need a community around us and this is often a problem working with digital technology. It’s very much a single person approach, the individual approach. We have to get over this. Connectedness is extremely important. Being able to communicate and this also includes reporting, when things go wrong, which once again is an area we have to tackle. confidence, confidence in our government, confidence in these various directives and regulations that can help us and co -regulation. It’s moving so fast to keep up with it. Industry has to be involved at all levels, but with young people and all of us.

I work a lot with young people, in particular now on a project called DigiGam and a Restless Plus project, where the target is for people in prison, in vocational training and in higher education. There are many things they want to know. First of all, as was already mentioned in the messages by Frances, detecting AI -generated content. But they also want to know how AI works. What are LLMs? How can I influence them? They want more control of self -generating. They want more control of their own self -generated content, which can very rapidly change become AI -generated fake news. But there is a rising concern about the AI sycophancy and how that is challenging our well -being.

The attention economy, we need to take a closer look. What is this attention economy where getting clicks is the objective even of journalists? They want to know marketing strategies, fact -checking, because now in that summary that we get, rather than knowing the real details, and of course one thing all young people want to learn more about, all of us do, algorithm bias, discrimination. I’ll hand it back to you. I hope that was comprehensible.

Francesco Vecchi

Thank you very much, Janice. I think that it was a very good setting, the scene for the conversation of today. I’m now happy to leave the floor to, wait a second. to Pascal Schneiders. Pascal is a postdoctoral researcher at the Department of Communication at the Johannes Gutenberg University of Mainz in Germany. His research interests include news use and opinion formation in digital information ecosystems, the digital transformation of news media and media and platform governance implication. Please, Pascal, take the floor. I will also ask our remote moderator, Sue Pinnim, as main speaker, please. Thank you.

Pascal Schneiders

Yeah, thank you very much, Francesco, for introducing. And I’m happy to take part in that workshop. I would like to share some insights or short literature review of what we know about labeling content on online platforms. Mostly from communication or platform studies. And first of all, my point is about visible disclosure methods such as labels or disclaimers and their effectiveness from an audience perspective. So it’s not about invisible methods such as cryptographic watermarking because, yeah, it’s evident that people can’t see them. They are invisible and that’s more on a technical side. So when considering the design of governance measures, of course, always the question arises as how prevalent deceptive synthetic images or audios or videos are on social media platforms and what effects they have on different people.

To be honest, we know very little about that because it’s the nature of things. Those content posts are mostly hidden and deceptive, and our knowledge is mainly based on a few prominent anecdotal cases. But the pressure to act is certainly there and high because the risks of undermining people’s autonomy or people’s capabilities to distinguish different forms of public communication and capabilities to form opinions and to make well -founded decisions in the absence of interventions. And what we know, in fact, is that individuals’ video literacy is only moderately developed. that is also true for younger ones. People are quite good at assessing the trustworthiness of sources based on sources familiarity, for example. And they have also a fairly good understanding of the risks online, also related to AI.

But according to initial studies, the knowledge of AI that people have is rather limited and the ability to distinguish between information, opinion and advertorials is quite low in general. And that means there’s a greater potential for manipulation in online posts that pretend to come from established sources like journalistic ones, for example. We also know quite a little about the effectiveness of labels, how effective they are in helping people to distinguish between synthetic and non -synthetic deceptive content, and especially since there are many different ways to label content, such as source -specific labels or claim -specific ones that are attached to a particular post from a specific account. And we also know that people are quite selectively attentive to warning labels, depending on the design of the label, the usage situation, people’s attitudes, their prior experiences, their involvement in different topics, and their degree of leader literacy.

And when detected AI disclosures, in general have mostly a negative influence on people’s judgments, which indicates a negative AI -based bias. For example, people generally perceive news items labeled as AI -generated to be less trustworthy, even when the articles themselves are not rated as less accurate or biased. And knowledge of journalism is interestingly a significant one right here. So the more people know about journalism, the more critical they are of AI. And when recognizing different forms of labels people wish for and contrasting colors of size, shape, and the placement of warning icons or labels are important. And that’s one of the key factors in the identification. or recognizing labels in their context. And as we know from recent studies, users, as I already mentioned, they wish for clear, understandable, intuitive, and upfront AI disclosures.

And as we know, as far as we know from the context of journalism, users care less about the technical details of AI use so they’re less interested in which models or prompts have been used. They’re more interested in about knowing of the, yeah, or more interested in the perceived openness of journalism, especially of journalism because journalism still isn’t, yeah, central intermedia, yeah, institution that intermediates between different groups in society. So trust, and trust. generated or established by being transparent is essential here. Furthermore, people who agree with the content of a synthetic post will not be or most likely not be swayed by labels or prevented to engage with the content. That’s something that we know or that is known as confirmation bias, for example.

So, persuading people or preventing people from engaging with the content or those people who have high beliefs in that specific content which is dealt with in a certain synthetic post, that’s quite unlikely. Moreover, people often forget a piece of content that has been labeled and an increased use of interstitial warnings may cause. fatigue. So labels or using labels may lose effectiveness over time because people forget that a certain content has been labeled or over time they oversee those labels. And that means that using labels may contribute to a continued influence effect when misinformation continues to influence decision making after a correction has been issued. And there are also a number of other unintended negative consequences of using labels that we know about from misinformation research.

For example, the backfire effect when correcting something or someone only further increases the belief in the misinformation. But we also have to mention that it’s not a robust empirical phenomenon in that context. So it’s quite I’m sure of how developed or how prevalent that backfire effect might be in reality. But there’s another unintended negative consequence, the so -called implied truth effect. So when a subset of misinformation is labeled as false, people may perceive unlabeled misinformation as better than true. True. And that’s yeah, it’s not always the case in reality. So what might be held is using detailed explanations of why certain content is misleading, because that might stick in people’s minds better and making use of the so -called sandwich principle.

So embedding false information between corrections at the beginning and the end, which is true. Might be helpful, helpful to. making people aware of misinformation or deceptive AI -generated content. And additionally, making use of so -called inoculations has been found to reduce the continued influence effects and to boost cognitive resistance or resilience, as Janice has already mentioned it. And in that case, people are exposed to weakened, controlled doses of misinformation and taught about deceptive techniques using, for example, gamification methods and making use of already mentioned AI literacy measures in school. That is, instead of shielding people from every false or misleading story, people can be taught to be persuasive. Techniques used by misleading strategic actors or content such as propaganda, conspiracy, theories or disinformation.

To conclude with the recommendation, making use of such inoculation could be combined with highlighting and implementing must -be -found strategies for verified content from trusted sources, rather than trying to label all AI -generated or AI -assisted deceptive content, because that is quite impossible because of the sheer amount of content on online platforms and the unintended negative consequences that I mentioned before. And a must -be -found rule for verified, trustworthy content from trustworthy sources already exists in reality in Germany, for example, for TV platforms. So we could try to adapt that. For online platforms as well. And lastly, that raises, of course, the question of who decides which content should be flagged as positive. That certainly should be done independently of the government or the state, and it should happen at repeated intervals and according to transparent criteria and processes.

Thanks very much.

Francesco Vecchi

Thank you very much, Pascal, for your contribution to the discussion. Now, before opening the floor to an open Q &A during the morning, I just wanted to say that, as you might have found on the wiki, that one of the main points of having this conversation today is that AI -generated content is already reshaping our human cognition. It is because we are exposed to that on social networks. It is because even algorithms are just feeding us what we want to receive. And these are exactly the points that raise the concerns of the Rome Declaration on Media Ecology and the Khan Declaration on the Sovereign of Mind. Sovereign of Mind. cognitive security. I mean, there are different ways of approaching the question of information integrity because we already understand that AI generated content, and in general, AI is influencing the way we understand reality, the way we face it, and therefore the way we shape our political beliefs.

Anyway, I think it’s time to share the results of the Mentimeter. And with this, I’m happy to leave the floor again to Frances to comment on the results. And also to explain a couple of technologies that might be helpful in solving at least some of the issues related to AI generated content on the social network. So please, Frances, take the floor.

Frances Douglas-Thompson

Thanks a lot. Thank you to everyone who filled in the Mentimeter. We got a lot of responses. These are the main ones, control, security, autonomy, power, protection. I think these are interesting because they’re slightly juxtaposing, right? But yeah, you can have a look at that. I wanted to very quickly, before we turn over to the floor, we were going to be joined by Camino Rojo from Google, but she’s unable to attend, unfortunately. But the proposal that we got was talking about C2PA. and SynthID, and these are two watermarking technologies that Google has rolled out just within their platform, and I think this is interesting because one, it shows that still these technologies are slightly siloed, which speaks a bit to what Pascal was saying, that these technologies are quite difficult to actually launch at scale across platforms, and what I really have enjoyed about the points made so far by Janice and Pascal is that clearly there’s attention that exists, right?

So watermarking seeks to be a good thing, but one, is it feasible? Two, is it positive? Does it send the right message? Is it able to work alongside digital literacy to provide clear transparency signals to users? Does it empower users? Does it provide them with control and does it protect them? Or does it send the wrong message, like for example give them, as Pascal said, a misunderstanding of what is true and what is false? For example, if something’s not labeled, does that mean that it’s highly reliable? Or should we have all information critically engaged with by users online? so yes these are two technologies that Google has currently that we were going to hear about SynthID essentially is watermarking but which is harder to strip away than C2PA but it’s only for Google generated AI content so it doesn’t work for other content C2PA works by embedding provenance metadata but again if you screenshot these images re -upload compress or share via social media then this metadata disappears so currently methods of labeling are fragmented and so today I hope that we can have some contributions thinking about whether that’s necessarily a bad thing.

The second thing I want to talk about and maybe go a bit of what Janice and Pascal were saying, Janice gave us a very clear overview that regulation exists already in the EU and now it’s our role to make sure that we enforce that regulation and think about how that can realistically improve our situation as users online and people who engage with content online. So I’m going to go ahead and start with Janice. Thank you very much. Thank you very much. Thank you very much. Thank you very much. Thank you very much. I would have to agree that when you label something as content AI generated, it may unconsciously make people assume that everything that’s not is evidence and is truth, and that’s quite problematic.

And I thought the point by Janice about resilience is interesting, and I would love to hear your contributions about what you think about user resilience. Is that putting too much emphasis on users, you know, having to have control and understanding of everything online? Is that too much emphasis to put on users and young people especially in having to understand constantly and determine what is true and what is not true? So, yeah, those are questions to go out. Lastly, to do with the mentee, I really would love contributions from the floor, not necessarily questions, but also comments. One, you know, have you ever shared? Have you ever shared content online that turned out to be AI generated without knowing?

Two, what do you think the biggest threat to information integrity in Europe is? Three, do you think? AI -generated content can always be visibly labeled? And are you aware of any technologies like C2PA or SynthID? And do you think they can actually solve the problem? Additionally, who do you think should be responsible for enforcing AI labeling? Should it be governments? Should it be platforms? Should users do it themselves when they publish it? We’d love to know. Thanks so much.

Francesco Vecchi

Thank you again, Frances. And let me just build on that. Yes, we already have questions from the remote hood. So not from remote audience, but if I could make my…

On-site participant

My name is Inej. I’m here with Ustick. And I was really intrigued by the question and the comment that you made on the biggest threats for disinformation here in Europe. And I do think that AI and especially deepfakes can play a role with that. Thank you. especially because they allow for it to be easier to manipulate certain images and if I can give you a bit of context I’m from Portugal and in Portugal during the last legislative elections there was just one party who was responsible for around 80 percent of misinformation that was spread online about the elections and I’ve also seen this party for example in their own newspapers sort of that they have share images for example that were fake I don’t know if they resorted to AI but it’s possible and it would make it easier of course sorry and I think this is also one concern that we need to take into account which is the role that even political parties are also playing in this and that even themselves have a responsibility not to use these technologies to produce their content if they want to be taken seriously and if they actually care about protecting our democracies.

Thank you and sorry about the voice.

Francesco Vecchi

No worries. We know the youth big program can be intense. Thank you very much. And I would strongly encourage everyone in the room to have the same approach. So please. OK, see one hand raised there in the end.

On-site participant

Hi, I’m Hurya Mameti. I come from the Action for Democratic Society, within which it’s also a hybrid info fact checking outlet in Kosovo. We deal a lot with AI generated content, especially during the times when important things are happening like elections. And we debunk many of those content being published. One of the things that we’re seeing now is. That there are being published AI generated content. I mean, all AI, even people that do not exist. and trying to actually influence to the audience, to the citizens of Kosovo when voting. They are kind of doing these interviews, putting, publishing images. When you see, let’s say, a logo of known media but with different colors or you see different things that are being within the AI -generated content, and you see that citizens believe those, even though those interviews do not really exist and they kind of try to tend to give the information that they support a political party or a specific candidate.

But beside this, we are seeing now that it’s known like slopaganda, so it’s the weak content that is being all AI -generated published and mostly related to politicians. Like we see images or videos of politicians. Politicians dancing, something that is not normal. On the other hand… As an organization, what we’re trying to do in Kosovo is gathering all the main actors, especially from media, academia, civil society, and public institutions, to at least, since we still don’t have AI law, and, of course, we deal with AI mostly according to European Union laws. But what we’re trying to do is to at least integrate AI within internal regulations, especially to the media, but also to the media to be transparent and put a watermark whenever an image is AI all generated.

Because sometimes even if they publish an image that is AI generated just to kind of show what they want to do with the article that is being published, but at least the citizens still believe it. So another point out is that what I think that it’s more risky now is, I don’t know, The pages, especially those accounts on social media that they publish this AI -generated content, when we talk about emotional disinformation, let’s say, just to get reactions or comments from the people, but the risk is that we don’t know who stays behind them. There is no data. There are not official media registered. They just tend to represent themselves as media just by putting a .info or news and a name that people believe, and you don’t know how to actually know who stands behind them and who is the one that’s publishing all this disinformation, especially generated with AI.

Francesco Vecchi

Thank you very much for your contribution. Anyone else who would like to take the floor, please?

On-site participant

thank you very much uh my name is it the beckall i’m joining from the council of europe’s anti -discrimination department there’s a lot of food for thought and also very interesting intervention right before me i wanted to also connect to this and what Frances you were asking about uh user uh reliance and whether we’re shifting too much of this responsibility to people and i wanted to bring a point that uh perhaps it is indeed too much responsibility for individuals and and the way to go forward is to shift this responsibility more to uh state’s positive obligations to ensure a um a user safe online environment and of course not only here platforms are responsible but also when it comes to the regulation of synthetic media um private actors must act i mean we talked about google’s water marking system and there’s a lot of innovation going on but states cannot outsource this responsibility to media governance to private companies, in our opinion.

And labeling, watermarking, and moderation policies are not enough unless they’re sitting in a public interest framework. So here, we believe that the state’s role should be to define these clear rules, manage the risk assessment, and ensure the transparency, but also create independent oversight and give researchers and regulators access to information and guarantee remedies for ensuring this environment. And the Council of Europe recently published a committee of ministers’ recommendation, and this specifically addresses online safety and how online safety should be part of enabling an online environment, and it should be accessible without any discrimination, and it should be inclusive and safe and pluralistic. And here, we really enforce the idea of a positive obligation, and perhaps to connect this to an earlier point on the risks.

I think for people who are not technical experts, this conversation can get very confusing, and I myself am not a technical expert as well. But I think it’s perhaps better to view transparency as not sort of an isolated technical obligation, but also within this human rights framework. And I don’t think transparency should be treated as an end in itself, but it should serve accountability and equality and access to redress. And what I think we see with these labeling, there are some questions that I’m also curious to ask the presenters. We often present them, you know, as technical solutions to misinformation, but what happens when these systems fail? The watermarking mechanism itself can become a target for manipulation as well.

And when these failures occur, whose content should become less trans? They’re trusted. Who do we give? the responsibility to, and also whose voices become the most easier to dismiss. Because, unfortunately, labeling a content as AI -generated doesn’t necessarily remove the discriminatory impact that content creates on the online environment, and we have examples of this as well. For example, there was a research, I think, in the UK Parliament that found that AI -generated anti -immigration imagery was circulating online, but even though it was marked as AI -generated, it was nevertheless amplified by the algorithm of that platform, and it reached millions of people. So, I would also be interested, I think Pascal had mentioned that it shouldn’t be on, it should be independent from the states, and perhaps that’s a way to ensure, you know, the independency.

And besides, you know, the independent oversight of this besides any governmental or political view, but I would be curious to hear if it should only stay within the private sphere. Thank you.

Francesco Vecchi

No worries at all, I think they were extremely interesting points before opening the floor for other questions just one second, I also believe it is important to get reminded of what does AI generated mean, you know, in a context where probably every one of us is massively using AI to support their work where do you draw the line of something which is AI generated or not of course, I mean, there are some cases where it is clear that you can use the term in other cases, less clear, so how do you regulate on that and the second point is let’s not forget that within the Digital Services Act, there is the code of practice on this information namely something that every company can willingly accept to adopt within their practices, but the point is that it was published before the real age of AI, so probably part of the conversation can be also discussing how can we adapt, renew the code of practice this kind of call of practice for the context we are living in.

Before leaving the floor to the lady there, I just wanted to check if there’s any question from the room, from online. No?

On-site participant

Thank you very much. I come from Armenia, from the Prosecutor General’s office. I very much wanted to kind of continue on what the Council of Europe colleague mentioned, and also one of the questions that arose, what exactly air -generated content are we speaking about? I think it’s extremely important that the states have some role in terms of regulation, but there is a fine line between, I mean, how that interference should be regulated not to violate human rights to freedom information, the private companies, and I think it’s very difficult to understand. Thank you. balanced approach, but apparently it should be a balanced approach. But another aspect I wanted to very much raise is the cooperation amongst the states, because if the regulation differs very much from country to country, it will be extremely difficult, especially to control.

I mean, the AI -generated content may be established anywhere, and then if the regulations are very different, it’s going to be extremely difficult to have a unified approach. So perhaps cooperation amongst the states is one of the things that should be emphasized when we speak about the state’s positive obligation, because otherwise it’s going to be extremely difficult to have somewhat unified approach. So this was something I wanted to raise from that perspective. Thank you. Hello. I’m just curious. Hello. I’m Jessica from ETHDIC, and I also wanted to build on… The point that was just raised of the unified approach, I think that it’s incredibly important that we work together as European countries. And we’re very good at this already.

We work together very effectively through the DSA. We work together very effectively on the DSA to the various organizations, for example, the European Board of Digital Services Coordinator. And I think that under the AI omnibus, when all of the European regulators are empowered to enforce these AI regulations, that we can continue this great cooperation. And my further point was also about kind of the opportunities and escalating harms to do with AI generated content, that there’s great opportunities in terms of our AI innovation. There’s opportunities for economic growth, for global connectivity, for AI driven productivity. Also. For education and civic participation. There are also the harms of algorithmic amplification of toxic content of AI. gender -based image abuse and also mis – and disinformation.

And I suppose the point is that we can’t just frame these as two trade -offs, that we must frame the challenge as not choosing one over the other, but building a system of governance that maximizes both the risks, that maximizes the opportunities while preventing and mitigating the systemic risks. Thank you.

Co-moderator

So we have a question from Olga Martinez in the set, and then we have a hand from Pascal, so I will first tell the question from Olga. The question is, are we overstimulating transparency as a solution when emotionally manipulative content can still be highly effective, even if users know it was AI -generated? I guess that giving the floor to Pascal is the perfect way of getting an answer to the question, so Pascal, would you like to take the floor again?

