Google explores AI-assisted scientific discovery through Gemini for Science

Google has introduced Gemini for Science, a collection of AI tools and experiments designed to support scientific research workflows. The initiative combines capabilities from systems including Co-Scientist, AlphaEvolve, Empirical Research Assistance, and NotebookLM.

According to Google, the AI-based tools are intended to support tasks such as hypothesis generation, literature analysis, and computational research.

Google said three experimental tools will initially be released through Google Labs, focusing on hypothesis generation, computational discovery and literature analysis. The company also announced Science Skills for Google Antigravity, integrating multiple life sciences databases and research tools.

Google said the programme is being developed in collaboration with more than 100 research institutions and scientific organisations. The company also highlighted research partnerships and conference collaborations linked to AI-supported scientific research.

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Study examines local warming effects linked to data centre expansion

New research suggests that expanding data centre infrastructure may contribute to localised warming effects similar to urban heat islands.

The study, published in the Journal of Engineering for Sustainable Buildings and Cities, examined several data centres in the Phoenix metropolitan area and found measurable increases in surrounding air temperatures. Researchers reported temperature increases ranging from approximately 1.5 to 4 degrees Fahrenheit within areas located downwind from facilities.

Data centres generate waste heat through cooling systems used to support high-performance computing operations.

According to the researchers, large data centre campuses can generate concentrated thermal output associated with high energy consumption.

The findings come as global demand for AI, cloud computing, and digital services continues to drive the construction of new facilities across the US and other regions. Northern Virginia, Phoenix, and several European locations have become major hubs for hyperscale infrastructure development.

The researchers said the observed effects differ from traditional urban heat islands because of continuous cooling activity and continuous energy consumption. The study noted that clusters of facilities may produce cumulative effects that require further investigation.

The researchers discussed potential implications for energy demand, infrastructure planning, and surrounding communities. The study said elevated local temperatures could influence cooling demand and related environmental conditions.

Furthermore, scientists stressed that additional peer-reviewed research remains necessary to determine the long-term climatic significance of large-scale data centre expansion.

Why does it matter?

The findings reflect growing scrutiny surrounding the environmental footprint of AI infrastructure. Data centres already face criticism over electricity consumption, water usage, and grid pressure. The possibility that concentrated AI infrastructure may also influence local temperatures introduces another dimension to debates surrounding sustainable digital expansion.

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Anthropic challenges US government restrictions on AI technology use

The US AI company Anthropic attempted to challenge a decision by the US Department of Defense to ban the use of its technology in government institutions. The company had been given 30 days to file an appeal after the Pentagon classified its products as a ‘supply chain risk’.

However, instead of following the proper procedures and sending the appeal to the designated official address, the head of Anthropic’s legal team emailed it directly to two DoW officials.

Reports cited by multiple outlets suggested disagreements between Anthropic and US defence authorities over potential military applications of AI systems and related safety restrictions. The reports referred to discussions about military and intelligence-related AI applications. After Pentagon asked Anthropic to bend its rules and company refused, Anthropic was latter classified as a ‘supply chain risk’.

Reports described the designation as an unusual step involving a major US AI company. According to reports, federal agencies were instructed to suspend use of Anthropic technologies following the classification decision.

Anthropic CEO Dario Amodei has said the company previously cooperated with the US military in areas such as intelligence analysis, modelling and simulation, operational planning, and cyber operations. However, he has also argued that the government’s action was not legally justified and indicated that the company has no choice but to challenge it in court.

Amodei went on to say that Anthropic does not believe private companies should be involved in operational military decision-making, particularly when systems could enable fully autonomous weapons or mass surveillance.

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CNIL reports record complaints and data breaches

The French data protection authority CNIL reported a record year in 2025 for complaints, fines and data breach notifications, while preparing for new responsibilities under the EU AI Act.

CNIL received 20,150 complaints in 2025, up 10% from 2024. The complaints covered issues linked to work, commerce, real estate, social networks and data breaches, with around 1,900 complaints directly concerning breaches.

