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
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.
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]
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
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.
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
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.
Excuse me, Janice.
Yes?
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?
No, I’m here and I can hear you.
Okay. Okay. Let’s go. I’ll ask Janice again.
Can you see my slides?
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.
Now, can you see my phone?
Yes, now we can.
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.
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.
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.
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.
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.
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…
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.
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.
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.
Thank you very much for your contribution. Anyone else who would like to take the floor, please?
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.
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?
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.
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?
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.
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.
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.
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 ….
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.
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.
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
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?
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?
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.
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
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?
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.
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.
Okay, so we have number four. Technological approaches are fragmented at current. Is that the technological approaches are fragmented at current? Or currently?
At the time being, I think. No, at the time being.
Is it meant that technological approaches differ from country to country? What is the idea?
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.
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.
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.
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
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
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.
Overview The rapid development of artificial intelligence (AI) presents profound philosophical, educational, and governance challenges and opportunities for the global community. To address these di…
Table: Survey of AI risks evolution August 2023 August 2024 August 2025` Longtermism, the philosophy of focusing on far-future risks, has gained significant influence. Many…
From TikTok’s innovative Election Centre for EU states to Meta’s robust Elections Operations Centre and Google’s Jigsaw Unit launching campaigns across TikTok and YouTube—these efforts are reshaping w…
They argue that young people need to be educated about generative AI to be informed users. This highlights the importance of ensuring that individuals understand the potential implications and risks o…
This does not mean constant suspicion, but a more informed form of scepticism. Just as society adapted to earlier waves of misinformation, it begins to develop what might be called social antibodies a…
For much of the public debate around artificial intelligence, attention has been fixed on capability: how powerful models are becoming, what tasks they can automate, and how close they are to matching…
Meta Platforms is developing labels that allow creators to identify images produced using their AI technology. Alessandro Paluzzi, a developer, shared screenshots of an in-app message on social media …
Meta’s decision to change how it labels AI-modified content on Instagram, Facebook, and Threads signifies another advancement in the company’s approach to generative AI. The visibility of AI’s involve…
In Where policy and practice collide, Monica Bulger et al. point out that they thereby transcend the administrative and cultural borders that have historically been essential for effecting regulatory …
She notes that platforms are often criticized for both over-censorship and under-moderation. Major Discussion Point Challenges of Misinformation Platforms use fact-checking, labeling, and reduci…
The European Union AI Act: calling a spade a spade The EU Artificial Intelligence Act Another “first” is the European Union’s Artificial Intelligence Act, also known as the “EU AI Act”, the fir…
Clear frameworks for accountability and oversight are necessary to address issues arising from AI’s use. 5. Legal and Regulatory Frameworks: Guidelines and Regulations: Strong rules and guidelines ar…
As human rights issues are increasingly brought up in standardisation discussions, there will be a push for human-rights-by-design approaches to be embedded into technical standards that form part of …
ChatGPT, the AI-powered tool that has taken the world by storm, has now caught governments’ eyes. In reaction to user complaints and worrying reports (such as those by Europol and the OECD) over data …
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 ideal for governance which is rooted in the principle of people’s sovereignty, …
The UN Security Council had its first meeting on AI and international peace and security. Having in mind that diplomacy typically moves at a glacial pace (which is understandable due to many factors t…
The spread of mis- and disinformation can undermine public trust in electoral institutions and the electoral process itself – such as voter registration, polling and results – and potentially result i…
WS #255 AI and disinformation: Safeguarding Elections Session report Speakers Knowledge Graph In-depth Analys…
In the second half of 2019 several steps were taken towards implementing the Call. The Global Internet Forum to Counter Terrorism (GIFCT) will become an independent organisation that will drive and co…
“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].
“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].
“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].
“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].
“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].
“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].
“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].
“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.
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.
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.
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.
Disclaimer: This is not an official session record. DiploAI generates these resources from audiovisual recordings, and they are presented as-is, including potential errors. Due to logistical challenges, such as discrepancies in audio/video or transcripts, names may be misspelled. We strive for accuracy to the best of our ability.
Related event