Pascal Schneiders

Perhaps to pick up the question just from before, I think certainly a holistic, bigger picture perspective is important here because as already mentioned, AI systems influence not only individual and public decision making and opinion formation but also the production and visibility of quality of information or of public relevant information in general. So we should take a holistic governance approach to make, to ensure that news media still have a viable future and can should be financed or subsidized for example by digital also by digital platforms or other funding instruments to yeah, to ensure that we also in the future can may have access to quality information. And as we know from research, for example, by Sascha Altai and Rasmus Kreis -Nielsen and Richard Fletcher from the Reuters Institute in Oxford, ensuring and funding or strengthening news media is the best way to fight misinformation because news media or making use of news media ensures people have access to other perspectives and have access to the possibility, capability to develop their resilience and to be inoculated or to be immune against misinformation.

And research clearly shows a positive. correlation between using news media and not believing misinformation. So that means we should. strengthening news media because of that correlation and not only look at the labeling negative or misleading content, but also taking the funding perspective of journalism and news media. And in regard to the oversight governance bodies, for sure I would also agree that those states independent oversight bodies should represent the pluralism of society. So to make sure that’s not, yeah, to prevent discrimination or to prevent the acceleration of discriminant perspectives or misleading content. So that’s something that we also have or know from the public service media in Germany. They are, yeah, they have oversight bodies which more or less try to represent the heterogeneity of society.

So I think that’s a way we could also follow with regard to digital platforms and AI -generated content.

Francesco Vecchi

Thank you very much. I’m just a bit conscious about time, so we’ll get one last intervention from the very back. I think the lady raised her hand first, right? And then I think we go to the messages, so please.

On-site participant

I’m Liliana coming from North Macedonia, from the Balkan region, and NGO. So basically, sorry, I just missed the beginning of the session. I do hope that you discussed it previously as information integrity becoming a part of the cybersecurity or not. So I would want to draw the attention to the information integrity part of the cybersecurity part of the cybersecurity. to this, let’s say, interdisciplinary approach. We’re entering really a period where AI -generated, AI content is really becoming… or lowering the cost of influence operations and developing different synthetic content production. I don’t think it’s becoming already just a media issue or just a disinformation issue. It’s becoming more of a global security issue, not only regionally but globally.

So basically, I’m wondering what kind of governance models are there or tools to fight and to be around information integrity and keeping it up or protecting the information integrity as we saw it on the Mentimeter. Because in smaller states and developing digital ecosystems, we don’t have the institutional capacities that could respond to this type of threats. Was there a discussion that disinformation integrity could be part of this? Part of the cyber resilience frameworks maybe in your countries? in the region, or it could become as a different approach. I’m just wondering of the tools and the approaches that were discussed or taken. So in that segment, I would want to also emphasize what we did in order to be resilient.

We designed our own software tool where we could actually assess and measure the manipulation level of what is presented from the government itself or from the media. And in that kind of situation, we found ourselves to be in between, fighting with both or sometimes three party instead. And that is very tiring, to be honest. To a certain point, it’s tiring and it’s time consuming, and it’s not cost effective for us because it doesn’t… It doesn’t bring us projects or money, it’s just bring us the truth. which is, we say, the most valuable thing at the end, trustworthiness of information. It could bring the good case and the criminal prosecution as it should be and security at large.

However, it is pointless at the end of the day. Nobody cares about the truth anymore because whether you’re presenting it, it’s just you’re fighting with the big, but it’s a different parties and stakeholder. So what are the tools and mechanisms you are applying and what are the governance models that are already there and whether we do keep pace fast enough to grab what is going to be in the future as generative AI is really fast growing. Thank you.

Francesco Vecchi

Thank you very much as a representative of civil society i cannot but agree with most of what you said just uh very briefly let’s remind that now i mean today we mentioned the dsa of course these kind of topics are also touched by the fight against disinformation uh initiatives at the european commission so it’s like one of the tools of a foreign policy and we know that exactly cognitive sovereignty is a cause is a question also of defense and security and for again we can approach the topic from different perspectives but at the end of the day they must be intertwined if we want our messages to be relevant in any way that said i fear that we are running out of time and we still have to agree on the messages so unless maybe i don’t know if uh gabby i want to some final remarks before going to the messages or ….

Gabija Skučaitė

Hello. So my name is Gabija Skučaitė I’m from Lithuania. I’m representing Academia, a group of educational institutions. So what I’m hearing today that we live in the world, which with my colleague, Professor Mehmet Urgai, we are calling times in between where liquidity, modernity is blurred and when nothing is true or false anymore. So it is difficult to distinguish what is true. Or maybe we can label everything and still we will be not sure. So this AI -saturated environment put all humanity and society in a very different position where we need to come back to what is really humane is the ability to make sense by human capabilities of what is true and what is false.

So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. So I think that’s what I’m hearing today. very much matter in this regard, in which context I see this information, which is given to me and by whom it is given to me. So I believe that we need to put more attention to raising awareness of AI algorithms, of sense -making in the age of AI, and here academia must take a really big role in this regard because we need to educate people, young generation, to make sense of the world, which is real, actually, because we live in the real world, and the world is alive and real.

We just have this meta -environment, some virtuality, which is part of our lives. So to distinguish this is a very humane capability, which we need to embrace by ourselves, which is within us, it never went away. We just… live in a little tricky environment and I I think we will be aware of this, and the labeling will not, you know, solve everything we as humans with human capabilities will. Thank you very much.

Francesco Vecchi

So before leaving the floor to the messages, because we’re running out of time, I thank Pari Esfandiari for sharing their thoughts to the chat. I’m afraid I came a bit late, but of course Pari points out that the problem is the social trust, and especially if we live in this kind of postmodernist historical novel where no one knows where to draw the line between fact and fiction, then of course trust in institutions and trust in educational institutions first and foremost is crucial to ensure information integrity. That said, without further ado, I leave the floor to Smee for the messages. Just let me remind you that the messages of your in general and even more those of the workshops, they need to reflect broad consensus of the room.

So I will let me explain how to interact with the messages and how they were drafted, but please remind that they reflect the broad consensus of the room and please just raise your hand if you strongly object to any of the messages. Share them now. Please.

Smee Cujic

So first apologies to the person who’s way behind me since I cannot face the call room. As my colleague said, please do not pay attention to comas or the full stops. We just want to talk about what generally came out during the session. So first message, A&E face of threats for information integrity. is increasingly being used during political campaigns. I see even nodding. Thank you. Next one. Responsibility should not be only on users, but states, media, and political parties themselves. States have a positive obligation. Silence. Good. Next one, a bit longer. While labeling needs to be put in the framework of interests of… It doesn’t address discrimination, unjust interference, or social harm. AI contact is already reshaping our beliefs.

It may be that AI contact, which is labeled, does not introduce greater clarity. There is a bias where unlabeled information is automatically perceived as high quality or truthful when, in reality, it may be entirely inaccurate. At the same time, labels are interpreted differently based on personal setting and critical engagement. We also need to raise awareness and human sense making of air -generated approaches. quite a long one, but I have the content. S

Francesco Vecchi

orry, just to double check, I saw that the person over there switched on the microphone a couple of times, just wanted to say did you want to say anything?

On-site participant

Yeah, it was about the point number two would it be possible to include private companies as well in this list of people? So state media, well, technology companies?

Francesco Vecchi

Yes, I think is there anyone in the room strongly objecting again to adding private in the phrase? Okay. Okay, so a few hands raised, also people that didn’t have the chance to speak before. So in general, please, if you want to take the floor, use it through the microphone, otherwise they cannot hear you remotely, so please.

On-site participant

sorry yeah if if i’m sorry i arrived late i’m uh from european fact -checking standards network efcsn i would have lots to say but i’ve and i’ve missed that train uh just if we add in all specific actors can we mention civil society organizations in that number two because they’re unless anyone’s opposed to it i agree thank you yeah my mic mic is working um i was wondering if then in this aspect we can take out political parties i i find it a bit colloquial because i think the obligations on the political parties should anyways be determined by state obligations uh unless you’re not sure if you’re not sure if you’re not sure if you’re

Francesco Vecchi

I would disagree on this, I’m sorry but I not all political parties become really part of the state some political parties and movements are not even officially recognized and in most cases it is indeed political parties that spread misinformation so I probably would rather keep the framing as it is but if anyone else has a strong objection again we can discuss about it. OK?

On-site participant

Sorry just because we were talking about this different institutions the nation state, identity providers and the transnational organizations because somehow everybody wants to have this this this this topic together, but I’m not sure whether only the tech companies are involved in the governance topics. Even though you have objections about political parties, I guess there are three actors because all these tech companies are kind of, they are intervening our knowledge and our space so that they can have different roles. And we talked a bit about governance as a post, like labeling as post topics, but not prevention related topics and governance and oversight is not only happening with the citizens. That’s why maybe we want to bring the civil society, everything in a three -way action.

It’s like private company without mentioning private companies, but if there are any objections, then it’s okay. Can I just intervene? I think the regulations in different countries whether civil society organizations, NGOs, are considered private or not. So I think, for me, if we start counting the risk is that we may miss very many that are regulated differently in different countries. So I would suggest keeping it as general as possible but providing the functions. For example, organizations that do have regulatory functions. So this way we will ensure that we do not miss any important organization from the list. So that would be my suggestion. Governmental organizations and private, I think, and NGOs, all other types may be included in any of this.

That would be my suggestion, not to narrow down.

Frances Douglas-Thompson

So you’re saying anybody that has government power over this issue? How would you phrase it in this number two? Perfect. Should we… We’ll put that in another week and I think come back to that when we go through. Yes, if I remember correctly, there will be still time to edit the messages after the conference. So in case there are still some disagreements, just quickly the last two points just to check if there’s protocols.

Smee Cujic

Okay, so we have number four. Technological approaches are fragmented at current. Is that the technological approaches are fragmented at current? Or currently?

Francesco Vecchi

At the time being, I think. No, at the time being.

On-site participant

Is it meant that technological approaches differ from country to country? What is the idea?

Frances Douglas-Thompson

Again, across platforms, but also country to country. For example, we talked about Google, but we don’t see similar technologies emerging necessarily. Maybe we just mentioned like that.

Francesco Vecchi

Okay, while we correct that, let’s go to the fifth one. Cooperation between states requires a more unified approach. Air material is generated globally, and we see vastly different approaches across jurisdictions.

On-site participant

Can I just suggest one thing as far as the point five is concerned? Cooperation and regulatory frameworks between the countries. I think it’s very important that regulatory frameworks are also aligned to the extent possible.

Francesco Vecchi

yeah personally I love the concept of interoperability but let’s see you know not necessarily homogenous but at least interoperable with one another okay any other strong objection then I would

On-site participant

to the point four I missed the beginning the technological topics other than Google have you talked about that because there are execution time authority one of the technologies but they can be used only via the big tech companies and government can propose a policy to use these technologies but it’s very recent and I’m not sure whether anybody is aware of this technology

Francesco Vecchi

Okay, then I thank you all for participating I think that the messages are extremely interesting and the conversation itself was definitely rich Thank you again for coming here today and let’s keep in touch also if you want to propose little changes in the next few days there will be still time to correct the commas, but I’m also happy to get to a broad consensus on the topic. Thank you again.

Related ResourcesKnowledge base sources related to the discussion topics (19)
Factual NotesClaims verified against the Diplo knowledge base (8)
Confirmedmedium

“The earlier YouthDig message had called for visible markers when AI is operating, youth input into ethical guidance and transparency regulation, AI literacy in school curricula, and impact and risk assessments for AI systems.”

This is broadly consistent with YouthDIG-related and AI-governance material in the knowledge base. Youth participation in digital policy is explicitly emphasised in YouthDIG discussions [S93] and [S98], while AI literacy, transparency, and impact assessment are all reflected in UNESCO’s AI ethics framework [S100].

Confirmedhigh

“The present session focused especially on synthetic media and transparency ‘at the point of consumption’, and that labelling/watermarking helps but is not sufficient on its own.”

The knowledge base strongly supports this framing. It explains that detection alone is insufficient, that provenance and visible signals matter, and that users often rely on labels when making quick trust judgments about content [S27]. It also states that trust will not be preserved through perfect detection or regulation alone, but through a combination of technical systems, ethical norms, resilient institutions, and citizen capacity [S90].

Confirmedhigh

“AI literacy should include understanding how AI works, how algorithms shape exposure, and where human oversight needs to remain.”

This is directly aligned with the knowledge base. AI literacy is described as needing to go beyond tool use to understanding data, algorithms, outputs, and the risks they pose [S103] and [S105]. UNESCO also highlights transparency, explainability, public engagement, education, and human accountability as core AI-governance principles [S100].

Additional Contextmedium

“Young people and users also need to understand regulation, not only technology, if they are to navigate information quality and integrity.”

The knowledge base supports the broader idea that effective information integrity depends not just on technical understanding but also on governance and policy frameworks. It stresses that regulation, institutional resilience, and shared responsibility across creators, governors, and citizens are all necessary [S90], and that broad consultations with states, civil society, experts, and platforms are part of developing information-integrity governance tools [S36].

Additional Contextmedium

“Janice linked this to the 2025 Democracy Shield, describing its core objective as quality and integrity, stopping interference from other countries in elections, and building the resilience of young people through digital literacy.”

The knowledge base does not specifically verify the 2025 Democracy Shield, but it does corroborate the substance of the policy goals described: protecting democratic governance from disinformation and interference, especially around elections, and strengthening resilience through media or digital literacy [S91] and [S92].

Confirmedmedium

“Europe was described as people-centric, grounded in safety, rights, and values, and oriented towards strategic autonomy and digital sovereignty through a precautionary, risk-averse approach.”

This characterisation matches the knowledge base’s portrayal of European digital governance. EU and Council of Europe-oriented materials emphasise fundamental rights, trust, transparency, safety, and strong governance frameworks [S96] and [S97]. UNESCO-aligned material in the knowledge base also reflects a rights-based, precaution-sensitive approach to AI governance, with human rights, dignity, fairness, oversight, and impact assessment at the centre [S100].

Confirmedhigh

“Technical transparency measures such as watermarking and labelling may help, but they are not sufficient on their own and need to be considered alongside literacy, resilience, governance, and changing user behaviour.”

This is strongly corroborated. The knowledge base states that provenance tools and labels can help, but they have clear limits and are most effective when paired with resilient institutions, ethical norms, and citizens who learn to question content carefully without assuming everything is fake [S27] and [S90].

Additional Contextlow

“The session was framed as a continuation of an earlier YouthDig message because the information environment keeps changing and policy ideas need to be revisited rather than treated as fixed.”

The knowledge base supports the broader factual premise that fast-changing AI and information environments require ongoing reassessment of governance responses. It describes AI governance as requiring constant revisits based on technological developments and societal responses [S46], which adds context to the report’s description of revisiting prior YouthDIG messages.