The authority also received 6,167 data breach notifications, an increase of 9.5% from 2024. Hacking accounted for one in two reported incidents, while cybersecurity failures represented one-third of investigations and nearly 30% of sanctions.

In total, CNIL carried out 323 investigations and issued 259 corrective measures, including 83 sanctions worth nearly €487 million. Two major sanctions accounted for a large share of the total, while the simplified procedure introduced in 2022 allowed faster action in less complex cases.

Cybersecurity will become an even bigger enforcement focus in 2026, with CNIL planning to devote 50% of its controls and enforcement actions to data security. Checks will focus on organisations affected by breaches, those subject to complaints and sectors processing large volumes of sensitive or highly personal data.

The report also highlights CNIL’s role in supporting professionals and public authorities. In 2025, it processed 539 health authorisation applications, handled 1,351 professional advice requests, delivered 90 opinions on draft laws or regulatory texts and launched seven public consultations.

On AI, CNIL is already designated to monitor prohibited uses under the EU AI Act and is expected to become the market surveillance authority for certain high-risk AI systems, including in biometrics, migration, law enforcement, employment and education.

The authority also published AI resources for designers and developers, developed a traceability tool for open-source AI models and joined the PANAME project with ANSSI, Inria and PEReN to test whether AI models process personal data.

Why does it matter?

CNIL’s annual report shows how data protection enforcement is increasingly shaped by cybersecurity and AI. Record breach notifications and complaints point to growing pressure on organisations to secure personal data, while CNIL’s future AI Act responsibilities place the authority at the centre of France’s oversight of prohibited and high-risk AI systems.

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EU publishes draft guidance on high-risk AI classification under AI Act

The European Commission has opened a public feedback period on draft guidance related to high-risk AI systems under the EU AI Act.

The draft guidance is intended to help providers and deployers determine whether AI systems fall within the Act’s high-risk category. The document includes examples illustrating how classification criteria may apply in different situations.

Under the AI Act, high-risk classification applies to specified AI use cases that may affect health, safety, or fundamental rights. According to the Commission, the guidance is intended to support consistent interpretation of the rules before compliance obligations take effect.

The document has been made available through the AI Act Single Information Platform. Stakeholders, including businesses, public authorities, researchers, civil society organisations, and citizens, may submit comments until 23 June 2026. The Commission said additional guidance related to high-risk AI obligations is expected at a later stage.

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Google and UNICEF launch AI-focused education partnership

Google and UNICEF have launched a global partnership focused on AI-supported education initiatives and digital learning infrastructure.

The initiative, funded through Google.org, will initially focus on Brazil, India, Pakistan, and Kenya. According to the organisations, the programme will address areas including literacy, numeracy, teacher support, and digital access.

Google said the partnership aims to combine AI tools with UNICEF’s education programmes to support localised digital learning systems. The initiative includes teacher training, educational technology deployment, and AI-supported learning tools.

Several Google AI tools, including Gemini, NotebookLM, and ReadAlong, will support the initiative. UNICEF said the programme is intended to support digital skills, AI literacy, and the integration of AI tools into classrooms.

The organisations also highlighted goals related to digital inclusion and education access in regions facing infrastructure limitations.

UNICEF said annual reports will assess programme implementation and scalability.

Why does it matter?

Governments, international organisations, and technology companies are increasingly positioning AI as a major component of future education systems. Partnerships involving AI-driven learning tools may significantly influence digital literacy, educational access, workforce preparation, and long-term economic development.

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Google launches Gemini 3.5 with advanced agentic AI capabilities

Google has announced Gemini 3.5, a new family of AI models designed to combine frontier-level reasoning with stronger agentic capabilities across consumer, developer and enterprise products.

The company is launching the series with Gemini 3.5 Flash, which it describes as its strongest agentic and coding model so far. Google said the model is built for complex, long-horizon tasks, including multi-step workflows, coding, document analysis and enterprise automation.

According to Google, Gemini 3.5 Flash outperforms Gemini 3.1 Pro on several coding and agentic benchmarks, including Terminal-Bench 2.1, GDPval-AA and MCP Atlas, while also improving multimodal reasoning. The company also claimed the model is significantly faster than other frontier models when measured by output tokens per second.