External Sources (105)
S1
EQUAL Global Partnership Research Coalition Annual Meeting | IGF 2023 — Chung Park Speech speed 101 words per minute …
S2
K. H. Onarheim — K. H. Onarheim
S3
Shkendije Geci — Shkendije Geci
S4
Sandboxes for Data Governance: Global Responsible Innovation | IGF 2023 WS #279 — Thank you. Thank you. Thank you. Thank you. Speakers Agne Vaiciukeviciute Speec…
S5
Liene Norberg — Liene Norberg
S6
Francesco Calabrese — Francesco Calabrese
S7
Vitali Francesco — Vitali Francesco
S8
Work for a brighter future — Professor General for Human Resources and Social Policy Chung has also served as Member of the UN …
S9
Frances Cairncross — Frances Cairncross
S10
Drew Thompson — Drew Thompson
S11
Work for a brighter future — Professor General for Human Resources and Social Policy Chung has also served as Member of the UN …
S12
[GUIDE] Who should be on your organising team? — Who are the key people you need to organise and run a meeting or event? Generally, a moderator (or host) is always requi…
S13
IGFSA | SIDE EVENT — Speakers and Moderators Amrita Choudhury, the Director of CCAOI, Treasurer of Internet Society India, Delhi Chapter an…
S14
Sandra Bart — Sandra Bart Legal Officer, CARICOM Secretariat I found the discussion on the role of Moderator to be especially useful. …
S15
Milan Vučković — Milan Vučković
S16
Nenad Milićević — Nenad Milicevic https://diplo-media.s3.eu-central-1.amazonaws.com/2024/04/Nenad-Milicevic.jpg Mr Nenad Milićević is a jo…
S18
Pascal Marmier — Pascal Marmier Secretary General, Economy of Trust Foundation, SICPA https://www.diplomacy.edu/wp-content/uploads/2021/0…
S19
Thomas Schneider — Thomas Schneider is ambassador and director of International Affairs at the Swiss Federal Office of Communications (OFCO…
S20
Main Topic 3 – Innovation and ethical implication  — These ethics are envisioned to establish a framework that enhances the beneficial facets of AI while mitigating its inhe…
S21
Janice Gross-Stein — Janice Gross-Stein
S22
Janet Welsh Brown — Janet Welsh Brown
S23
Jana Mišić — PhD candidate in Ethics and Technology https://dig.watch/wp-content/uploads/Jana-Misic.jpg Ms Jana Mišić is a Marie-Curi…
S24
The power and limitations of visual metaphors — I usually communicate by drawing. This time, I will write a text. There is a saying that one picture conveys a thousand …
S25
The price of ignoring context in problem-solving — Facebook criteria for ‘friendship’ replace personal exploration and validation of personal encounters. As children swap …
S26
How does identity impact segregation? — ‘Identity politics is back’, opines a comment to my blog post The Trump Swerve. I admit to having difficulties with the …
S27
Certifying humanity: Labeling content amid AI flood — For much of the public debate around artificial intelligence, attention has been fixed on capability: how powerful model…
S28
Day 0 Event #12 Tackling Misinformation with Information Literacy — There’s usually a kernel of truth in this with a lot of misinformation around it, which makes it a lot trickier for t…
S29
Rethinking learning: Hope, solutions, and wisdom with AI in the classroom — Some intellectual struggle is essential for development. This might mean specific assignments done without AI assistance…
S30
AI in schools: The reality is messier than the solutions — As the school year is in full swing, the issue of AI in schools and education keeps coming up everywhere. Teachers share…
S31
AI and the wisdom of generations — The design of AI systems is often framed in terms of innovation, efficiency, and speed. However, these metrics alone can…
S32
WS #376 Elevating Childrens Voices in AI Design — while AI is outpacing that system entirely. Rather than banning AI in schools, we should teach students how to use it ef…
S33
AI promises, ethics, and human rights: Time to open Pandora’s box — In 2021, I participated in the Artificial Intelligence online course offered by Diplo. In one of our online sessions, a …
S34
Protecting the Vulnerable Online — Furthermore, it is argued that platforms should prioritize user safety from the beginning by designing their products wi…
S35
Time to (re)take responsibility — It’s not a gun that kills someone; it’s the person who pulls the trigger. It’s not Facebook or e-mail that ruins people’…
S36
Information Integrity on Digital Platforms | Our Common Agenda Policy Brief 8 — Available at https://ec.europa.eu/commission/presscorner/detail/en/mex_23_723. DIGITAL PLATFORM RESPONSES Digital…
S37
Hidden in plain view – I — It’s obvious (and efficient): we humans communicate differences and presume commonalities. When I speak I do not begi…
S38
Online Choice Architecture: How digital design can harm competition and consumers — Evidence from consumer complaining behavior. Marketing Science, 39(1), 168-187. 153 Federal Trade Commission (FTC). …
S39
Main Topic 3 –  Identification of AI generated content — Importally, the moderation included a mention of Mr. Katkus, who, due to traffic disruptions, could not participate. Thi…
S40
Fake news: what’s behind the media frenzy — In fact, the walls of these echo chambers can be so thick that ‘any misinformation spreads almost instantaneously within…
S41
Day 0 Event #256 Truth Under Siege: Tools to Counter Digital Censorship — And we experimented with different ways of creating content, but what gave us more successful or impact was the initiati…
S42
WS #300 Information Integrity through Journalism & Alternative Platforms — It’s not about states talking to each other. It’s about everybody being involved. It’s inclusive, human rights-based, hu…
S43
Regulating social media: a multistakeholder ‘content congress’ — You do not have to be a fan of conspiracy theories to worry about the precedent that Apple, YouTube and Facebook set by …
S44
Is the journalist a scientist or an artist? — Too smart to serve In short, this text doesn’t mean to support the dummies against the learned; it rather tries to mon…
S45
Review of AI and digital developments in 2024 — From TikTok’s innovative Election Centre for EU states to Meta’s robust Elections Operations Centre and Google’s Jigsaw …
S46
Four seasons of AI:  From excitement to clarity in the first year of ChatGPT — How to address AI risks   There are three main types of AI risks that should shape AI regulations:  the immediate a…
S47
Meta Platforms develops labels for AI-generated content — Meta Platforms is developing labels that allow creators to identify images produced using their AI technology. Alessandr…
S48
Ethics and AI | Part 6 — The European Union AI Act: calling a spade a spade The EU Artificial Intelligence Act Another “first” is the Euro…
S49
Governments vs ChatGPT: Regulation around the world — ChatGPT, the AI-powered tool that has taken the world by storm, has now caught governments’ eyes. In reaction to user co…
S50
Human rights — Clear frameworks for accountability and oversight are necessary to address issues arising from AI’s use. 5. Legal and R…
S51
AI and Digital in 2023: From a winter of excitement to an autumn of clarity — As human rights issues are increasingly brought up in standardisation discussions, there will be a push for human-rights…
S52
AI and international peace: A new kid on the UN Security Council block — The UN Security Council had its first meeting on AI and international peace and security. Having in mind that diplomacy …
S53
WS #255 AI and disinformation: Safeguarding Elections WS #255 AI and disinformation: Safeguarding Elections Session …
S54
Information Integrity on Digital Platforms | Our Common Agenda Policy Brief 8 — The Code of Conduct may draw upon the following recommendations: Commitment to information integrity All stakeholde…
S55
Certifying humanity: Labeling content amid AI flood — For much of the public debate around artificial intelligence, attention has been fixed on capability: how powerful model…
S56
Meta revises AI labels on social media platforms to balance transparency and user experience. — Meta’s decision to change how it labels AI-modified content on Instagram, Facebook, and Threads signifies another advanc…
S57
The EU on Internet governance: Strong on description – Weak on prescription — The third important question addresses conflicts of jurisdiction and laws. The EU communication is among the first offic…
S58
Day 0 Event #61 Accelerating progress for unified digital cooperation — And yeah, if you look at the ecosystem, not the specialized cloud service providers, but also the operators increasing…
S59
Workshop 2: The Interplay Between Digital Sovereignty and Development — The precondition, there are a lot of interventions that are planned. One of them is the so-called Digital Network Act th…
S60
AI and international peace and security: Key issues and relevance for Geneva — Furthermore, these actors can engage in research and capacity-building initiatives that promote understanding of AI tech…
S61
AI diplomacy — Privacy and data protection are particularly pertinent, given that AI systems often require massive datasets, which can …
S62
A Global Digital Compact – an Open, Free and Secure Digital Future for All | Our Common Agenda Policy Brief 5  — States are also exploring legally-binding arrangements to tackle criminal threats as well as capacity for governments an…
S63
Artificial intelligence: policy implications — robots): should they be regarded as natural persons, legal persons, animals or objects, or should a new category be crea…
S64
What Proliferation of Artificial Intelligence Means for Information Integrity? — They suggest watermarking requirements for AI companies as a specific solution. Evidence Referenced Romania’s recent…
S65
Fake or advert: between disinformation and digital marketing | IGF 2023 Networking Session #171 — A noteworthy observation is the value of bringing local business organizations together as part of broader coalitions to…
S66
Public Diplomacy and Nation Branding: Conceptual Similarities and Differences — While nation branding can be easily translated into many languages, public diplomacy may cause some problems. Several co…
S67
What’s new with cybersecurity negotiations? UN Cyber OEWG Final Report analysis — The UN’s Open-ended Working Group (OEWG) on Developments in the Field of ICTs in the Context of International Security (…
S68
Rhetoric — Diplomats seeking to analyse political rhetoric can benefit from knowledge of the terms and techniques of classical rhet…
S69
WS #300 Information Integrity through Journalism & Alternative Platforms — Evidence Shared personal experience of working for major outlets like New York Times, LA Times, BBC, CBS News and bein…
S70
Digital sovereignty: The end of the open internet as we know it? (Part 1) — In the context of an offensive and chauvinist turn in US policy, the popular magazine The Economist suggested a range of…
S71
Navigating the interplay between artificial intelligence, philosophy, education, and governance — Overview The rapid development of artificial intelligence (AI) presents profound philosophical, educational, and gover…
S72
From summer disillusionment to autumn clarity: Ten lessons for AI — Table: Survey of AI risks evolution August 2023 August 2024 August 2025` Longtermism, the ph…
S73
Review of AI and digital developments in 2024 — From TikTok’s innovative Election Centre for EU states to Meta’s robust Elections Operations Centre and Google’s Jigsaw …
S74
IGF 2023 WS #313 Generative AI systems facing UNESCO AI Ethics Recommendation — They argue that young people need to be educated about generative AI to be informed users. This highlights the importanc…
S75
AI in 2026: Learning to live with powerful systems — This does not mean constant suspicion, but a more informed form of scepticism. Just as society adapted to earlier waves …
S76
Certifying humanity: Labeling content amid AI flood — For much of the public debate around artificial intelligence, attention has been fixed on capability: how powerful model…
S77
Meta Platforms develops labels for AI-generated content — Meta Platforms is developing labels that allow creators to identify images produced using their AI technology. Alessandr…
S78
Meta revises AI labels on social media platforms to balance transparency and user experience. — Meta’s decision to change how it labels AI-modified content on Instagram, Facebook, and Threads signifies another advanc…
S79
Youth and media literacy: EU – US lessons and practices — In Where policy and practice collide, Monica Bulger et al. point out that they thereby transcend the administrative and …
S80
Day 0 Event #12 Tackling Misinformation with Information Literacy — She notes that platforms are often criticized for both over-censorship and under-moderation. Major Discussion Point …
S81
Ethics and AI | Part 6 — The European Union AI Act: calling a spade a spade The EU Artificial Intelligence Act Another “first” is the Euro…
S82
Human rights — Clear frameworks for accountability and oversight are necessary to address issues arising from AI’s use. 5. Legal and R…
S83
AI and Digital in 2023: From a winter of excitement to an autumn of clarity — As human rights issues are increasingly brought up in standardisation discussions, there will be a push for human-rights…
S84
Governments vs ChatGPT: Regulation around the world — ChatGPT, the AI-powered tool that has taken the world by storm, has now caught governments’ eyes. In reaction to user co…
S85
Main Topic 4: Transatlantic rift on Freedom of Expression — May I ask for a bit of feedback if I am audible well? Yes, you are. You can continue. Thank you. So, there is a European…
S86
AI and international peace: A new kid on the UN Security Council block — The UN Security Council had its first meeting on AI and international peace and security. Having in mind that diplomacy …
S87
Information Integrity on Digital Platforms | Our Common Agenda Policy Brief 8 — The spread of mis- and disinformation can undermine public trust in electoral institutions and the electoral process its…
S88
WS #255 AI and disinformation: Safeguarding Elections WS #255 AI and disinformation: Safeguarding Elections Session …
S89
Top digital policy developments in 2019: A year in review — In the second half of 2019 several steps were taken towards implementing the Call. The Global Internet Forum to Counter …
S90
Deepfakes and the AI scam wave eroding trust — Doing so requires more than better detection tools. It calls for technical systems that give genuine content a clear sig…
S91
Tackling disinformation, protecting democratic governance: Challenges and opportunities — The mechanisms behind disinformation vary by context, therefore, addressing the problem requires not only reactive one-s…
S92
High Level Leaders Session 2 | IGF 2023 Table of contents Knowledge Graph of Debate Session report Speakers D…
S93
Intergenerational dialogue – YOUthDIG Messages — And also members of the technical community as speakers. We also actually went outside of our conference room for a bit …
S94
Pre 9: Discussion on the outcomes of the Global Multistakeholder High Level Conference on Governance of Web 4.0 and Virtual Worlds — Let me clarify that the concept is not the Commission concept or even the EU concept. It comes from the discussions in t…
S95
Open Forum #52 Strengthening Information Integrity Through Coalitions — ## Geographic and Linguistic Equity Gaps Yu Jie, an audience member with social media research background, highlighted…
S96
Facilitating an integrated approach to digital issues — Report from the fifth panel of the conference The Internet as a Global Public Resource (29‒30 April 2015). The session b…
S97
Main Topic 2 –  European approach on data governance  — This approach is integral to the overarching data strategy launched in 2020, which aims to fuel economic growth and inno…
S98
Lightning Talk #22 Eurodig Inviting Global Stakeholders — Major discussion point Content Moderation and Information Quality Topics Human rights | Legal and regulatory The…
S99
Young people’s digital responsibility — What would you say if you had to read that on average, children in Europe start to go online at the age of seven? And ho…
S100
Ethics and AI | Part 3 — Since AI begins in the minds of men, it is in the minds of men that the defences of ethics must be constructed 1. UNES…
S101
The year of AI clarity: 10 AI Forecasts for 2025 — 2025 Initiatives: 4. Canada Current Policy: Canada is reviewing Bill S-210, which mandates age verification for…
S102
High Level Session 1: Losing the Information Space? Ensuring Human Rights and Resilient Societies in the Age of Big Tech — We need to have a systemic change within the way we relate. to this digital space. And when talking about transparency, …
S103
Are we copilots or just passengers on ‘AI flights’? — Human agency in the age of AI A few days ago, while boarding a flight, I glanced into the cockpit. It was a maze of sc…
S104
AI as a companion in our most human moments — AI takes this concept further, actively engaging with what we share and helping us identify patterns or contradictions i…
S105
Part 7: ‘Interpretability: From human language to DroidSpeak’ — Thus, the question of governance is rather a question of timing than complexity. Complexity and its relation to the time…
Speakers Analysis
Detailed breakdown of each speaker’s arguments and positions
F
Frances Douglas-Thompson
6 arguments173 words per minute1348 words465 seconds
Argument 1
Visible markers as a starting point, not a complete solution (Frances Douglas-Thompson)
EXPLANATION
She presents visible markers and watermarking as useful initial tools for improving transparency around AI-generated media, but not as sufficient on their own. Her point is that labeling can contribute to better disclosure while still leaving major gaps that require broader discussion and additional responses.
EVIDENCE
She said a YouthDIG message had called for digital services and platforms to use visible markers to show when AI is operating, but immediately questioned whether that is always good, whether it makes content trustworthy, and whether it can actually convey harm [18]. She also explicitly stated that watermarking and labeling synthetic material are probably not a catch-all way to deal with the issue, framing the session as a space to examine those limits [18].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources support the idea that labels can help manage uncertainty but are not sufficient on their own. Provenance and labeling are presented as useful signals, yet their limits are emphasized in cross-platform environments and in high-volume information ecosystems [S27]. Research on misinformation responses also notes that labeling is not a simple fix and remains experimental in practice [S28].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Pascal Schneiders, Co-moderator, On-site participant, Smee Cujic, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Pascal Schneiders, Co-moderator, On-site participant, Gabija Skučaitė, Francesco Vecchi
Argument 2
Labels can help transparency but may create false trust in unlabeled content and are hard to scale across platforms (Frances Douglas-Thompson)
EXPLANATION
She argues that labels may improve transparency signals for users, but they can also mislead people into assuming unlabeled content is reliable. She also highlights practical scaling problems, since labeling technologies are not consistently implemented across platforms.
EVIDENCE
She asked whether watermarking and labeling are feasible, whether they send the right message, and whether they might instead lead users to misunderstand truthfulness by assuming that content without a label is highly reliable [173-182]. She further noted that technologies such as SynthID and C2PA are currently siloed, platform-specific, or easily broken by reposting, showing why cross-platform scaling remains difficult [173][182].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is directly corroborated by evidence that users may infer unlabeled content is true simply because it has not yet been checked, and that people interpret labels in varied ways across contexts [S28]. Additional context from provenance discussions shows that verification signals often break when content moves across platforms, limiting scalability and consistency [S27].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Pascal Schneiders, Co-moderator, On-site participant, Smee Cujic, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Pascal Schneiders, Co-moderator, On-site participant, Gabija Skučaitė, Francesco Vecchi
Argument 3
Technological labeling systems are fragmented and fragile, especially when content is reposted or altered (Frances Douglas-Thompson)
EXPLANATION
She contends that current technical solutions for labeling AI content are not robust enough to function reliably across the wider information ecosystem. Their effectiveness is weakened because they are tied to particular platforms or fail when content is modified or redistributed.
EVIDENCE
She explained that Google’s SynthID is harder to strip away than C2PA but only works for Google-generated AI content, meaning it does not cover other content ecosystems [182]. She also explained that C2PA depends on provenance metadata, but that metadata disappears if images are screenshotted, re-uploaded, compressed, or reshared through social media, making current labeling methods fragmented and brittle [182].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External discussion of provenance systems confirms that metadata can be stripped when content is compressed or recirculated on social media, and that watermarking can be weakened through editing, making labeling systems brittle in real-world circulation [S27].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
On-site participant, Smee Cujic, Francesco Vecchi, Janice Richardson
DISAGREED WITH
Pascal Schneiders, Co-moderator, On-site participant, Gabija Skučaitė, Francesco Vecchi
Argument 4
Youth messages called for AI literacy in schools, including technical understanding and human oversight (Frances Douglas-Thompson)
EXPLANATION
She recalls that earlier youth recommendations emphasized embedding AI literacy in education, not just teaching how to use AI tools. The goal is to ensure students understand how AI functions, what algorithms do, and where human supervision must remain in place.
EVIDENCE
She summarized the YouthDIG message by saying AI literacy should be embedded in school curricula and should cover not only use of AI but also how AI works, how its algorithms function, and where human oversight must be maintained [18]. She presented this as one of the core asks from the youth message alongside visible markers, ethical guidance with youth input, and impact and risk assessment [18].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is reinforced by sources arguing that AI literacy should be a core educational skill, including understanding what AI is and is not, where it fails, and when independent human judgment is needed [S29]. Another source similarly argues that schools should teach students how to use AI effectively rather than ignore its presence, while emphasizing critical thinking and fact-checking [S32].
MAJOR DISCUSSION POINT
Major discussion point 2: Digital literacy, human sense-making, and user resilience
AGREED WITH
Janice Richardson, Pascal Schneiders, Gabija Skučaitė, Francesco Vecchi
Argument 5
Ethical AI guidance and transparency rules should include young people in their development (Frances Douglas-Thompson)
EXPLANATION
She argues that governance around AI should not be designed only by institutions or companies, but should include young people directly. This reflects a participatory approach in which those affected by AI systems help shape the ethical guidance and transparency standards governing them.
EVIDENCE
In reviewing the YouthDIG message, she said that ethical guidance on AI applications should be developed with input from young people [18]. She framed this as one of the principal recommendations from the prior youth process, showing that youth participation was already considered a governance requirement rather than an optional extra [18].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources strongly support youth inclusion in AI governance, noting that young people are affected now and must be part of shaping the technology, not treated only as future stakeholders [S32]. Broader policy guidance on information integrity also says youth should be encouraged and involved in the policy space because they can identify differentiated impacts and flaws in proposed responses [S36].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
Argument 6
Responsibility for safe information environments should not fall only on users but also on states, platforms, media, and political actors (Frances Douglas-Thompson)
EXPLANATION
She raises the question of whether too much burden is being placed on users, especially young people, to constantly judge what is true online. Her framing suggests that responsibility must be shared more broadly across institutions and actors involved in shaping the information environment.
EVIDENCE
She asked whether emphasizing user resilience puts too much pressure on users and young people to constantly understand and determine what is true and false online [191-194]. She also explicitly asked who should be responsible for enforcing AI labeling, listing governments, platforms, and users who publish content as possible responsible actors [203-207].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is supported by sources stressing platform accountability, transparency, and safety-by-design obligations rather than leaving harms to users to manage alone [S34], as well as UN policy material emphasizing platform responsibilities, implementation gaps, and the need for bottom-up user empowerment alongside institutional action [S36].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
AGREED WITH
On-site participant, Janice Richardson, Smee Cujic, Francesco Vecchi
DISAGREED WITH
Pascal Schneiders, On-site participant, Francesco Vecchi
P
Pascal Schneiders
5 arguments105 words per minute1549 words881 seconds
Argument 1
Audience-facing labels have mixed effectiveness because users notice and interpret them selectively (Pascal Schneiders)
EXPLANATION
He argues that visible labels and disclaimers do not work uniformly because users pay attention to them unevenly and interpret them differently. Their impact depends on many contextual factors, so labeling cannot be assumed to reliably improve information integrity on its own.
EVIDENCE
He said there are many different ways to label content and that little is known about how effective labels are in helping people distinguish synthetic from non-synthetic deceptive content [117]. He also explained that people are selectively attentive to warning labels depending on design, usage situation, prior attitudes, experience, topic involvement, and media literacy, showing why audience-facing labels have mixed effects [118][123-125].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External evidence supports this by showing that labels are interpreted differently by users, including ambiguity over what ‘altered’ means, and that their effects vary across generations, cultures, and contexts [S28]. Research on disclosure and online choice architecture similarly finds that transparency and disclosures often do not reliably reduce influence and can backfire through overload or misplaced trust [S38].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Frances Douglas-Thompson, Co-moderator, On-site participant, Smee Cujic, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Frances Douglas-Thompson, Co-moderator, On-site participant, Gabija Skučaitė, Francesco Vecchi
Argument 2
AI labels often reduce trust, but they do not reliably stop people from believing or sharing content they already agree with (Pascal Schneiders)
EXPLANATION
He says labels can trigger skepticism toward AI-generated content, but that does not mean they reliably counter persuasion or sharing. Confirmation bias means people who already agree with a message may continue to believe and engage with it despite warning labels.
EVIDENCE
He stated that detected AI disclosures usually have a negative influence on judgments, indicating an AI-based bias, and gave the example that news items labeled as AI-generated are often perceived as less trustworthy even when not rated as less accurate or biased [119-122]. He then added that people who agree with the content of a synthetic post will most likely not be swayed by labels or prevented from engaging with it, linking this directly to confirmation bias [129-131].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Additional context comes from research showing that awareness and disclosure do not necessarily reduce the impact of manipulative choice architecture, and that consumers may still be influenced even when they know such techniques are being used [S38]. Evidence on misinformation consumption also notes that people often engage with content in emotional or low-attention modes, where truth evaluation is weak and accumulated exposure still shapes belief [S28].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Frances Douglas-Thompson, Co-moderator, On-site participant, Smee Cujic, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Frances Douglas-Thompson, Co-moderator, On-site participant, Gabija Skučaitė, Francesco Vecchi
Argument 3
Inoculation and literacy approaches may be more sustainable than trying to label all deceptive content (Pascal Schneiders)
EXPLANATION
He argues that broad-based literacy and inoculation strategies are more realistic and durable than attempting to label every deceptive AI-generated post. Because the volume of online content is too large and labeling has side effects, resilience-building offers a more scalable response.
EVIDENCE
He described how inoculation works by exposing people to weakened, controlled doses of misinformation and teaching them deceptive techniques through methods such as gamification and AI literacy in schools [145-147]. He concluded that inoculation should be combined with making verified content easier to find, rather than trying to label all AI-generated or AI-assisted deceptive content, which he said is nearly impossible given the amount of online material and the unintended negative consequences of labels [149-150].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is corroborated by external sources highlighting pre-bunking and inoculation approaches as promising responses to misinformation, including exposing users to small bits of misinformation to build resistance [S40]. Other sources emphasize that media and information literacy is essential because labeling alone is not enough and user interpretation remains highly variable [S28].
MAJOR DISCUSSION POINT
Major discussion point 2: Digital literacy, human sense-making, and user resilience
AGREED WITH
Frances Douglas-Thompson, Janice Richardson, Gabija Skučaitė, Francesco Vecchi
Argument 4
A holistic governance approach should support the long-term viability of journalism, not only label harmful content (Pascal Schneiders)
EXPLANATION
He argues that addressing misinformation and AI-generated harms requires more than warnings and labels; it also requires preserving trustworthy information institutions. Supporting journalism is part of governance because healthy news ecosystems help citizens access reliable public-interest information.
EVIDENCE
He said governance should ensure that news media still have a viable future and suggested they may need to be financed or subsidized, including by digital platforms or other funding instruments, so people retain access to quality information [292-293]. He then argued that policymakers should not only focus on labeling negative or misleading content but also on strengthening the funding and sustainability of journalism and news media [296].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources reinforce this argument by stressing the need to safeguard journalistic functions and support media viability as part of a healthier information ecosystem, rather than focusing only on harmful content moderation [S42]. Additional context from trust-and-authenticity debates notes that journalism is particularly affected by synthetic-content uncertainty and depends on maintaining credible institutions [S27].
MAJOR DISCUSSION POINT
Major discussion point 6: Supporting trustworthy information ecosystems, journalism, and security-oriented responses
AGREED WITH
On-site participant, Francesco Vecchi, Gabija Skučaitė
DISAGREED WITH
On-site participant, Frances Douglas-Thompson, Francesco Vecchi
Argument 5
Stronger news media reduce susceptibility to misinformation by providing verified information and exposure to multiple perspectives (Pascal Schneiders)
EXPLANATION
He contends that strong journalism is one of the most effective defenses against misinformation because it broadens access to trustworthy reporting and competing viewpoints. This helps people develop resilience and lowers the likelihood that they will believe false claims.
EVIDENCE
He cited research by Sascha Altay, Rasmus Kleis Nielsen, and Richard Fletcher from the Reuters Institute, saying that ensuring and strengthening news media is the best way to fight misinformation [294]. He also stated that research clearly shows a positive correlation between using news media and not believing misinformation, which he used to support his call for strengthening news institutions [295-296].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
Supporting context appears in sources arguing that trust in traditional news media should be maintained as a quality marker and warning that excessive focus on fake content can itself erode trust [S39]. Broader discussions of balanced responses to fake news also emphasize awareness, education, and fact-checking institutions rather than relying only on suppression [S40].
MAJOR DISCUSSION POINT
Major discussion point 6: Supporting trustworthy information ecosystems, journalism, and security-oriented responses
AGREED WITH
On-site participant, Francesco Vecchi, Gabija Skučaitė
C
Co-moderator
1 argument145 words per minute84 words34 seconds
Argument 1
Transparency alone may not reduce harm because emotionally manipulative AI content can still spread widely (Co-moderator)
EXPLANATION
The co-moderator raises the concern that transparency may be overemphasized as a solution. The point is that even when users know content is AI-generated, manipulative content can still have powerful emotional effects and continue circulating widely.
EVIDENCE
The co-moderator relayed a remote question asking whether transparency is being overstimulated as a solution when emotionally manipulative content can still be highly effective even if users know it was AI-generated [289-291]. This question itself framed the concern that disclosure may not be enough to reduce influence or virality [289-291].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This concern is supported by evidence that users often consume content in emotional or low-attention states where truth is not their priority, yet repeated exposure still shapes belief [S28]. Research on disclosures also shows that making users aware is not always sufficient to protect them from harmful choice architecture or influence [S38].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, On-site participant, Smee Cujic, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, On-site participant, Gabija Skučaitė, Francesco Vecchi
O
On-site participant
13 arguments137 words per minute2692 words1171 seconds
Argument 1
Labeling AI-generated content does not automatically solve discrimination, manipulation, or amplification harms (On-site participant)
EXPLANATION
The participant argues that labeling and moderation are insufficient if they are not embedded in a broader public-interest and human-rights framework. Even disclosed AI content can still discriminate, manipulate, or be algorithmically amplified, so labeling alone does not remove harm.
EVIDENCE
A participant from the Council of Europe’s anti-discrimination department said labeling, watermarking, and moderation policies are not enough unless they sit in a public-interest framework, and argued that transparency should serve accountability, equality, and redress rather than be treated as an end in itself [245-252]. The same participant cited research from the UK Parliament showing that AI-generated anti-immigration imagery circulated online and was still amplified to millions of users even though it was marked as AI-generated, demonstrating that labels do not automatically stop harm [258-260].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources support this by showing that disclosure and transparency alone often do not reduce harmful influence and can even backfire [S38]. Broader information-integrity material also notes that platforms may still amplify lies and hate through engagement-driven systems, meaning labels do not by themselves address structural harms [S36].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, Smee Cujic, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, Gabija Skučaitė, Francesco Vecchi
Argument 2
States have positive obligations to guarantee a safe, pluralistic, and rights-respecting online environment and should not outsource governance entirely to private companies (On-site participant)
EXPLANATION
The participant argues that responsibility for online safety should be anchored in public obligations, not left mainly to platforms or private firms. States must set the rules, assess risks, guarantee oversight and remedies, and ensure that the online environment remains inclusive and pluralistic.
EVIDENCE
The Council of Europe participant said it may be too much to place responsibility on individuals and instead argued that states have positive obligations to ensure a user-safe online environment [245]. The participant added that states should define clear rules, manage risk assessment, ensure transparency, create independent oversight, provide access for researchers and regulators, and guarantee remedies, while also referencing a recent Council of Europe recommendation on an online environment that is inclusive, safe, pluralistic, and non-discriminatory [247-249].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is reinforced by sources calling for stronger regulation, safety-by-design, and accountability rather than relying on self-regulation by platforms alone [S34]. Human-rights-oriented policy guidance similarly stresses platform gaps, the need for transparency and researcher access, and broader governance obligations to protect information integrity [S36].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
AGREED WITH
Frances Douglas-Thompson, Janice Richardson, Smee Cujic, Francesco Vecchi
DISAGREED WITH
Pascal Schneiders, Frances Douglas-Thompson, Francesco Vecchi
Argument 3
Oversight should be independent, transparent, and designed to avoid political capture or discrimination (On-site participant)
EXPLANATION
The participant argues that governance mechanisms for synthetic media should not be controlled in a way that risks bias, capture, or discriminatory outcomes. Oversight needs to be transparent and independent so that failures in moderation or labeling do not unfairly silence or discredit certain groups.
EVIDENCE
The participant called for states to ensure transparency, independent oversight, and access for researchers and regulators, emphasizing that governance should include accountability and remedies [247][252]. The participant also asked what happens when watermarking systems fail, who is blamed when trust is lost, and whose voices become easiest to dismiss, linking weak oversight to risks of discrimination and unfair treatment [253-260].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External material supports the need for transparency in content governance and criticizes opaque moderation systems where companies act as de facto arbiters of speech without sufficient public accountability [S43]. UN policy guidance also highlights persistent gaps in transparency, implementation, and oversight in platform responses to online harms [S36].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
AGREED WITH
Frances Douglas-Thompson, Janice Richardson, Smee Cujic, Francesco Vecchi
DISAGREED WITH
Pascal Schneiders, Frances Douglas-Thompson, Francesco Vecchi
Argument 4
AI and deepfakes increase the ease of spreading election misinformation and manipulating political images and narratives (On-site participant)
EXPLANATION
The participant argues that AI, especially deepfakes and synthetic media, lowers the cost and difficulty of producing misleading political content. This makes election manipulation easier by enabling false images, altered visuals, and misleading political narratives to spread more quickly.
EVIDENCE
One participant said AI and especially deepfakes can play a role in disinformation because they make it easier to manipulate certain images during elections [215-217]. Another participant from Kosovo said their organization repeatedly debunks AI-generated election content and described fake interviews, synthetic personas, altered logos, and misleading visuals being used to influence voters [224-231].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is supported by broader human rights and ethics analysis warning that AI-driven fake news can influence elections and democracy [S33]. Additional context on fake news notes that elections across multiple countries have become focal points for concern about manipulated digital information [S40].
MAJOR DISCUSSION POINT
Major discussion point 4: Political manipulation, elections, and democratic risk
AGREED WITH
Francesco Vecchi, Smee Cujic
Argument 5
Political parties themselves may be major producers or amplifiers of misinformation and should bear responsibility (On-site participant)
EXPLANATION
The participant argues that political parties are not merely victims of AI-enabled misinformation but can also be direct sources or amplifiers of it. Because of this, they should be held responsible for how they use or spread manipulative technologies and false content.
EVIDENCE
A participant from Portugal said that during the last legislative elections, one party was responsible for around 80 percent of misinformation spread online about the elections [217]. The participant also said that this party’s own newspapers had shared fake images and argued that political parties themselves have a responsibility not to use such technologies if they want to protect democracy and be taken seriously [217].
MAJOR DISCUSSION POINT
Major discussion point 4: Political manipulation, elections, and democratic risk
AGREED WITH
Francesco Vecchi, Smee Cujic
DISAGREED WITH
Francesco Vecchi, Janice Richardson
Argument 6
In Kosovo, AI-generated fake interviews, fake media branding, and synthetic personas are being used to influence voters (On-site participant)
EXPLANATION
The participant provides a concrete example of how AI-generated content is being deployed in electoral contexts to mislead citizens. The argument is that these tactics imitate recognizable media formats and identities, making them especially persuasive during politically sensitive moments.
EVIDENCE
The participant from a fact-checking outlet in Kosovo said they deal extensively with AI-generated content during elections and debunk many such items [224-226]. The participant described AI-generated people who do not exist, fake interviews, altered logos of known media outlets, and other synthetic political content that citizens believe and that is used to suggest support for a party or candidate [229-232].
MAJOR DISCUSSION POINT
Major discussion point 4: Political manipulation, elections, and democratic risk
AGREED WITH
Francesco Vecchi, Smee Cujic
Argument 7
Anonymous pseudo-media accounts are especially dangerous because citizens cannot identify who is behind manipulative AI content (On-site participant)
EXPLANATION
The participant argues that a major risk comes from anonymous or fake media-style accounts that imitate legitimate outlets but conceal their operators. This anonymity makes accountability difficult and increases the effectiveness of emotionally manipulative AI-generated content.
EVIDENCE
The participant from Kosovo warned that some accounts publish emotional disinformation and AI-generated material while presenting themselves as media through names that include terms like ‘.info’ or ‘news’ [239-242]. The participant stressed that there is no data about who stands behind these actors and that citizens therefore cannot tell who is producing or coordinating the disinformation [239-242].
MAJOR DISCUSSION POINT
Major discussion point 4: Political manipulation, elections, and democratic risk
AGREED WITH
Francesco Vecchi, Smee Cujic
Argument 8
Fragmented national and platform approaches make enforcement difficult because AI-generated material circulates globally (On-site participant)
EXPLANATION
The participant argues that enforcement becomes extremely difficult when regulatory systems differ across countries while AI-generated content moves easily across borders and platforms. Nationally isolated responses cannot effectively control material created in one jurisdiction and consumed in another.
EVIDENCE
A participant from Armenia said that if regulation differs greatly from country to country, controlling AI-generated content will be extremely difficult because such content can be created anywhere [271-273]. Another participant later noted that technology-based approaches are also fragmented and raised concerns about access to tools through large companies, reinforcing the problem of uneven implementation [423].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External evidence notes that if regions adopt different rules, labeling may become fragmented rather than helpful, and that voluntary and legal schemes may overlap confusingly across jurisdictions [S27]. UN policy material also highlights that platform enforcement and moderation capacity are patchy across regions and languages, underscoring uneven global implementation [S36].
MAJOR DISCUSSION POINT
Major discussion point 5: Need for coordinated and systemic responses across Europe
AGREED WITH
Smee Cujic, Frances Douglas-Thompson, Francesco Vecchi, Janice Richardson
DISAGREED WITH
Francesco Vecchi, Smee Cujic, Frances Douglas-Thompson
Argument 9
European cooperation and regulatory alignment are necessary to manage cross-border AI harms effectively (On-site participant)
EXPLANATION
The participant argues that states need coordinated and aligned regulatory frameworks to deal with AI harms that cross borders. Without cooperation, countries will struggle to create a coherent and enforceable response to globally distributed synthetic media.
EVIDENCE
The participant from Armenia said cooperation among states should be emphasized because otherwise it will be extremely difficult to maintain any unified approach to AI-generated content across jurisdictions [271-274]. The same participant framed this cooperation as part of states’ positive obligations and as essential for workable regulation [271-273].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is supported by discussion of the need for interoperable standards in multilingual and multipolar contexts, especially for high-stakes domains like diplomacy and elections [S27].
MAJOR DISCUSSION POINT
Major discussion point 5: Need for coordinated and systemic responses across Europe
AGREED WITH
Smee Cujic, Frances Douglas-Thompson, Francesco Vecchi, Janice Richardson
DISAGREED WITH
Francesco Vecchi, Smee Cujic, Frances Douglas-Thompson
Argument 10
Europe already has experience coordinating through shared frameworks like the DSA and should continue joint enforcement (On-site participant)
EXPLANATION
The participant argues that Europe is not starting from scratch because it already has strong experience in collective digital governance. Existing cooperation under the DSA and related bodies provides a foundation for future joint enforcement of AI regulation.
EVIDENCE
A participant identifying as Jessica said European countries already work together effectively through the DSA and through bodies such as the European Board of Digital Services Coordinators [277-282]. She added that under the AI omnibus, European regulators can continue this pattern of cooperation in enforcing AI rules [282].
MAJOR DISCUSSION POINT
Major discussion point 5: Need for coordinated and systemic responses across Europe
AGREED WITH
Smee Cujic, Frances Douglas-Thompson, Francesco Vecchi, Janice Richardson
DISAGREED WITH
Francesco Vecchi, Smee Cujic, Frances Douglas-Thompson
Argument 11
The challenge is not choosing between innovation and safety, but building governance that supports opportunities while mitigating systemic risks (On-site participant)
EXPLANATION
The participant argues against framing AI policy as a simple trade-off between growth and protection. Instead, governance should simultaneously encourage innovation and economic opportunity while reducing harms such as toxic amplification, abuse, and disinformation.
EVIDENCE
Jessica said AI offers opportunities for innovation, economic growth, global connectivity, productivity, education, and civic participation [283-285]. She then said these benefits should not be treated as alternatives to addressing harms such as toxic content amplification, gender-based image abuse, and mis- and disinformation, and argued for governance that maximizes opportunities while preventing and mitigating systemic risks [286-287].
MAJOR DISCUSSION POINT
Major discussion point 5: Need for coordinated and systemic responses across Europe
AGREED WITH
Smee Cujic, Frances Douglas-Thompson, Francesco Vecchi, Janice Richardson
Argument 12
Information integrity should also be treated as a cybersecurity and broader security issue, not only as a media problem (On-site participant)
EXPLANATION
The participant argues that AI-generated influence operations have become a security concern that goes beyond journalism or media policy. Because synthetic content lowers the cost of manipulation and influence, information integrity should be integrated into cyber resilience and broader security frameworks.
EVIDENCE
A participant from North Macedonia asked whether information integrity had been discussed as part of cybersecurity and argued for an interdisciplinary approach [306-309]. She said AI-generated content is lowering the cost of influence operations and is becoming not just a media or disinformation issue but a regional and global security issue [310-313].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources frame AI-related manipulation as a matter of democracy, security, dignity, and broader societal protection, not just media policy [S33]. Additional context from policy discussions on fake news shows that some governments have treated misinformation as a major national threat with serious political consequences [S40].
MAJOR DISCUSSION POINT
Major discussion point 6: Supporting trustworthy information ecosystems, journalism, and security-oriented responses
AGREED WITH
Pascal Schneiders, Francesco Vecchi, Gabija Skučaitė
Argument 13
Smaller states and weaker digital ecosystems lack capacity, so practical tools and governance models are needed to respond to AI-enabled influence operations (On-site participant)