Google said the model can support agentic workflows through its Antigravity development platform, including the use of collaborative subagents for coding, financial document preparation, data analysis and other complex enterprise tasks. It also highlighted richer multimodal capabilities, including interactive web interfaces, visual reasoning and generative UI experiences.

Gemini 3.5 Flash is available through the Gemini app, AI Mode in Google Search, the Gemini API in Google AI Studio, Android Studio, Google Antigravity and Gemini Enterprise products. Google also said Gemini 3.5 Pro is being used internally and is expected to roll out next month.

The announcement also introduced Gemini Spark, a personal AI agent powered by Gemini 3.5 Flash. Google said Spark is designed to run continuously, helping users navigate digital tasks and take action under their direction. It is starting with trusted testers, with a beta planned for Google AI Ultra subscribers in the US.

Alongside performance improvements, Google said Gemini 3.5 was developed under its Frontier Safety Framework. The company said it strengthened safeguards related to cybersecurity and chemical, biological, radiological and nuclear risks, while adding safety training and interpretability tools intended to reduce harmful outputs and mistaken refusals.

The launch reflects a wider industry shift from conversational AI assistants towards systems that can plan, coordinate and execute tasks across digital environments, with major AI companies increasingly competing on agentic workflows, coding performance, multimodal interaction and enterprise integration.

Why does it matter?

Gemini 3.5 shows how the AI race is moving beyond chatbot performance towards systems that can act across software, workflows and enterprise environments. Faster agentic models could help automate coding, analysis and business operations, but they also raise governance questions around supervision, safety, accountability and how much autonomy users and organisations should give to AI agents.

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OpenAI expands verification tools as AI slop blurs digital trust

OpenAI has announced new measures to strengthen the provenance and verification of AI-generated content as synthetic media becomes more widespread across digital platforms.

The company said it is expanding support for Content Credentials and compliance with the Coalition for Content Provenance and Authenticity (C2PA) standard. The standard uses metadata and cryptographic signatures to help ensure that information about a piece of media travels securely with the content, including details on where it came from and how it may have been created or edited.

OpenAI also plans to integrate Google DeepMind’s SynthID watermarking into images generated through ChatGPT, Codex and the OpenAI API. The company said SynthID will add an invisible watermarking layer that complements C2PA metadata, particularly when metadata is removed, lost, or altered during file conversions, resizing, screenshots, or other transformations.

The company said it is adopting a multi-layered provenance approach that combines metadata, watermarking and public verification tools rather than relying on a single detection method. According to OpenAI, C2PA can provide richer contextual information, while SynthID can help preserve a signal when metadata does not survive.

The move also connects to wider concerns about AI slop, as synthetic media and low-quality AI-generated content become harder to distinguish from authentic images. Provenance tools cannot solve the problem alone, but they can provide clearer signals about how digital media was created or modified.

OpenAI also previewed a public verification tool that will allow users to check whether ChatGPT, Codex or the OpenAI API generated an uploaded image. The tool will look for provenance signals, including Content Credentials and SynthID watermarks. Still, OpenAI said it will not make a definitive judgement when no signal is detected, because provenance signals can sometimes be removed.

At launch, the verification tool is limited to OpenAI-generated content. The company said it aims to support wider cross-platform verification efforts in the coming months and eventually expand support to more types of online content.

Why does it matter?

AI-generated content is becoming harder to distinguish from authentic media, fuelling concerns around AI slop, deepfakes and manipulated information. Provenance systems such as Content Credentials, watermarking and verification tools can help people understand where media came from and whether it was generated or modified by AI. However, OpenAI’s approach also shows the limits of technical detection: metadata can be stripped, watermarks may not survive every transformation, and no single method can provide complete certainty.

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Spotify verification badges target AI slop and voice impersonation

Spotify has introduced new verification badges for podcast shows and reinforced its impersonation policies as AI tools make it easier to clone voices, imitate creators and produce misleading audio content.