EXPLANATION
The participant argues that many smaller or less-resourced countries do not have the institutional capacity needed to respond effectively to AI-driven information threats. As a result, they need practical tools, governance models, and support mechanisms that are realistic for their contexts.
EVIDENCE
The North Macedonia participant said smaller states and developing digital ecosystems do not have the institutional capacities to respond to these threats and asked what governance models and tools are available [313-317]. She also described her organization’s own software tool for assessing manipulation levels in government and media content, but said this work is exhausting, time-consuming, and not cost-effective despite its importance for truth, prosecution, and security [318-327].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is enriched by evidence that research access, moderation tools, and enforcement capacity are unevenly distributed globally and concentrated in the global North, leaving many regions under-resourced [S36].
MAJOR DISCUSSION POINT
Major discussion point 6: Supporting trustworthy information ecosystems, journalism, and security-oriented responses
AGREED WITH
Pascal Schneiders, Francesco Vecchi, Gabija Skučaitė
F
Francesco Vecchi
4 arguments137 words per minute1916 words836 seconds
Argument 1
AI-generated content is already reshaping beliefs and cognition, so integrity cannot be addressed only through simple labels (Francesco Vecchi)
EXPLANATION
He argues that AI-generated content affects the way people perceive reality and form beliefs, making the issue deeper than a technical labeling problem. Because cognition itself is being shaped through exposure and algorithmic feeds, information integrity requires broader responses than simple content markers.
EVIDENCE
He said one main reason for the discussion was that AI-generated content is already reshaping human cognition because people are exposed to it on social networks and algorithms feed them what they want to receive [157-159]. He connected this to concerns in the Rome Declaration on Media Ecology and the Khan Declaration on cognitive security, arguing that AI is influencing how people understand reality and shape political beliefs [160-162].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources support the claim that abundant synthetic content has already shifted how people relate to information by making authenticity harder to verify at scale [S27]. Additional context from misinformation research shows that users often absorb content in low-attention, emotionally driven contexts where repeated exposure still shapes beliefs [S28].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, On-site participant, Smee Cujic, Gabija Skučaitė
DISAGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, On-site participant, Gabija Skučaitė
Argument 2
Defining what counts as AI-generated content is itself a regulatory challenge, especially when AI is embedded in ordinary work processes (Francesco Vecchi)
EXPLANATION
He points out that regulating AI-generated content is difficult because the boundary between human and AI contribution is often unclear. In everyday use, many people rely on AI support tools, so legal or policy definitions of what counts as AI-generated are not always straightforward.
EVIDENCE
He asked the audience to remember what ‘AI-generated’ means in a context where many people use AI to support their work and questioned where the line should be drawn between something AI-generated and not AI-generated [263]. He used this ambiguity to suggest that regulation itself faces a definitional problem, especially in mixed human-AI production processes [263].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is directly corroborated by external discussion of boundary problems in certification and labeling: standards must decide whether spellcheck, translation tools, accessibility aids, or human-AI collaboration count as ‘AI-free’ or AI-generated, showing that the category itself is contested [S27].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
AGREED WITH
Frances Douglas-Thompson, On-site participant, Janice Richardson, Smee Cujic
DISAGREED WITH
Pascal Schneiders, On-site participant, Frances Douglas-Thompson
Argument 3
Information integrity is tied to cognitive security, sovereignty of mind, and the shaping of political beliefs (Francesco Vecchi)
EXPLANATION
He frames information integrity as a matter of cognitive sovereignty and democratic self-determination, not just media accuracy. His argument is that AI affects how people process reality and politics, making it relevant to both individual autonomy and collective democratic security.
EVIDENCE
He referred to the Rome Declaration on Media Ecology and the Khan Declaration on cognitive security and sovereignty of mind as frameworks for understanding the issue [160-161]. He then argued that AI-generated content and AI more broadly are influencing how people understand reality, face it, and shape their political beliefs [162].
MAJOR DISCUSSION POINT
Major discussion point 4: Political manipulation, elections, and democratic risk
AGREED WITH
On-site participant, Smee Cujic
Argument 4
Trust in institutions and educational systems is central when societies struggle to distinguish fact from fiction (Francesco Vecchi)
EXPLANATION
He argues that when social trust breaks down and people no longer know how to distinguish fact from fiction, institutional trust becomes crucial. Educational institutions in particular play a foundational role in sustaining information integrity under these conditions.
EVIDENCE
He summarized a chat contribution by saying the core problem is social trust and described the current context as one where people do not know where to draw the line between fact and fiction [352-353]. He concluded that trust in institutions, and especially in educational institutions, is crucial for ensuring information integrity [353].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources support this by emphasizing that institutions such as journalism, education, and diplomacy are especially affected by authenticity uncertainty and remain central to public trust [S27]. Further context from education-focused analysis argues that schools must cultivate judgment, wisdom, and independent thinking in an AI-saturated environment [S29].
MAJOR DISCUSSION POINT
Major discussion point 6: Supporting trustworthy information ecosystems, journalism, and security-oriented responses
AGREED WITH
Pascal Schneiders, On-site participant, Gabija Skučaitė
J
Janice Richardson
5 arguments124 words per minute890 words428 seconds
Argument 1
Young people and all users need to understand not only AI but also the regulation shaping digital environments (Janice Richardson)
EXPLANATION
She argues that digital literacy should include knowledge of legal and regulatory frameworks, not just technical understanding. For her, informed participation in information integrity requires users, especially young people, to understand the rules and instruments that shape digital spaces.
EVIDENCE
She said that one message missing from the earlier framing was that young people and everyone else have a responsibility to understand regulation [20-21]. She linked this to information quality and integrity and introduced the Democracy Shield as a recent legal instrument aimed at stopping electoral interference and building resilience through digital literacy [22-24].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External support comes from policy material encouraging users, especially youth, to be included in the policy space because they are directly affected by emerging platforms and proposals [S36].
MAJOR DISCUSSION POINT
Major discussion point 2: Digital literacy, human sense-making, and user resilience
AGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Frances Douglas-Thompson, On-site participant, Smee Cujic
Argument 2
User resilience depends on capacities such as control, community, connectedness, communication, confidence, and co-regulation (Janice Richardson)
EXPLANATION
She argues that resilience is not a single skill but a broader set of social and individual capacities. Users need technical control, supportive communities, communication and reporting channels, trust in institutions, and cooperative regulatory arrangements to navigate AI-driven information risks.
EVIDENCE
She said user resilience is a key objective and can be described through seven C’s, beginning with control, which requires knowing one’s tools and developing digital competence [69-72]. She then added community, connectedness, communication including reporting, confidence in government and regulation, and co-regulation involving industry and users as necessary elements of resilience [73-79].
MAJOR DISCUSSION POINT
Major discussion point 2: Digital literacy, human sense-making, and user resilience
AGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Gabija Skučaitė, Francesco Vecchi
DISAGREED WITH
Frances Douglas-Thompson, On-site participant, Smee Cujic
Argument 3
AI literacy should include how AI works, how to detect synthetic content, and how algorithmic bias and attention economies affect users (Janice Richardson)
EXPLANATION
She argues that meaningful AI literacy must go beyond surface-level awareness and include both technical and social dimensions of AI systems. Users should understand content detection, system design, self-generated content risks, sycophancy, marketing, fact-checking, and discrimination.
EVIDENCE
She said people in her projects want to learn how to detect AI-generated content and how AI works, including what LLMs are and how users can influence them [80-85]. She also said they want more control over self-generated content, are concerned about AI sycophancy and well-being, and want to understand the attention economy, marketing strategies, fact-checking, and algorithmic bias and discrimination [86-90].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is reinforced by educational sources arguing that students need to understand what AI is and is not, where it fails, and how to evaluate its outputs critically [S29]. Additional context from school-based discussions highlights how AI use interacts with broader attention and motivation problems in digital environments [S30].
MAJOR DISCUSSION POINT
Major discussion point 2: Digital literacy, human sense-making, and user resilience
AGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Gabija Skučaitė, Francesco Vecchi
Argument 4
Europe takes a people-centric, rights-based, precautionary approach to AI and data governance, unlike the US and China (Janice Richardson)
EXPLANATION
She argues that Europe has a distinctive governance model centered on people, rights, and precaution, in contrast with the market-driven US approach and the state-control-oriented Chinese model. This comparative framing is meant to show why European regulation matters for information integrity and sovereignty.
EVIDENCE
She said Europe has a people-centric approach based on safety, rights, and values, and described it as precautionary and risk-averse with goals of strategic autonomy and digital sovereignty [25-27][51-54]. She contrasted this with the United States’ competition- and innovation-oriented model led by private sector actors and China’s emphasis on territorial control over data, platforms, networks, and industrial policy [55-59].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
AGREED WITH
On-site participant, Smee Cujic, Frances Douglas-Thompson, Francesco Vecchi
Argument 5
Existing European instruments such as GDPR, DSA, DMA, the AI Act, and the AI Framework Convention already provide a regulatory basis for protecting users (Janice Richardson)
EXPLANATION
She argues that Europe already has a substantial legal toolkit that users should know and use. These instruments create protections around personal data, platform responsibility, market choice, consumer rights, AI risk, and human rights safeguards.
EVIDENCE
She listed GDPR as giving people control over personal data and ensuring transparency and rights, the Digital Services Act as targeting manipulative and harmful content from tech companies, and the Digital Markets Act as supporting freedom of choice [60-63]. She also referred to the Consumer Rights Directive, the AI Act with its system of banning dangerous and high-risk uses, and the AI Framework Convention of the Council of Europe as protecting human rights, democracy, and the rule of law [64-68].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
AGREED WITH
Frances Douglas-Thompson, On-site participant, Smee Cujic, Francesco Vecchi
G
Gabija Skučaitė
2 arguments159 words per minute378 words142 seconds
Argument 1
The key long-term response is strengthening human sense-making rather than relying on labels alone (Gabija Skučaitė)
EXPLANATION
She argues that in an AI-saturated environment where truth and falsity are increasingly blurred, the decisive response is not more labeling but stronger human judgment. Human beings need to recover and exercise their own capacity to make sense of reality and context.
EVIDENCE
She described the current moment as one in which nothing is clearly true or false anymore and said that even if everything were labeled, people still might not be sure [332-334]. She argued that this environment requires humanity to return to what is truly human: the ability to make sense of what is true and false, and concluded that labeling will not solve everything because human capabilities will [335][346-350].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources support this by arguing that some intellectual struggle and independent judgment must remain central in education, and that students need wisdom about when not to rely on AI [S29]. Broader reflections on problem-solving and discernment similarly warn against replacing reflective human sense-making with externally structured cues and shortcuts [S25].
MAJOR DISCUSSION POINT
Major discussion point 2: Digital literacy, human sense-making, and user resilience
AGREED WITH
Frances Douglas-Thompson, Janice Richardson, Pascal Schneiders, Francesco Vecchi
DISAGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, On-site participant, Francesco Vecchi
Argument 2
Academia should help people distinguish reality from synthetic or manipulative virtual content (Gabija Skučaitė)
EXPLANATION
She argues that educational institutions have a major responsibility to teach people how to interpret and distinguish real-world experience from synthetic or manipulative digital environments. Academia should therefore take a leading role in awareness-building and critical understanding of AI systems.
EVIDENCE
She said context matters greatly in how information is understood and argued that more attention must be paid to raising awareness of AI algorithms and sense-making in the age of AI [346-347]. She then stated that academia must take a really big role in educating young people to make sense of the real world in relation to the virtual meta-environment that now surrounds daily life [347-350].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is enriched by sources emphasizing that education must preserve genuine learning, judgment, and independent thinking in a world where AI is everywhere [S29], and that schools are already confronting how AI alters students’ relationship to learning and reality-testing [S30].
MAJOR DISCUSSION POINT
Major discussion point 2: Digital literacy, human sense-making, and user resilience
AGREED WITH
Pascal Schneiders, On-site participant, Francesco Vecchi
S
Smee Cujic
4 arguments125 words per minute223 words106 seconds
Argument 1
Messages from the session stressed that labeling must sit within a broader public-interest framework and that labels are interpreted differently by users (Smee Cujic)
EXPLANATION
In summarizing the workshop messages, Smee emphasizes that labels are only one part of a broader governance response. The session message recognized that labels do not automatically eliminate social harms and that users interpret them in varied ways depending on context and critical engagement.
EVIDENCE
When reading the drafted session messages, Smee said that labeling needs to be put in a broader framework and that it does not address discrimination, unjust interference, or social harm on its own [367-374]. Smee also read out that AI content is already reshaping beliefs, that labels may not create greater clarity, that unlabeled information may be wrongly assumed truthful, and that labels are interpreted differently based on personal setting and critical engagement [370-374].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External sources directly support both parts of this claim: labels are interpreted differently depending on users and context [S28], and labeling/provenance systems are useful but limited tools that need broader governance choices and public-interest framing [S27].
MAJOR DISCUSSION POINT
Major discussion point 1: Limits and value of AI labeling and watermarking for information integrity
AGREED WITH
Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, On-site participant, Gabija Skučaitė, Francesco Vecchi
Argument 2
Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic)
EXPLANATION
Smee’s summary reflects a collective conclusion that users should not bear sole responsibility for information integrity. The workshop message instead distributed responsibility across states, media, and other relevant actors with public obligations.
EVIDENCE
Smee read out the second draft message stating that responsibility should not be only on users, but on states, media, and political parties themselves, and added that states have a positive obligation [364-365]. This summary was presented as one of the main outputs that reflected the room’s broad consensus [358-360][364-366].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is supported by sources emphasizing platform accountability, safety-by-design, and the inadequacy of relying solely on self-regulation or user vigilance [S34]. UN guidance on information integrity also stresses institutional responsibilities, policy gaps, and the need to involve users without placing the whole burden on them [S36].
MAJOR DISCUSSION POINT
Major discussion point 3: Governance, regulation, and responsibility for information integrity
AGREED WITH
Frances Douglas-Thompson, On-site participant, Janice Richardson, Francesco Vecchi
DISAGREED WITH
On-site participant, Francesco Vecchi, On-site participant, Janice Richardson
Argument 3
AI-generated content is increasingly being used during political campaigns and poses direct threats to democratic integrity (Smee Cujic)
EXPLANATION
In the session conclusions, Smee highlights political campaigning as a key arena in which AI-generated threats are already materializing. The implication is that democratic integrity is directly endangered by the growing use of synthetic media in electoral contexts.
EVIDENCE
Smee read the first draft message from the session conclusions stating that AI faces threats for information integrity and is increasingly being used during political campaigns [361-363]. This message was presented as a distilled outcome of the discussion and met with visible agreement in the room [361-363].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
External evidence supports this with broader warnings that AI-enabled fake news and synthetic manipulation can influence elections and democracy [S33]. Additional context from misinformation analysis notes recurring concerns over election interference and politically harmful fake news across countries [S40].
MAJOR DISCUSSION POINT
Major discussion point 4: Political manipulation, elections, and democratic risk
AGREED WITH
On-site participant, Francesco Vecchi
Argument 4
Session conclusions called for stronger cooperation between states and more unified or interoperable approaches across jurisdictions (Smee Cujic)
EXPLANATION
Smee’s summary reflects the discussion’s conclusion that isolated national approaches are insufficient. The session called for stronger interstate cooperation and more aligned or interoperable regulatory responses to cross-border AI harms.
EVIDENCE
Smee read out the fifth draft message stating that cooperation between states requires a more unified approach because AI material is generated globally and approaches differ greatly across jurisdictions [416-418]. This wording was then further refined by participants to emphasize regulatory frameworks and interoperability, showing that cross-border coordination was a clear takeaway [419-422].
EXTERNAL EVIDENCE (KNOWLEDGE BASE)
This is corroborated by external discussion of the need for interoperable standards across regions and the risk that fragmented regulatory approaches undermine the usefulness of labeling and certification [S27].
MAJOR DISCUSSION POINT
Major discussion point 5: Need for coordinated and systemic responses across Europe
AGREED WITH
On-site participant, Frances Douglas-Thompson, Francesco Vecchi, Janice Richardson
DISAGREED WITH
On-site participant, Francesco Vecchi, Frances Douglas-Thompson
Agreements
Agreement Points
AI labeling and visible markers are useful for transparency but are not sufficient on their own and can create misleading signals.
Speakers: Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, On-site participant, Smee Cujic, Gabija Skučaitė, Francesco Vecchi
Visible markers as a starting point, not a complete solution (Frances Douglas-Thompson) Labels can help transparency but may create false trust in unlabeled content and are hard to scale across platforms (Frances Douglas-Thompson) Technological labeling systems are fragmented and fragile, especially when content is reposted or altered (Frances Douglas-Thompson) Audience-facing labels have mixed effectiveness because users notice and interpret them selectively (Pascal Schneiders) AI labels often reduce trust, but they do not reliably stop people from believing or sharing content they already agree with (Pascal Schneiders) Transparency alone may not reduce harm because emotionally manipulative AI content can still spread widely (Co-moderator) Labeling AI-generated content does not automatically solve discrimination, manipulation, or amplification harms (On-site participant) Messages from the session stressed that labeling must sit within a broader public-interest framework and that labels are interpreted differently by users (Smee Cujic) The key long-term response is strengthening human sense-making rather than relying on labels alone (Gabija Skučaitė) AI-generated content is already reshaping beliefs and cognition, so integrity cannot be addressed only through simple labels (Francesco Vecchi)
Multiple speakers agreed that visible markers and labeling may help transparency, but they are not a complete response. Frances introduced visible markers as a starting point while questioning whether labels make content trustworthy, convey harm, or solve the issue [18]. She later added that current systems such as SynthID and C2PA are siloed, fragile, and may wrongly lead users to treat unlabeled content as reliable [173-182]. Pascal similarly argued that labels have mixed effectiveness because users notice and interpret them selectively, may distrust AI-labeled content without better understanding it, and often are not dissuaded when content confirms their beliefs [117-145]. The remote question relayed by the co-moderator directly challenged whether transparency is being overemphasized when emotionally manipulative AI content can still work even if disclosed [289-291]. A participant from the Council of Europe anti-discrimination department agreed that labeling, watermarking, and moderation are insufficient unless embedded in a public-interest and human-rights framework, noting that labeled AI-generated harmful imagery can still be amplified [245-260]. This was reflected in the final session messages read by Smee, which stated that labeling does not by itself address discrimination, unjust interference, or social harm, and that unlabeled information may be wrongly assumed to be truthful [367-374]. Gabija reinforced that even if everything were labeled, people still might not know what is true, so stronger human sense-making is needed [332-350]. Francesco also framed the issue as one of cognition and political belief formation rather than a mere labeling problem [157-162].
POLICY CONTEXT (KNOWLEDGE BASE)
This aligns with broader transparency expectations for platforms, but also with evidence that labels can confuse users or be overlooked. UN policy framing emphasizes meaningful transparency and user empowerment rather than single-point fixes [S54]. Analysis of AI provenance debates notes that detection and labeling help manage uncertainty but have clear limits, especially once content moves across platforms [S55]. Meta’s revised labeling practice further illustrates that visible markers can create confusion or reduced salience depending on design choices [S56].
Information integrity requires stronger digital literacy, AI literacy, user resilience, and human sense-making.
Speakers: Frances Douglas-Thompson, Janice Richardson, Pascal Schneiders, Gabija Skučaitė, Francesco Vecchi