The new Verified by Spotify badge will appear on selected podcast show pages and in search results. According to Spotify, the badge identifies a show as the official presence of a creator, publisher or brand, helping listeners understand who they are hearing and giving creators a clearer way to establish authenticity on the platform.

Also, Spotify said the badge will begin appearing on select shows and expand over the coming months. Eligibility will depend on factors including sustained listener activity, good standing under Spotify’s platform policies and verified audience authenticity, including safeguards against fraudulent or bot-driven listenership.

Spotify is introducing podcast verification badges and stronger impersonation rules as AI slop expands into audio, voice cloning and creator identity.
Image via Magnific

The company also reaffirmed that its policies prohibit unauthorised impersonation, including through AI voice cloning. Spotify said it will remove podcast shows and content that impersonate another creator or host’s likeness without permission, whether through AI-generated voices or other methods.

However, the move shows how concerns over AI slop are expanding from low-quality visual and written content into audio and identity. In podcasting, the issue is not only whether synthetic content is poor quality, but whether listeners can tell when a voice, host or show is authentic.

Spotify framed the update as part of a broader effort to protect creators and give listeners clearer signals about who they are hearing. The company said podcasting depends on trust between creators and audiences, and that authenticity is becoming more complex as AI lowers the barrier to producing and distributing audio content.

Why does it matter?

AI slop is moving beyond visual clutter and into identity. In podcasting, synthetic voices and impersonation can directly affect the creator’s reputation, listener trust and the credibility of audio platforms. Spotify’s verification badges and impersonation rules show how platforms are beginning to respond not only with content moderation, but with identity signals, authenticity checks and stronger creator protections.

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Why digital literacy is becoming a strategic necessity in the AI era

For many years, digital policy focused mainly on connectivity. Governments measured progress through broadband expansion, smartphone adoption, internet penetration, and device accessibility. Success was defined by how many people could connect to digital networks rather than by how effectively they could navigate increasingly complex digital environments.

However, AI, algorithmic recommendation systems, synthetic media, and platform-driven information ecosystems are now forcing policymakers to reconsider this approach. Access alone no longer guarantees empowerment. Citizens may be connected to the digital world while remaining vulnerable to manipulation, misinformation, cyber fraud, algorithmic bias, and AI-generated deception.

 Book, Publication, Advertisement, Text, Poster, Paper

Digital literacy is therefore evolving into something much broader than technical competence. It gradually includes media literacy, AI literacy, critical thinking, online safety awareness, privacy protection, and the ability to evaluate the credibility of information sources. In many countries, digital literacy is becoming directly linked to democratic resilience, social cohesion, economic competitiveness, and national security.

International organisations, regulators, and governments are beginning to frame digital literacy not merely as an educational issue but as a structural policy challenge. UNESCO initiatives, EU educational frameworks, online safety regulations, and national AI strategies all point to the same conclusion: societies are entering a phase where the ability to critically navigate digital systems may become as important as traditional literacy itself.

From digital access to digital judgement

The shift from access to judgement is becoming visible across multiple policy initiatives worldwide. Early digital inclusion strategies focused on closing infrastructure gaps and improving affordability. Current discussions increasingly focus on cognitive resilience and information integrity.

For example, UNESCO’s ‘Digital Citizens for Peace’ initiative in Pakistan offers a strong example of that transition. Pakistan has more than 205 million mobile subscribers and over 116 million internet users, yet UNESCO describes a growing ‘literacy-connectivity gap’. Digital access has expanded far faster than critical media literacy capabilities, leaving many users exposed to disinformation and online manipulation.

 Flag, Pakistan Flag

Rather than relying only on reactive fact-checking, UNESCO’s programme seeks to foster long-term digital judgement. Young journalists and content creators participate in media and information literacy camps that combine mentorship, role-playing exercises, ethical communication practices, and collaborative learning. Participants are encouraged not only to recognise misinformation but also to understand the broader social consequences of hate speech, manipulation, and digital polarisation.