Youth messages called for AI literacy in schools, including technical understanding and human oversight (Frances Douglas-Thompson) Young people and all users need to understand not only AI but also the regulation shaping digital environments (Janice Richardson) User resilience depends on capacities such as control, community, connectedness, communication, confidence, and co-regulation (Janice Richardson) AI literacy should include how AI works, how to detect synthetic content, and how algorithmic bias and attention economies affect users (Janice Richardson) Inoculation and literacy approaches may be more sustainable than trying to label all deceptive content (Pascal Schneiders) The key long-term response is strengthening human sense-making rather than relying on labels alone (Gabija Skučaitė) Academia should help people distinguish reality from synthetic or manipulative virtual content (Gabija Skučaitė) Trust in institutions and educational systems is central when societies struggle to distinguish fact from fiction (Francesco Vecchi)
A strong area of agreement was that resilience depends on education and literacy, not just technical controls. Frances recalled the YouthDIG call to embed AI literacy in school curricula, including how AI works, how algorithms function, and where human oversight must remain [18]. Janice argued that people, especially young people, must understand regulation as part of digital literacy and described user resilience through capacities such as control, community, connectedness, communication, confidence, and co-regulation [20-24][69-79]. She also said users want to learn to detect AI-generated content, understand LLMs, manage self-generated content risks, and grasp attention economies, fact-checking, and algorithmic bias [80-90]. Pascal agreed that inoculation and literacy approaches are more realistic than trying to label all deceptive content and advocated teaching people deceptive techniques through AI literacy and gamified methods [145-150]. Gabija similarly argued that in an AI-saturated environment, the essential response is human sense-making and that academia must educate people to distinguish the real world from manipulative virtual environments [332-350]. Francesco added that trust in institutions, especially educational ones, is crucial when societies struggle to distinguish fact from fiction [352-353].
POLICY CONTEXT (KNOWLEDGE BASE)
This is strongly supported by UN policy frameworks calling for investment in digital literacy so users can understand platforms, data use, and how to identify and respond to mis- and disinformation [S54]. The Global Digital Compact policy brief similarly stresses curricula for digitally literate citizens capable of critical thinking, while also warning that literacy alone is insufficient [S62]. Prior discussions on AI and information integrity also emphasize tailored literacy approaches for different audiences [S64].
Responsibility for information integrity should not fall on users alone; states and other actors have obligations and roles.
Speakers: Frances Douglas-Thompson, On-site participant, Janice Richardson, Smee Cujic, Francesco Vecchi
Responsibility for safe information environments should not fall only on users but also on states, platforms, media, and political actors (Frances Douglas-Thompson) States have positive obligations to guarantee a safe, pluralistic, and rights-respecting online environment and should not outsource governance entirely to private companies (On-site participant) Oversight should be independent, transparent, and designed to avoid political capture or discrimination (On-site participant) Existing European instruments such as GDPR, DSA, DMA, the AI Act, and the AI Framework Convention already provide a regulatory basis for protecting users (Janice Richardson) Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic) Defining what counts as AI-generated content is itself a regulatory challenge, especially when AI is embedded in ordinary work processes (Francesco Vecchi)
Speakers broadly agreed that users alone cannot carry the burden of identifying and managing AI-generated harms. Frances explicitly asked whether too much pressure is being placed on users and young people and raised governments, platforms, and publishers as actors who may need responsibility for labeling enforcement [191-207]. The Council of Europe participant strongly argued that states have positive obligations to ensure a safe, pluralistic, and non-discriminatory online environment, and that governance should include clear rules, oversight, access for researchers and regulators, and remedies rather than being outsourced to private companies [245-260]. Janice reinforced that Europe already has a substantial legal and regulatory toolkit, including GDPR, DSA, DMA, the AI Act, and the AI Framework Convention, which users should know and which protect rights and address platform harms [60-68]. Francesco added that regulation is complicated by the definitional challenge of deciding what counts as AI-generated content in mixed human-AI workflows [263]. In the final messages, Smee summarized the room’s agreement that responsibility should not lie only with users but with states, media, and political parties, with states bearing positive obligations [364-366].
POLICY CONTEXT (KNOWLEDGE BASE)
This directly reflects UN framing that the onus for safety should not lie with users and that transparency, accountability, and oversight must be collective responsibilities shared across governments, platforms, and other actors [S62]. The UN information integrity brief also assigns distinct responsibilities to member states, digital platforms, news media, and all stakeholders, including rights-consistent regulation and support for independent media [S54].
AI-generated content is already affecting elections, political campaigns, and democratic integrity.
Speakers: On-site participant, Francesco Vecchi, Smee Cujic
AI and deepfakes increase the ease of spreading election misinformation and manipulating political images and narratives (On-site participant) Political parties themselves may be major producers or amplifiers of misinformation and should bear responsibility (On-site participant) In Kosovo, AI-generated fake interviews, fake media branding, and synthetic personas are being used to influence voters (On-site participant) Anonymous pseudo-media accounts are especially dangerous because citizens cannot identify who is behind manipulative AI content (On-site participant) Information integrity is tied to cognitive security, sovereignty of mind, and the shaping of political beliefs (Francesco Vecchi) AI-generated content is increasingly being used during political campaigns and poses direct threats to democratic integrity (Smee Cujic)
There was broad agreement that AI-generated content is not a hypothetical problem but an active threat in elections and political campaigning. A participant from Portugal argued that AI and deepfakes make it easier to manipulate images during elections and said one party had been responsible for a large share of election misinformation, including fake images, showing that political parties themselves may be producers of such harms [215-217]. A participant from Kosovo described repeated debunking of AI-generated election content, including fake interviews, synthetic personas, altered media logos, and pseudo-media accounts used to influence voters [224-242]. Francesco linked the discussion to cognitive security and sovereignty of mind, arguing that AI is shaping how people understand reality and form political beliefs [160-162]. Smee’s final summary captured the room’s agreement that AI-generated content is increasingly being used during political campaigns and poses a threat to information integrity [361-363].
POLICY CONTEXT (KNOWLEDGE BASE)
This is supported by UN language warning that AI’s ability to generate believable content at scale intensifies misinformation and disinformation threats [S62]. The information integrity brief explicitly identifies harms that undermine democratic processes [S54]. Prior discussion records also connect AI-enabled manipulation to elections and cite concerns around disinformation campaigns and political advertising practices [S64] [S65].
Cross-border AI harms require stronger cooperation, alignment, and interoperable approaches across states and platforms.
Speakers: On-site participant, Smee Cujic, Frances Douglas-Thompson, Francesco Vecchi, Janice Richardson
Fragmented national and platform approaches make enforcement difficult because AI-generated material circulates globally (On-site participant) European cooperation and regulatory alignment are necessary to manage cross-border AI harms effectively (On-site participant) Europe already has experience coordinating through shared frameworks like the DSA and should continue joint enforcement (On-site participant) The challenge is not choosing between innovation and safety, but building governance that supports opportunities while mitigating systemic risks (On-site participant) Technological labeling systems are fragmented and fragile, especially when content is reposted or altered (Frances Douglas-Thompson) Session conclusions called for stronger cooperation between states and more unified or interoperable approaches across jurisdictions (Smee Cujic) Europe takes a people-centric, rights-based, precautionary approach to AI and data governance, unlike the US and China (Janice Richardson)
Speakers converged on the need for cross-border cooperation because AI-generated content and the technologies used to identify it are fragmented across jurisdictions and platforms. A participant from Armenia argued that if regulation differs greatly between countries, effective control becomes extremely difficult because AI-generated content can be produced anywhere, making cooperation among states essential [271-274]. Another participant noted that Europe already has experience cooperating through the DSA and related bodies and should continue joint enforcement under emerging AI rules [277-287]. Frances also emphasized fragmentation at the technical level, noting that current labeling technologies are siloed or break when content is reposted or altered [173-182]. Janice placed this in a broader geopolitical context by contrasting Europe’s rights-based approach with different US and Chinese governance models [51-60]. The final message read by Smee stated that cooperation between states requires a more unified approach because AI material is generated globally and legal approaches vary across jurisdictions, and participants refined this toward alignment and interoperability [416-422].
POLICY CONTEXT (KNOWLEDGE BASE)
This aligns with UN calls for interoperable transparency and safety measures given the transnational nature of digital platforms [S62]. Related policy language stresses collective action so national or industry initiatives do not further fragment the Internet, and calls for active policy compatibility and interoperability [S62]. Broader AI governance discussions also recommend multilateral frameworks, knowledge sharing, and regional cooperation mechanisms around interoperability and standards [S60] [S63].
Information integrity should be addressed systemically, including support for trustworthy institutions such as journalism, education, and broader security frameworks.
Speakers: Pascal Schneiders, On-site participant, Francesco Vecchi, Gabija Skučaitė
A holistic governance approach should support the long-term viability of journalism, not only label harmful content (Pascal Schneiders) Stronger news media reduce susceptibility to misinformation by providing verified information and exposure to multiple perspectives (Pascal Schneiders) Information integrity should also be treated as a cybersecurity and broader security issue, not only as a media problem (On-site participant) Smaller states and weaker digital ecosystems lack capacity, so practical tools and governance models are needed to respond to AI-enabled influence operations (On-site participant) Trust in institutions and educational systems is central when societies struggle to distinguish fact from fiction (Francesco Vecchi) Academia should help people distinguish reality from synthetic or manipulative virtual content (Gabija Skučaitė)
A further agreement point was that information integrity must be tackled as part of a wider ecosystem of trusted institutions and security responses. Pascal argued that governance should not only label misleading content but also sustain the viability of journalism, including possible financing or support, because stronger news media correlate with lower susceptibility to misinformation [292-301]. A participant from North Macedonia argued that AI-enabled influence operations are no longer just a media issue but a regional and global security issue, and asked for practical governance models and tools, especially for smaller states lacking institutional capacity [306-327]. Francesco similarly emphasized that cognitive sovereignty, defense, and security are intertwined with disinformation responses at the European level [329]. He also underlined the importance of trust in institutions and educational institutions when fact and fiction are hard to distinguish [352-353]. Gabija added that academia has a major role in helping people make sense of reality in an AI-saturated environment [346-350].
POLICY CONTEXT (KNOWLEDGE BASE)
This is consistent with UN recommendations that responses to information harms include support for free, viable, independent, and plural media; funding and training for fact-checking; and investment in digital literacy and research [S54]. It is also reinforced by prior IGF discussion framing journalism as democratic infrastructure and information integrity as tied to broader democratic and institutional resilience, not just platform moderation [S69].
Similar Viewpoints
These speakers shared the view that transparency tools such as labels and watermarks may help but cannot be treated as a standalone fix. Frances questioned whether labels produce trust or simply send the wrong message, especially when unlabeled content may then be assumed reliable [173-182]. Pascal added that labels are selectively noticed, can reduce trust without changing beliefs, and do little against confirmation bias [117-145]. The Council of Europe participant and the remote question relayed by the co-moderator both stressed that even labeled content can remain manipulative, discriminatory, and widely amplified [245-260][289-291].
Speakers: Frances Douglas-Thompson, Pascal Schneiders, On-site participant, Co-moderator
Visible markers as a starting point, not a complete solution (Frances Douglas-Thompson) Labels can help transparency but may create false trust in unlabeled content and are hard to scale across platforms (Frances Douglas-Thompson) Audience-facing labels have mixed effectiveness because users notice and interpret them selectively (Pascal Schneiders) AI labels often reduce trust, but they do not reliably stop people from believing or sharing content they already agree with (Pascal Schneiders) Labeling AI-generated content does not automatically solve discrimination, manipulation, or amplification harms (On-site participant) Transparency alone may not reduce harm because emotionally manipulative AI content can still spread widely (Co-moderator)
These speakers converged on the need for a literacy- and resilience-based response. Frances recalled calls for AI literacy in schools [18]. Janice expanded this into a broader model of user resilience and regulation literacy, along with technical understanding of AI, fact-checking, and algorithmic bias [20-24][69-90]. Pascal argued that inoculation and literacy are more sustainable than trying to label every deceptive item [145-150]. Gabija framed the same concern in more philosophical terms, emphasizing human sense-making and the educational role of academia [332-350].
Speakers: Janice Richardson, Pascal Schneiders, Gabija Skučaitė, Frances Douglas-Thompson
Young people and all users need to understand not only AI but also the regulation shaping digital environments (Janice Richardson) User resilience depends on capacities such as control, community, connectedness, communication, confidence, and co-regulation (Janice Richardson) AI literacy should include how AI works, how to detect synthetic content, and how algorithmic bias and attention economies affect users (Janice Richardson) Inoculation and literacy approaches may be more sustainable than trying to label all deceptive content (Pascal Schneiders) The key long-term response is strengthening human sense-making rather than relying on labels alone (Gabija Skučaitė) Academia should help people distinguish reality from synthetic or manipulative virtual content (Gabija Skučaitė) Youth messages called for AI literacy in schools, including technical understanding and human oversight (Frances Douglas-Thompson)
These speakers shared the view that governance responsibility must be distributed across institutional actors and not imposed only on users. Frances explicitly questioned overburdening users and asked who should enforce AI labeling [191-207]. The Council of Europe participant emphasized positive state obligations, oversight, and remedies [245-260]. Janice pointed to existing European legal instruments that already establish responsibilities and protections [60-68]. Smee’s final session message codified this consensus by stating that responsibility should not be only on users [364-366].
Speakers: Frances Douglas-Thompson, On-site participant, Smee Cujic, Janice Richardson
Responsibility for safe information environments should not fall only on users but also on states, platforms, media, and political actors (Frances Douglas-Thompson) States have positive obligations to guarantee a safe, pluralistic, and rights-respecting online environment and should not outsource governance entirely to private companies (On-site participant) Oversight should be independent, transparent, and designed to avoid political capture or discrimination (On-site participant) Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic) Existing European instruments such as GDPR, DSA, DMA, the AI Act, and the AI Framework Convention already provide a regulatory basis for protecting users (Janice Richardson)
These speakers agreed that AI-generated content is already being weaponized in democratic processes. Participants gave concrete examples from Portugal and Kosovo of election misinformation, fake political imagery, false interviews, and anonymous pseudo-media operations [215-217][224-242]. Francesco framed these developments as matters of cognitive security and political belief formation [160-162]. Smee’s final summary then recognized the room’s agreement that AI-generated content is increasingly being used during political campaigns [361-363].
Speakers: On-site participant, Francesco Vecchi, Smee Cujic
AI and deepfakes increase the ease of spreading election misinformation and manipulating political images and narratives (On-site participant) Political parties themselves may be major producers or amplifiers of misinformation and should bear responsibility (On-site participant) In Kosovo, AI-generated fake interviews, fake media branding, and synthetic personas are being used to influence voters (On-site participant) Anonymous pseudo-media accounts are especially dangerous because citizens cannot identify who is behind manipulative AI content (On-site participant) Information integrity is tied to cognitive security, sovereignty of mind, and the shaping of political beliefs (Francesco Vecchi) AI-generated content is increasingly being used during political campaigns and poses direct threats to democratic integrity (Smee Cujic)
These speakers agreed that fragmented governance is a major obstacle and that more coordinated approaches are needed. Participants stressed that divergent national regulations make enforcement hard because AI content crosses borders [271-274]. Frances pointed to fragmentation in technical labeling systems across platforms [173-182]. Janice framed the issue geopolitically through divergent regional governance models [51-60]. Smee’s final message reflected consensus around stronger interstate cooperation and more unified or interoperable approaches [416-422].
Speakers: On-site participant, Frances Douglas-Thompson, Smee Cujic, Janice Richardson
Fragmented national and platform approaches make enforcement difficult because AI-generated material circulates globally (On-site participant) European cooperation and regulatory alignment are necessary to manage cross-border AI harms effectively (On-site participant) Europe already has experience coordinating through shared frameworks like the DSA and should continue joint enforcement (On-site participant) Technological labeling systems are fragmented and fragile, especially when content is reposted or altered (Frances Douglas-Thompson) Session conclusions called for stronger cooperation between states and more unified or interoperable approaches across jurisdictions (Smee Cujic) Europe takes a people-centric, rights-based, precautionary approach to AI and data governance, unlike the US and China (Janice Richardson)
Unexpected Consensus
Broad agreement that labeling can backfire or create false confidence in unlabeled content.
Speakers: Frances Douglas-Thompson, Pascal Schneiders, On-site participant, Smee Cujic
Labels can help transparency but may create false trust in unlabeled content and are hard to scale across platforms (Frances Douglas-Thompson) Audience-facing labels have mixed effectiveness because users notice and interpret them selectively (Pascal Schneiders) Labeling AI-generated content does not automatically solve discrimination, manipulation, or amplification harms (On-site participant) Messages from the session stressed that labeling must sit within a broader public-interest framework and that labels are interpreted differently by users (Smee Cujic)
An unexpected consensus was how strongly speakers from different backgrounds converged not just on the limits of labeling, but on the specific risk that labels may distort trust. Frances warned that unlabeled content may be assumed highly reliable [180-182]. Pascal discussed implied truth effects and selective attention to labels [132-145]. The Council of Europe participant argued that labels do not stop harmful amplification or discrimination [245-260]. Smee’s final summary repeated that unlabeled information may be automatically perceived as high quality or truthful, even when inaccurate [370-374].
POLICY CONTEXT (KNOWLEDGE BASE)
This concern is enriched by prior analysis showing that labeling and provenance signals are partial aids, not guarantees, and can shift people toward simplistic heuristics rather than careful verification [S55]. Platform experience also shows labeling controversies can misrepresent authentic content or make AI involvement easier to miss, illustrating how labels may mislead or create misplaced confidence [S56].
Consensus that political parties themselves may be direct contributors to misinformation, not just platforms or anonymous actors.
Speakers: On-site participant, Smee Cujic, Francesco Vecchi
Political parties themselves may be major producers or amplifiers of misinformation and should bear responsibility (On-site participant) Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic)
It was notable that the discussion did not limit accountability to platforms or states. A participant from Portugal explicitly said a political party had been responsible for most election misinformation in a recent campaign and argued that political parties themselves must not use such technologies if they care about democracy [215-217]. This translated into the final session message, where Smee read that responsibility should lie not only with users but also with states, media, and political parties [364-365]. Francesco then defended keeping political parties explicitly named in the drafting discussion [383].
POLICY CONTEXT (KNOWLEDGE BASE)
This is consistent with the UN principle that all stakeholders should refrain from using, supporting, or amplifying disinformation for political or strategic purposes [S54]. Historical discussion of political advertising also shows that campaign actors, influencers, and organized political communication can themselves drive disinformation, not merely intermediaries like platforms [S65].
Shared recognition that information integrity is not only a media problem but also a question of security, cognition, and democratic sovereignty.
Speakers: Francesco Vecchi, On-site participant, Pascal Schneiders
Information integrity is tied to cognitive security, sovereignty of mind, and the shaping of political beliefs (Francesco Vecchi) Information integrity should also be treated as a cybersecurity and broader security issue, not only as a media problem (On-site participant) A holistic governance approach should support the long-term viability of journalism, not only label harmful content (Pascal Schneiders)
A noteworthy consensus emerged across security, governance, and media perspectives that the problem is broader than disinformation moderation. Francesco connected AI-generated content to cognitive security and sovereignty of mind [160-162]. The participant from North Macedonia explicitly argued that AI-generated influence operations are becoming a global security issue, not just a media issue [306-313]. Pascal complemented this by calling for a holistic governance approach that includes sustaining journalism and information ecosystems [292-301].
POLICY CONTEXT (KNOWLEDGE BASE)
This broader framing is supported by UN language linking information integrity to democratic processes, human rights, online safety, and the need to avoid fragmentation of the Internet [S54] [S62]. Cyber and digital sovereignty discussions also connect harms to political and electoral processes, public institutions, and state sovereignty, showing that information integrity intersects with security and governance rather than media alone [S67] [S70].
Overall Assessment

The strongest areas of agreement were that AI labeling and watermarking may be useful but are insufficient alone; that user resilience, AI literacy, and human sense-making are essential; that responsibility must be shared across states and other actors rather than imposed only on users; and that AI-generated political manipulation is already a real democratic risk requiring coordinated cross-border responses [18][69-90][145-150][160-162][191-207][215-242][245-260][361-374][416-422].

High consensus on the main diagnosis and broad policy direction. Speakers from academia, civil society, research, and moderation largely aligned on the limits of purely technical fixes and the need for systemic governance, literacy, and institutional responsibility.

Differences
Different Viewpoints
How far AI labeling and watermarking can meaningfully improve information integrity
Speakers: Frances Douglas-Thompson, Pascal Schneiders, Co-moderator, On-site participant, Gabija Skučaitė, Francesco Vecchi
Visible markers as a starting point, not a complete solution (Frances Douglas-Thompson) Labels can help transparency but may create false trust in unlabeled content and are hard to scale across platforms (Frances Douglas-Thompson) Technological labeling systems are fragmented and fragile, especially when content is reposted or altered (Frances Douglas-Thompson) Audience-facing labels have mixed effectiveness because users notice and interpret them selectively (Pascal Schneiders) AI labels often reduce trust, but they do not reliably stop people from believing or sharing content they already agree with (Pascal Schneiders) Transparency alone may not reduce harm because emotionally manipulative AI content can still spread widely (Co-moderator) Labeling AI-generated content does not automatically solve discrimination, manipulation, or amplification harms (On-site participant) The key long-term response is strengthening human sense-making rather than relying on labels alone (Gabija Skučaitė) AI-generated content is already reshaping beliefs and cognition, so integrity cannot be addressed only through simple labels (Francesco Vecchi)
Speakers broadly accepted that labels and visible markers may help transparency, but disagreed over how much weight to give them as a governance solution. Frances presented markers as a useful starting point while explicitly questioning whether they actually convey harm, create trust, or work at scale across platforms [18][173-182]. Pascal went further, stressing that labels are selectively noticed, interpreted differently, often only reduce trust in AI content, and may not stop engagement when users already agree with the message [117-145]. The co-moderator sharpened this concern by asking whether transparency is being overemphasized when emotionally manipulative AI content can still be effective even if users know it is AI-generated [289-291]. A Council of Europe participant argued that labeling, watermarking, and moderation are insufficient unless embedded in a public-interest and human-rights framework, since labeled harmful content can still be amplified and discriminatory [245-260]. Gabija argued even more strongly that labeling cannot solve the core problem because human sense-making is the decisive response in an AI-saturated environment [332-350]. Francesco also framed the issue as deeper than labels because AI is already reshaping cognition, reality perception, and political belief formation [157-162].
POLICY CONTEXT (KNOWLEDGE BASE)
This debate has clear prior context. Some discussions have proposed watermarking requirements for AI companies as a concrete response to election-related disinformation [S64]. At the same time, analysis of provenance and labeling stresses that such mechanisms help but are limited in informal or cross-platform environments and should not be treated as comprehensive solutions [S55]. Platform practice also shows user confusion over AI labels and ongoing redesign of how they are displayed [S56].
Whether responsibility for information integrity should rest mainly on user resilience or more heavily on states and other institutions
Speakers: Frances Douglas-Thompson, Janice Richardson, On-site participant, Smee Cujic
Responsibility for safe information environments should not fall only on users but also on states, platforms, media, and political actors (Frances Douglas-Thompson) Young people and all users need to understand not only AI but also the regulation shaping digital environments (Janice Richardson) User resilience depends on capacities such as control, community, connectedness, communication, confidence, and co-regulation (Janice Richardson) States have positive obligations to guarantee a safe, pluralistic, and rights-respecting online environment and should not outsource governance entirely to private companies (On-site participant) Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic)
There was a substantive disagreement over where the main burden of response should fall. Janice emphasized user resilience, arguing that young people and all users must understand regulation and develop capacities such as control, connectedness, communication, confidence, and co-regulation [20-24][69-79]. Frances questioned whether this puts too much emphasis on users, especially young people, asking if it is too much to expect them constantly to determine what is true online and suggesting broader responsibility among governments, platforms, and users who publish content [191-207]. A Council of Europe participant pushed further toward state responsibility, arguing it is indeed too much to place the burden on individuals and that states have positive obligations to ensure a safe, pluralistic, and rights-respecting online environment rather than outsourcing governance to private actors [245-249]. The draft messages then reflected the room’s tilt toward shared responsibility beyond users alone [364-365].
POLICY CONTEXT (KNOWLEDGE BASE)
UN policy framing clearly pushes against a user-only model, stating that the onus for safety should not lie with users and calling for transparency, accountability, oversight, and safe-design obligations across institutions and firms [S62]. At the same time, UN recommendations do support user empowerment and literacy as important components, which helps explain why this remains a live balance-of-responsibility debate rather than a binary choice [S54].
Who should carry governance and oversight authority: independent non-state bodies, states, or a broader multistakeholder mix
Speakers: Pascal Schneiders, On-site participant, Frances Douglas-Thompson, Francesco Vecchi
A holistic governance approach should support the long-term viability of journalism, not only label harmful content (Pascal Schneiders) States have positive obligations to guarantee a safe, pluralistic, and rights-respecting online environment and should not outsource governance entirely to private companies (On-site participant) Oversight should be independent, transparent, and designed to avoid political capture or discrimination (On-site participant) Responsibility for safe information environments should not fall only on users but also on states, platforms, media, and political actors (Frances Douglas-Thompson) Defining what counts as AI-generated content is itself a regulatory challenge, especially when AI is embedded in ordinary work processes (Francesco Vecchi)
Speakers agreed that governance is needed but differed over who should exercise authority. Pascal argued that decisions over which content should be positively flagged should be made independently of government or the state, through transparent criteria and repeated review, and later linked oversight to pluralistic bodies similar to those in public-service media [153-155][297-301]. By contrast, a Council of Europe participant insisted that states cannot outsource responsibility to private companies and must define rules, assess risks, ensure transparency, create independent oversight, and guarantee remedies [245-249]. Frances also framed responsibility as shared among governments, platforms, and users who publish content rather than assigned exclusively to one actor [203-207]. Francesco added another complicating dimension by noting that even defining what counts as AI-generated content is difficult when AI is embedded in ordinary work processes, making any oversight model harder to operationalize [263].
POLICY CONTEXT (KNOWLEDGE BASE)
This reflects a longstanding governance debate. UN digital policy emphasizes long-established multistakeholder institutions and calls for collective efforts that maintain interoperability across legal and regulatory differences [S62]. Other AI governance materials argue for collaborative responsibility across states, private sector, civil society, and international organizations [S60]. Earlier Internet governance analysis also highlights tension between stronger governmental roles and broader participatory mechanisms in technical and policy decisions [S57].
How specific responsibility should be assigned in the session conclusions
Speakers: On-site participant, Francesco Vecchi, On-site participant, Janice Richardson
Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic) Political parties themselves may be major producers or amplifiers of misinformation and should bear responsibility (On-site participant)
An unexpected but clear disagreement arose over the wording of the final session message on responsibility. One participant proposed explicitly adding private companies or technology companies to the list of responsible actors in addition to states and media [377-382]. Another participant proposed also mentioning civil society organizations and suggested removing political parties as too colloquial or derivative of state obligations [382]. Francesco explicitly disagreed with removing political parties, arguing that not all parties are part of the state and that political parties and movements often spread misinformation, so they should remain named [383]. Another participant then argued for keeping the wording more general and function-based so as not to miss organizations that are classified differently in different countries [385-398]. This showed disagreement not on the need for shared responsibility, but on how specifically to distribute and name it in governance language [364-365][377-398].
Whether Europe needs a more unified approach or a more interoperable and flexible one across jurisdictions
Speakers: On-site participant, Francesco Vecchi, Smee Cujic, Frances Douglas-Thompson
Fragmented national and platform approaches make enforcement difficult because AI-generated material circulates globally (On-site participant) European cooperation and regulatory alignment are necessary to manage cross-border AI harms effectively (On-site participant) Europe already has experience coordinating through shared frameworks like the DSA and should continue joint enforcement (On-site participant) Session conclusions called for stronger cooperation between states and more unified or interoperable approaches across jurisdictions (Smee Cujic)
Participants agreed that cross-border cooperation is necessary, but differed over whether the goal should be a unified model or interoperable diversity. The Armenian participant argued that differing regulations across countries make control extremely difficult and emphasized cooperation among states to create a more unified approach [271-274]. In the closing messages, Smee summarized this as a call for stronger cooperation because AI material is generated globally while approaches differ across jurisdictions [416-418]. Another participant suggested that regulatory frameworks should be aligned as far as possible [419-421]. Francesco responded that he personally preferred the concept of interoperability rather than necessarily homogeneous rules, indicating a less centralized model of coordination [422]. Frances also linked fragmentation to platform and country differences in technological approaches [413-415].
POLICY CONTEXT (KNOWLEDGE BASE)
This maps onto established European and international policy tensions between harmonization and interoperability. EU-related discussion points to a preference in some areas for horizontal common rules to reduce fragmentation [S58], while broader UN framing stresses compatibility and interoperability across differing jurisdictions rather than strict uniformity [S62]. Historical AI policy discussion likewise notes calls for international harmonisation of standards to avoid fragmentation [S63].
Unexpected Differences
Disagreement over whether political parties should be explicitly named as responsible actors in the final messages
Speakers: On-site participant, Francesco Vecchi, On-site participant
Political parties themselves may be major producers or amplifiers of misinformation and should bear responsibility (On-site participant) Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic)
This disagreement was unexpected because the room largely shared concern about misinformation in political campaigns, yet conflict emerged over the drafting of responsibility. One participant suggested removing political parties from the responsibility list as too colloquial or because obligations should flow through states [382]. Francesco directly opposed this, arguing that many political parties and movements are not part of the state and are often active spreaders of misinformation, so they should remain explicitly named [383]. This was less a disagreement over the problem than over whether political actors should be singled out in final governance language [361-365][382-383].
POLICY CONTEXT (KNOWLEDGE BASE)
Relevant context comes from UN language that all stakeholders should refrain from using or amplifying disinformation for political purposes, which supports naming political actors where appropriate [S54]. Historical discussion of political advertising and campaign practices also shows that parties and campaign ecosystems can be active sources of manipulation and disinformation, strengthening the case for explicit attribution [S65].
Disagreement over whether final messages should name specific actors like private companies and civil society or remain functionally general
Speakers: On-site participant, On-site participant, Janice Richardson, Frances Douglas-Thompson
Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic)
This was unexpected because it arose not over substantive goals but over drafting strategy. One participant wanted private or technology companies explicitly added [377-382]. Another wanted civil society organizations included as well [382]. Janice then suggested keeping the language more general and framed around functions, warning that country-to-country legal categories differ and actor lists may omit important entities [391-398]. Frances deferred the wording issue for later editing [399-404]. The disagreement revealed uncertainty about whether precision or generality is better for multistakeholder governance messages [364-365][377-404].
POLICY CONTEXT (KNOWLEDGE BASE)
UN information integrity and digital governance briefs explicitly assign roles to different actor classes, including member states, digital platforms, news media, business actors, and other stakeholders [S54] [S62]. AI governance materials similarly frame responsibility as distributed across states, private sector, civil society, and international organizations [S60]. This gives clear policy precedent for actor-specific formulations rather than purely abstract language.
Disagreement over whether the right cross-border goal is regulatory alignment/unification or interoperability
Speakers: On-site participant, Francesco Vecchi
European cooperation and regulatory alignment are necessary to manage cross-border AI harms effectively (On-site participant) Session conclusions called for stronger cooperation between states and more unified or interoperable approaches across jurisdictions (Smee Cujic)
This disagreement was relatively technical and emerged late in the messaging phase rather than the substantive debate. A participant proposed that cooperation should involve regulatory frameworks being aligned as far as possible [419-421]. Francesco responded that he preferred interoperability to homogeneity, indicating a more flexible approach [422]. The difference was not over whether states should cooperate, but over what kind of convergence should be pursued across jurisdictions [416-422].
POLICY CONTEXT (KNOWLEDGE BASE)
This is a well-established policy distinction. UN digital governance language emphasizes interoperable transparency and safety measures and active policy compatibility across jurisdictions [S62]. European digital policy debates also stress interoperability and legal certainty in cross-border governance [S58], while some AI policy discussions advocate harmonisation of standards to reduce fragmentation [S63].
Overall Assessment