Such programmes reflect an important evolution in policymaking. Digital literacy is no longer treated as a narrow technical skill associated with operating software or navigating websites. Increasingly, policymakers view it as a civic competence linked to democratic participation and responsible engagement in digital spaces.

That transition matters because modern information environments are no longer passive. Algorithms actively shape what users see, recommend emotionally engaging material, and amplify content capable of driving interaction. We, as citizens, therefore, need to understand not only the information itself, but also the systems that distribute it.

AI raises the stakes

AI dramatically intensifies these challenges. Generative AI systems can now produce realistic text, audio, images, and video at scale, often with minimal cost or expertise required. As we already know, deepfakes, synthetic media, AI-generated propaganda, and automated misinformation campaigns are becoming easier to deploy and harder to identify.

Such developments are forcing governments and educational institutions to rethink how societies prepare citizens for digital environments increasingly influenced by AI systems.

The Council of the European Union has recently called for a ‘human-centred approach’ to AI in education, stressing that teachers must remain central to the learning process even as AI tools expand across classrooms.

Furthermore, the Council has highlighted several major risks associated with AI integration, including misinformation, algorithmic bias, unequal access to digital resources, excessive technological dependence, and data protection concerns.

Importantly, the Council has not framed AI literacy as a purely technical matter. Instead, European policymakers have emphasised critical reflection, ethical understanding, and responsible digital citizenship. Teachers are described not merely as users of AI systems, but as guides capable of helping students understand limitations, biases, and broader societal implications.

That distinction is critical. AI literacy cannot simply mean learning how to use AI tools productively. Communities also need to understand how such systems influence perception, automate decisions, and shape public discourse. Without these skills, populations may struggle to distinguish authentic information from synthetic manipulation.

As such, digital literacy increasingly intersects with cyber resilience. Individuals and organisations need to understand the emerging threats connected to synthetic media, AI-driven fraud, deepfake impersonation, and automated social engineering techniques.

Education systems are the first line of defence

Schools and universities are gradually becoming central pillars of digital resilience strategies. Educational institutions are expected to prepare students not only for labour markets shaped by AI but also for digital societies susceptible to manipulation and polarisation.

That challenge places considerable pressure on teachers. Many education systems still struggle with uneven digital infrastructure, insufficient training, and outdated curricula. AI adoption risks widening those gaps if implementation occurs without adequate preparation.

UNESCO initiatives reflect similar priorities globally. In Tanzania, UNESCO supported ICT teacher training programmes involving 139 ICT master trainers across 20 regions. 15 online ICT modules were integrated into broader professional development systems, helping educators build long-term digital competencies rather than relying on isolated workshops.

Such efforts reveal an important reality often overlooked in AI discussions. Technology alone does not transform education. Institutional capacity, teacher confidence, curriculum design, and long-term support mechanisms remain equally important.

 Female, Girl, Person, Teen, Pen, Head, Computer, Electronics, Laptop, Pc, Face, Writing, Ylona Garcia

Education systems also face a delicate balancing act. AI tools may improve accessibility, personalise learning experiences, and reduce administrative burdens. At the same time, overreliance on automation could weaken concentration, analytical thinking, and independent problem-solving abilities among students.

Several governments are therefore attempting to preserve human oversight while embracing technological innovation. European frameworks increasingly stress ‘digital humanism’, ensuring that AI systems support rather than replace human agency and democratic values.

Misinformation and civic resilience

The relationship between digital literacy and democratic resilience is becoming increasingly direct. Misinformation campaigns no longer operate only through fringe websites or isolated propaganda channels. False narratives now spread through mainstream social platforms, encrypted messaging applications, short-form video systems, and AI-generated media.

UNESCO’s ‘Share Responsibly’ campaign in Lebanon illustrates how policymakers are attempting to address misinformation as a social behaviour problem, not just a technological issue. Rather than focusing exclusively on platforms, the campaign highlights everyday spaces such as taxis, shops, and public areas where digital misinformation circulates through ordinary conversations and social sharing practices.

UNESCO and Lebanon launch national campaign promoting media literacy and responsible information sharing.