The main disagreements centered on the effectiveness of labeling and watermarking, the balance between user resilience and state/institutional responsibility, the proper design of oversight and governance, and the form of cross-border coordination across Europe [173-182][191-207][245-260][271-274][292-301][332-350].

Moderate. The speakers mostly agreed on the core diagnosis that AI-generated and manipulative content threatens information integrity, democratic processes, and user autonomy, but differed significantly on policy emphasis and implementation design. This suggests broad consensus on the problem but ongoing contestation over the most legitimate and workable mix of technical, educational, regulatory, and institutional responses.

Partial Agreements
These speakers agreed on the goal of improving information integrity and user protection, but disagreed on the route. Frances supported visible markers as part of the response while warning they are not sufficient and may create false inferences [18][173-182]. Pascal agreed labels may play some role but argued that inoculation, literacy, and making trusted content easier to find are more sustainable than trying to label everything [145-150]. The Council of Europe participant agreed on the need for transparency but insisted it must sit inside a public-interest, accountability, and rights framework [245-260]. Gabija and Francesco both accepted the goal of protecting integrity but shifted emphasis toward human sense-making and broader cognitive impacts rather than technical labels [157-162][332-350].
Speakers: Frances Douglas-Thompson, Pascal Schneiders, On-site participant, Gabija Skučaitė, Francesco Vecchi
Visible markers as a starting point, not a complete solution (Frances Douglas-Thompson) Labels can help transparency but may create false trust in unlabeled content and are hard to scale across platforms (Frances Douglas-Thompson) Audience-facing labels have mixed effectiveness because users notice and interpret them selectively (Pascal Schneiders) Inoculation and literacy approaches may be more sustainable than trying to label all deceptive content (Pascal Schneiders) Labeling AI-generated content does not automatically solve discrimination, manipulation, or amplification harms (On-site participant) The key long-term response is strengthening human sense-making rather than relying on labels alone (Gabija Skučaitė) AI-generated content is already reshaping beliefs and cognition, so integrity cannot be addressed only through simple labels (Francesco Vecchi)
There was broad agreement on the goal of building resilience against misinformation and AI harms, but disagreement over the balance between empowering users and imposing institutional duties. Janice stressed user literacy and resilience capacities including control, communication, confidence, and co-regulation [69-79]. Frances questioned whether this asks too much of users and especially young people [191-194]. The Council of Europe participant argued the balance should move more strongly toward state positive obligations, rule-setting, and remedies [245-249]. The final session message reflected a compromise around shared responsibility beyond users alone [364-365].
Speakers: Janice Richardson, Frances Douglas-Thompson, On-site participant, Smee Cujic
Young people and all users need to understand not only AI but also the regulation shaping digital environments (Janice Richardson) User resilience depends on capacities such as control, community, connectedness, communication, confidence, and co-regulation (Janice Richardson) Responsibility for safe information environments should not fall only on users but also on states, platforms, media, and political actors (Frances Douglas-Thompson) States have positive obligations to guarantee a safe, pluralistic, and rights-respecting online environment and should not outsource governance entirely to private companies (On-site participant) Session messages emphasized shared responsibility across states, media, and other actors rather than users alone (Smee Cujic)
Speakers shared the goal of creating effective governance for AI-enabled information harms, but differed on implementation. Janice emphasized that Europe already has a substantial regulatory basis in GDPR, DSA, DMA, the AI Act, and the AI Framework Convention [60-68]. The Council of Europe participant agreed that states must take responsibility but stressed public obligations, independent oversight, and remedies [245-249]. Pascal agreed on the need for governance but placed more emphasis on pluralistic independent oversight and support for journalism rather than government deciding content status [153-155][292-301]. Francesco added that any governance design must also confront the definitional difficulty of what counts as AI-generated in mixed human-AI workflows [263].
Speakers: Pascal Schneiders, On-site participant, Francesco Vecchi, Janice Richardson
A holistic governance approach should support the long-term viability of journalism, not only label harmful content (Pascal Schneiders) Stronger news media reduce susceptibility to misinformation by providing verified information and exposure to multiple perspectives (Pascal Schneiders) States have positive obligations to guarantee a safe, pluralistic, and rights-respecting online environment and should not outsource governance entirely to private companies (On-site participant) Defining what counts as AI-generated content is itself a regulatory challenge, especially when AI is embedded in ordinary work processes (Francesco Vecchi) Existing European instruments such as GDPR, DSA, DMA, the AI Act, and the AI Framework Convention already provide a regulatory basis for protecting users (Janice Richardson)
Participants agreed on the goal of cross-border European coordination against AI-related harms. The Armenian participant called for cooperation and a more unified approach because AI-generated content is global [271-274]. Another participant pointed to existing European cooperation through the DSA and related bodies as a strong foundation for joint enforcement [277-282]. In the conclusions, this became a call for stronger cooperation because approaches differ across jurisdictions [416-418]. Francesco, however, preferred interoperability over complete homogeneity, showing agreement on the objective but a difference on the institutional form it should take [422].
Speakers: On-site participant, Francesco Vecchi, Smee Cujic, On-site participant
European cooperation and regulatory alignment are necessary to manage cross-border AI harms effectively (On-site participant) Europe already has experience coordinating through shared frameworks like the DSA and should continue joint enforcement (On-site participant) Session conclusions called for stronger cooperation between states and more unified or interoperable approaches across jurisdictions (Smee Cujic)
Takeaways
Key takeaways
AI labeling and watermarking were broadly seen as useful transparency tools, but not sufficient on their own to ensure information integrity. Visible labels can have unintended effects: users may selectively notice them, interpret them differently, distrust labeled content automatically, or wrongly assume unlabeled content is trustworthy. Current technical solutions for identifying AI-generated content are fragmented across platforms and fragile when content is altered, reposted, compressed, or screenshotted. Transparency should be embedded in a broader public-interest and human-rights framework; labeling alone does not address manipulation, discrimination, amplification, or emotionally persuasive harms. AI-generated and AI-mediated content is already reshaping cognition, beliefs, and political opinion formation, making information integrity a broader societal and democratic issue. Digital literacy and AI literacy were emphasized as central long-term responses, including understanding how AI works, how synthetic content is produced, how algorithmic bias operates, and how regulation shapes digital environments. User resilience was framed as multidimensional, involving control, community, connectedness, communication, confidence, and co-regulation, rather than relying only on individual vigilance. Human sense-making was highlighted as essential: participants stressed that people must be able to distinguish reality from synthetic or manipulative content, and that academia has an important educational role. Responsibility for information integrity should not rest only on users; states, platforms, media, political actors, and other relevant institutions also bear responsibility. States were described as having positive obligations to ensure a safe, pluralistic, rights-respecting online environment and should not outsource governance entirely to private companies. Europe’s approach was characterized as people-centric, rights-based, and precautionary, supported by existing frameworks such as the GDPR, DSA, DMA, AI Act, and the AI Framework Convention. Political manipulation was identified as a major risk area, especially during elections, with examples of AI-generated fake interviews, fake media branding, deepfakes, and synthetic personas used to influence voters. Political parties themselves were identified by some participants as producers or amplifiers of misinformation and therefore as actors that should also bear responsibility. Anonymous pseudo-media accounts and unclear origin of synthetic content were seen as especially dangerous because audiences cannot determine who is behind manipulative campaigns. A coordinated European response was seen as necessary because AI-generated content circulates across borders while enforcement and regulation remain uneven. Participants emphasized that the goal should not be framed as innovation versus safety, but as building governance that enables AI opportunities while mitigating systemic risks. A broader systemic response should include support for trustworthy journalism and information ecosystems, since stronger news media can reduce susceptibility to misinformation. Information integrity was also framed as connected to cybersecurity, democratic resilience, cognitive security, and sovereignty of mind, not merely as a media or fact-checking issue.
Resolutions and action items
Draft session messages were presented and received broad consensus from the room. A session message was accepted that AI poses increasing threats to information integrity and is increasingly used during political campaigns. A session message was accepted that responsibility should not fall only on users, but should be shared by states, media, and other relevant actors; participants discussed adding private companies and civil society to this framing. A session message was accepted in principle that labeling must be placed in a broader public-interest framework and that labels alone do not resolve discrimination, social harm, or misleading perceptions of truthfulness. A session message was accepted that technological approaches are currently fragmented across platforms and jurisdictions. A session message was accepted that stronger cooperation between states and more unified or interoperable approaches are needed because AI-generated material circulates globally. Participants were invited to suggest further edits to the wording of the messages after the session, with the understanding that there would still be time to refine language and punctuation after the conference. The discussion surfaced practical action directions rather than assigned tasks: improve AI and digital literacy, strengthen enforcement of existing European regulation, develop independent oversight, and support trustworthy journalism and public-interest information ecosystems.
Unresolved issues
How exactly to define ‘AI-generated content’ in regulatory terms, especially when AI is embedded in ordinary work and content production processes. Whether visible labeling should be treated as a primary intervention or only as one limited tool among broader governance, literacy, and ecosystem measures. Who should ultimately be responsible for enforcing AI labeling and related transparency obligations: governments, platforms, users, independent bodies, or a combination of actors. How oversight should be structured so that it is independent, transparent, representative, and protected from political capture or discrimination. Whether and how to update existing instruments such as the Code of Practice on Disinformation for the current AI-driven information environment. How to design labels so they improve understanding without creating false reassurance about unlabeled content or causing user fatigue. Whether emotionally manipulative or discriminatory AI-generated content can be effectively mitigated through transparency mechanisms at all, given that such content may remain persuasive even when labeled. How to scale technical provenance and watermarking systems across platforms and jurisdictions when current systems are siloed and easily disrupted by reposting or editing. How to ensure coordinated cross-border enforcement where national legal approaches differ significantly. What concrete governance tools and capacity-building models are available for smaller states and weaker digital ecosystems facing AI-enabled influence operations. How responsibility should be distributed among states, platforms, media, political parties, private companies, civil society organizations, and transnational actors in the final wording of the session messages.
Suggested compromises
Participants suggested broadening the responsibility message beyond users, with proposals to include not only states and media but also private companies and civil society organizations. When disagreement arose over listing specific actors, a compromise was suggested to keep the wording more general and refer instead to organizations or actors with relevant regulatory or governance functions, to avoid excluding entities treated differently across countries. On cross-border regulation, a compromise suggestion was to aim for unified or at least interoperable regulatory frameworks rather than insisting on completely identical national rules. The session accepted broad substantive consensus on the draft messages while leaving wording details open for later refinement, allowing participants to propose edits after the session rather than forcing final wording immediately.
Thought Provoking Comments
Janice Richardson argued that young people and all users have a responsibility not only to use digital tools, but also to understand regulation, and she framed Europe’s approach to information integrity as a people-centric, rights-based model distinct from the US market-driven model and China’s state-control model.
This was insightful because it widened the discussion beyond AI labeling and watermarking into governance literacy. She reframed the issue from being only about technical detection of synthetic media to being about understanding the legal and geopolitical systems shaping information environments. Her comparison of Europe, the US, and China introduced a strategic dimension that linked information integrity to digital sovereignty and democratic resilience.
This comment set a broader conceptual frame for the rest of the session. After this, the conversation no longer focused narrowly on whether content can be labeled, but on who governs, according to what values, and with what legal tools. It also paved the way for later interventions about state obligations, cross-border cooperation, and the need for regulatory alignment.
Speaker: Janice Richardson
Janice Richardson’s idea of the ‘seven C’s to user resilience’—control, community, connectedness, communication/reporting, confidence, co-regulation, and competence—along with her warning that young people want not just detection tools but understanding of AI, algorithmic bias, attention economy, and sycophancy.
This was thought-provoking because it resisted a simplistic solutionist approach. Instead of treating resilience as mere media literacy or personal skepticism, she described it as a layered social and institutional capacity. Her point that users also need confidence in institutions and co-regulation challenged the tendency to place the burden solely on individuals.
This became a recurring thread in the discussion. Frances later explicitly asked whether too much responsibility was being placed on users, and several participants from the floor responded directly to that dilemma. It helped shift the conversation from ‘how do we label content?’ to ‘what kind of ecosystem helps people navigate manipulated content?’
Speaker: Janice Richardson
Pascal Schneiders explained that visible AI labels may reduce trust in labeled content, but can also create unintended effects such as the implied truth effect, selective attention, warning fatigue, and limited influence on users who already agree with the content due to confirmation bias.
This was one of the most analytically rich comments because it challenged the central assumption behind the session’s starting point: that more transparency markers necessarily improve information integrity. By bringing in empirical findings from communication research, he showed that labels are psychologically and socially complex, and may even backfire.
This was a major turning point. After Pascal’s intervention, the discussion moved away from viewing labeling as an obvious good and toward questioning its limits. Frances explicitly built on this by asking whether labels can create false confidence in unlabeled content. Later audience interventions and final messages also reflected this more cautious, nuanced position.
Speaker: Pascal Schneiders
Pascal Schneiders concluded that instead of trying to label all deceptive AI content, which is practically impossible, platforms and regulators should combine inoculation strategies with making verified content from trusted sources ‘must-be-found.’
This was insightful because it replaced a reactive moderation mindset with a more systemic model: strengthen cognitive resistance and information quality rather than only flag bad content. It also shifted attention toward the visibility and support of reliable journalism as a governance strategy.
This introduced a constructive alternative and influenced later discussion about strengthening news media, oversight, and public-interest frameworks. It also gave the session a more policy-oriented direction, showing that the answer may lie not only in identifying false content but in redesigning the information ecosystem around trustworthy sources.
Speaker: Pascal Schneiders
Frances Douglas-Thompson asked whether visible AI labeling empowers users or instead sends the wrong message—for example, that unlabeled content is therefore reliable—and whether resilience places too much responsibility on users, especially young people.
This was thought-provoking because it synthesized tensions raised by earlier speakers into a clear normative question. It challenged both techno-solutionism and overreliance on literacy narratives. Her framing highlighted the risk that transparency tools may unintentionally simplify a much more complex problem.
This comment directly opened the floor into deeper engagement. Multiple later speakers responded to this exact tension: whether responsibility should lie with users, states, platforms, political parties, or civil society. It transformed the Q&A from a collection of examples into a more principled debate about accountability.
Speaker: Frances Douglas-Thompson
The participant from Portugal noted that in the country’s legislative elections, one political party was responsible for around 80% of online misinformation, and stressed that political parties themselves must be held responsible if they use manipulative or AI-assisted content.
This was insightful because it grounded the discussion in a concrete electoral case and broadened responsibility beyond platforms and users. It challenged any tendency to treat disinformation as a purely technological problem by pointing to political actors as active producers of manipulation.
This shifted the discussion toward democratic accountability and later influenced the drafting of the session messages, where political parties remained explicitly named as responsible actors despite some debate. It helped anchor the abstract discussion in real political consequences.
Speaker: On-site participant (Inej, YouthDig)
The participant from Kosovo described how AI-generated fake interviews, synthetic people, and ‘slopaganda’ are being used around elections, often through pseudo-media accounts with no clear ownership, and emphasized the danger of not knowing who stands behind such content.
This was highly thought-provoking because it exposed the operational reality of synthetic disinformation: not only false content, but false media identities, emotional manipulation, and hidden actors. Her intervention also highlighted transparency’s limit when the problem is not just the artifact but the infrastructure of anonymous influence.
Her comments intensified the urgency of the discussion and added practical evidence from election monitoring. They pushed the conversation toward questions of traceability, enforcement, and institutional preparedness, especially in countries without comprehensive AI law. This also reinforced later concerns about state obligations and cross-border governance.
Speaker: On-site participant (Hurya Mameti)
The Council of Europe participant argued that it is too much to place responsibility on individuals alone; states have positive obligations to ensure a safe online environment, and labeling, watermarking, and moderation are insufficient unless embedded in a public-interest, human-rights framework with independent oversight, transparency, and remedies.
This was one of the strongest normative interventions because it challenged the default balance of responsibility in digital governance. It reframed transparency not as an end in itself but as a tool that must serve accountability, equality, and redress. It also raised the important question of what happens when technical systems fail and whose voices are most likely to be dismissed.
This significantly deepened the discussion. It moved the conversation from technical effectiveness to legitimacy, discrimination, and institutional design. Several subsequent remarks—about state roles, cross-border alignment, independent oversight, and the wording of the final messages—echoed this intervention.
Speaker: On-site participant (Council of Europe anti-discrimination department)
The participant from Armenia stressed that while states do have a role, regulation must avoid violating freedom of information and must involve cooperation among states; otherwise, content created anywhere will evade fragmented national regimes.
This was insightful because it highlighted the tension between regulation and fundamental rights while also drawing attention to a core structural problem: jurisdictional fragmentation. It added an international-law and enforcement perspective that had not been fully articulated before.
This comment helped shift the conversation from domestic governance to interoperability and international coordination. It directly influenced the final message drafting, where cooperation between states and more unified regulatory approaches became one of the agreed conclusions.
Speaker: On-site participant (Armenia, Prosecutor General’s office)
Jessica argued that AI governance should not be framed as a trade-off between innovation and harm prevention; instead, Europe should build systems that maximize opportunities such as education, productivity, and civic participation while mitigating systemic risks such as toxic amplification, gender-based abuse, and disinformation.
This was thought-provoking because it resisted a binary framing and proposed a more mature governance lens. Rather than asking whether AI is good or bad, she suggested that institutions should be designed to enable beneficial uses while constraining harms.
Her comment balanced the discussion, which had become heavily focused on threats. It reintroduced the idea of proportional governance and innovation-friendly regulation, linking back to Janice’s description of European regulatory philosophy. It added nuance before the conversation moved toward final recommendations.
Speaker: On-site participant (Jessica, YouthDig)
In response to the question about whether transparency is overstimulated as a solution, Pascal Schneiders argued that the best way to fight misinformation is to strengthen and fund news media, because research shows people who use news media are less likely to believe misinformation.
This was insightful because it shifted the debate from detecting harmful content to sustaining trustworthy institutions. It suggested that information integrity is not only about countering bad content but about preserving the social infrastructures that make truth-seeking possible.
This broadened the policy horizon of the session. It connected platform governance to media sustainability and made the discussion more structural. It also reinforced the move away from narrow technical fixes and toward ecosystem-level solutions.
Speaker: Pascal Schneiders
The participant from North Macedonia argued that information integrity is no longer just a media or disinformation issue but a cybersecurity and global security issue, especially for smaller states with weaker institutional capacities, and asked what governance tools can realistically keep pace with fast-moving generative AI threats.
This comment was thought-provoking because it reframed the issue as one of national and international security, not merely content moderation. It also brought in the perspective of smaller states and civil society actors who are overwhelmed by the scale and speed of synthetic influence operations.
This intervention expanded the conversation into resilience, defense, and institutional asymmetry. Francesco responded by linking the topic to foreign policy, cognitive sovereignty, and defense. It helped consolidate the idea that information integrity must be approached across multiple policy domains.
Speaker: On-site participant (Liliana, North Macedonia)
Gabija Skučaitė argued that in an AI-saturated environment where labeling cannot solve everything, society must return to the human capacity for sense-making—understanding context, source, and meaning—and that academia has a major role in teaching people to distinguish the real world from its virtual overlays.
This was a reflective and philosophical intervention that deepened the discussion beyond policy and technology. It reminded the group that information integrity is ultimately tied to human judgment, interpretation, and trust, not just to technical markers.
Her comment served as a closing reframing of the entire session. It pulled together themes of literacy, trust, and resilience and gave the discussion a human-centered conclusion. This perspective also aligned with the final messages emphasizing awareness and human sense-making rather than labeling alone.
Speaker: Gabija Skučaitė
Overall Assessment

The key comments collectively transformed the session from a relatively narrow discussion about AI labeling and watermarking into a much broader debate about governance, democracy, trust, human rights, media systems, and cognitive resilience. Janice Richardson and Pascal Schneiders were especially influential in shifting the discussion away from simple technical fixes: Janice by situating the issue in a European regulatory and geopolitical framework, and Pascal by showing that labels can have limited or even counterproductive effects. Frances Douglas-Thompson then sharpened this tension by explicitly asking whether transparency and resilience might misplace responsibility onto users. Audience interventions added concrete electoral examples from Portugal and Kosovo, normative pressure around state obligations and public-interest oversight from the Council of Europe, and structural concerns about cross-border cooperation, security, and institutional capacity. By the end, the conversation had evolved into a multi-layered understanding of information integrity: one that sees AI-generated content as not just a content problem, but an ecosystem problem involving political actors, platform design, legal coordination, independent oversight, journalism, and the human ability to make sense of reality.

Follow-up Questions
Should visible markers/labels for AI-generated or synthetic content be used universally, and are they always beneficial for users?
This is central to the session’s theme because labeling is presented as a possible policy response, but speakers questioned whether labels actually help users, convey harm accurately, or create false trust in unlabeled content.
Speaker: Frances Douglas-Thompson; Francesco Vecchi
Can AI-generated content always be visibly labeled in practice?
This matters because technical and governance solutions depend on whether universal detection and labeling are feasible across formats, platforms, and contexts.
Speaker: Frances Douglas-Thompson
Where should the line be drawn between AI-assisted and AI-generated content for regulatory purposes?
This is important because effective regulation requires a workable definition of what counts as AI-generated content, especially when many people use AI tools in routine work.
Speaker: Francesco Vecchi; Armenia participant from the Prosecutor General’s Office
How effective are visible disclosures, labels, or disclaimers in helping audiences distinguish synthetic from non-synthetic deceptive content?
Pascal explicitly noted that current knowledge is limited, making this a major research gap for designing evidence-based platform or policy interventions.
Speaker: Pascal Schneiders
How prevalent are deceptive synthetic images, audio, and video on social media, and what effects do they have on different people?
He stated that we know very little about prevalence and effects, yet policy pressure is high. Better evidence is needed to calibrate responses proportionately.
Speaker: Pascal Schneiders
What design features make AI labels understandable, visible, and effective for users?
He highlighted that recognition depends on size, color, shape, placement, and context, so research is needed to determine best practices for label design.
Speaker: Pascal Schneiders
Do labels create unintended effects such as false trust in unlabeled content, user fatigue, forgetting, backfire effects, or implied truth effects?
This is important because interventions may worsen misinformation dynamics if users interpret unlabeled content as truthful or become desensitized to warnings.
Speaker: Pascal Schneiders; Frances Douglas-Thompson; Olga Martinez
Would detailed explanatory labels and techniques like the ‘sandwich principle’ work better than simple labels?
He suggested these approaches may improve retention and correction effectiveness, indicating a need for comparative research on intervention formats.
Speaker: Pascal Schneiders
Can inoculation approaches, including gamified misinformation education, improve resilience against deceptive AI-generated content?
Both pointed toward resilience-building and literacy. This is important because prevention may be more scalable than trying to label all harmful content.
Speaker: Pascal Schneiders; Janice Richardson
Should governance prioritize ‘must-be-found’ strategies that elevate verified trustworthy content rather than attempting to label all deceptive AI content?
He proposed this as a potentially more realistic alternative given the scale of online content and the limits of labeling.
Speaker: Pascal Schneiders
Who should decide which sources or content are trustworthy enough to be positively flagged, and how should that process be governed?
This is important because trust designation raises accountability, independence, pluralism, and anti-discrimination concerns.
Speaker: Pascal Schneiders; Council of Europe participant (Iti/It the Beckall)
How can young people and the public be better educated not only about AI literacy but also about regulation and legal protections?
She argued that resilience depends on understanding both technology and the legal instruments meant to protect users, making this a key policy and educational follow-up area.
Speaker: Janice Richardson
What do young people most want to learn about AI, including LLMs, algorithmic bias, AI sycophancy, attention economy, fact-checking, and control over self-generated content?
She reported these as concrete learner needs from projects she works on, indicating areas for curriculum development and further study.
Speaker: Janice Richardson
Is too much responsibility being placed on users, especially young people, to determine what is true online?
This is important for deciding the balance between user resilience, platform obligations, and state duties in online information governance.
Speaker: Frances Douglas-Thompson; Council of Europe participant (Iti/It the Beckall)
What should the balance be between state obligations, platform responsibility, media responsibility, political party responsibility, and user responsibility for AI labeling and information integrity?
Responsibility allocation was a recurring unresolved issue, critical for designing enforceable and legitimate governance frameworks.
Speaker: Frances Douglas-Thompson; Inej; Council of Europe participant (Iti/It the Beckall); Hurya Mameti; message-drafting participants
How should political parties be regulated or held accountable for using AI-generated misinformation during elections?
Both raised election-related cases showing that political actors may themselves spread AI-driven misinformation, making democratic integrity a priority research and policy area.
Speaker: Inej; Hurya Mameti
How can harmful anonymous or pseudo-media accounts using AI-generated content be identified and governed when the actors behind them are unknown?
This is important because enforcement is difficult when disinformation is spread by opaque actors posing as media outlets without traceable ownership.
Speaker: Hurya Mameti
How should internal media regulations and transparency standards incorporate AI-generated material, including watermarking of illustrative AI images?
She described an ongoing effort in Kosovo, suggesting a need for comparative work on newsroom standards and practical implementation models.
Speaker: Hurya Mameti
When watermarking or labeling systems fail or are manipulated, whose content becomes less trusted and whose voices become easier to dismiss?
This matters because technical failures may have unequal social impacts, especially on already marginalized groups or politically contested speech.
Speaker: Council of Europe participant (Iti/It the Beckall)
Can emotionally manipulative AI-generated content remain effective even when users know it is AI-generated?
This is important because transparency alone may not mitigate harms if emotional amplification and algorithmic spread still drive engagement.
Speaker: Olga Martinez; Council of Europe participant (Iti/It the Beckall)
How can transparency obligations be embedded within a broader human-rights and public-interest framework rather than treated as an end in itself?
She stressed that transparency should serve accountability, equality, access to redress, and non-discrimination, suggesting a broader governance research agenda.
Speaker: Council of Europe participant (Iti/It the Beckall)
Should oversight of AI labeling and content governance be state-led, privately led, or managed through independent pluralistic bodies?
This unresolved question is important because institutional design affects legitimacy, rights protection, and resistance to politicization.
Speaker: Council of Europe participant (Iti/It the Beckall); Pascal Schneiders
How can countries cooperate to create more unified or interoperable regulatory approaches to AI-generated content across jurisdictions?
Cross-border content flows make fragmented national rules hard to enforce, so international cooperation and interoperability emerged as a major follow-up area.
Speaker: Armenia participant from the Prosecutor General’s Office; Jessica from YouthDig; final message-drafting participants
How can existing instruments such as the Digital Services Act code of practice on disinformation be adapted or renewed for the AI era?
He noted that current frameworks predate the present AI wave, making reform or updating of existing governance tools a concrete policy research need.
Speaker: Francesco Vecchi
How can governance maximize AI’s opportunities for innovation, education, civic participation, and productivity while preventing systemic harms such as misinformation and abuse?
She explicitly framed this as avoiding a false trade-off, pointing to the need for governance models that support both innovation and risk mitigation.
Speaker: Jessica from YouthDig
Should information integrity be treated as part of cybersecurity and cyber resilience frameworks, especially in smaller states with weaker institutional capacity?
She argued that AI-driven influence operations are now a security issue, suggesting the need to explore integrated governance models linking misinformation, cyber resilience, and national security.
Speaker: Liliana from North Macedonia
What governance models and practical tools are available for protecting information integrity, particularly for smaller or developing digital ecosystems?
She explicitly asked about available tools and governance approaches, indicating demand for comparative policy research and capacity-building models.
Speaker: Liliana from North Macedonia
Are current institutions and policies keeping pace with the speed of generative AI development?
This is important because slow governance adaptation may leave societies exposed to rapidly evolving synthetic media threats.
Speaker: Liliana from North Macedonia
How can social trust in institutions, education, and information systems be rebuilt in a context where facts and fiction are increasingly blurred?
Both pointed to erosion of trust and human sense-making as foundational issues, suggesting a broader societal research agenda beyond technical labeling solutions.
Speaker: Pari Esfandiari; Gabija Skučaitė
How should education systems and academia develop human sense-making capacities to help people distinguish reality from AI-saturated or synthetic environments?
This is important because several participants argued that labeling alone is insufficient and that durable resilience depends on cognitive and educational capacities.
Speaker: Gabija Skučaitė; Janice Richardson
How fragmented are current technological approaches to AI provenance and watermarking across platforms and countries, and can they be made interoperable?
Fragmentation was repeatedly noted in relation to C2PA, SynthID, and platform-specific systems, making interoperability and scalability a key area for further research.
Speaker: Frances Douglas-Thompson; final message-drafting participants; last on-site participant
Are current provenance tools such as C2PA and SynthID actually capable of solving the problem, given metadata loss through screenshots, compression, and cross-platform sharing?
She explicitly described the limitations of these systems, indicating the need for technical evaluation of robustness and real-world effectiveness.
Speaker: Frances Douglas-Thompson
Have users unknowingly shared AI-generated content, and what does that imply for public awareness and platform design?
She invited reflection on this user experience, which points to a research area on user behavior, detection limits, and inadvertent amplification of synthetic media.
Speaker: Frances Douglas-Thompson
What is the biggest threat to information integrity in Europe today?
This overarching question remained open and generated election-related examples, indicating the need to map and prioritize threat categories such as deepfakes, emotional disinformation, and political manipulation.
Speaker: Frances Douglas-Thompson; Inej; Hurya Mameti
How can quality journalism and news media be strengthened or funded as a response to misinformation and AI-driven deception?
He cited research linking news use with lower belief in misinformation, making media sustainability a significant area for further policy development and study.
Speaker: Pascal Schneiders

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