This approach, among other national and institutional initiatives (EU, governments, etc), recognises an important reality: misinformation spreads because people trust familiar networks and emotionally engaging narratives. Digital literacy, therefore, requires behavioural and cultural dimensions alongside technical awareness.

AI further complicates this dynamic. Synthetic voices, realistic avatars, and automated content generation systems can manufacture the illusion of public consensus. Information operations become more scalable, more personalised, and potentially more persuasive.

Growing concerns around online radicalisation, conspiracy movements, and digital polarisation explain why many governments now frame digital literacy as part of broader societal resilience strategies. Citizens capable of critically assessing digital content are less vulnerable to manipulation, foreign influence operations, and emotionally driven misinformation ecosystems.

Platform design and user autonomy

Digital literacy alone cannot solve the structural problems embedded in digital platforms themselves. Society may develop stronger critical thinking skills while remaining exposed to systems intentionally designed to maximise engagement, emotional reaction, and behavioural influence.

Regulators are increasingly recognising that platform architecture matters as much as user education.

European regulators have intensified scrutiny of recommender systems, addictive platform features, and manipulative interface design. Investigations involving major technology firms increasingly focus on algorithmic amplification, dark patterns, and risks connected to minors’ online experiences.

The UK’s Ofcom has also strengthened its focus on online safety obligations involving children, illegal content, and algorithmic harms under the Online Safety Act. Such initiatives reflect a growing understanding that digital literacy must be paired with platform accountability.

UK child safety enforcement expands as Ofcom investigates adult sites over age-check compliance.

Individuals cannot realistically bear the full responsibility of navigating opaque recommendation systems, behavioural targeting mechanisms, and AI-driven engagement architectures alone. Effective digital governance requires a dual approach: empowering users while regulating platform behaviour.

That broader regulatory environment is reshaping the way policymakers think about digital citizenship. Instead of assuming neutral technological environments, governments increasingly recognise that digital systems actively influence behaviour, attention, and perception.

AI literacy and the future workforce

Digital literacy debates increasingly extend beyond democratic resilience into labour markets and economic competitiveness. AI systems are transforming workplaces across industries, forcing workers to adapt continuously to changing technological environments.

The World Economic Forum has argued that organisations succeeding with AI are redesigning workflows around human-machine collaboration rather than simply deploying technology. HR leaders are increasingly expected to oversee continuous learning systems, workforce adaptation, and AI-related reskilling strategies.

 Adult, Female, Person, Woman, Male, Man, Indoors, Plant, Executive, Computer Hardware, Electronics, Hardware, Monitor, Screen, Face, Head, Furniture, Mobile Phone, Phone, Computer, Laptop, Pc, Cup, Chair, Ray Caesar

Research by the International Labour Organization similarly highlights growing risks of inequality if lifelong learning systems fail to evolve quickly enough. Workers lacking digital and AI-related skills may face exclusion from emerging labour markets, while technological concentration could deepen economic disparities between regions and social groups.

Such developments demonstrate that digital literacy is no longer confined to classrooms. Governments increasingly view AI and digital competencies as long-term economic infrastructure linked to productivity, competitiveness, and social stability.

National frameworks and international governance

As highlighted previously, the growing strategic importance of digital literacy is visible across national and international governance frameworks. UNESCO, the EU, Canada, China, Australia, and multiple other jurisdictions are integrating AI literacy, ethical governance, and digital resilience into broader policy agendas.

China has recently launched pilot programmes for AI ethics review and governance services, focusing on risks such as algorithmic discrimination and emotional dependence. European institutions continue to expand AI education frameworks and digital rights protections.

Despite different political systems and regulatory philosophies, many governments are converging around similar concerns. AI systems simultaneously influence education, labour markets, information ecosystems, public trust, cybersecurity, and democratic participation.

That convergence explains why digital literacy is now being discussed alongside concepts such as strategic autonomy, societal resilience, and democratic stability.

Limitations and unresolved tensions

Digital literacy initiatives nevertheless face important limitations. Awareness campaigns alone cannot resolve structural inequalities, opaque algorithms, or concentrated technological power.

There is also a risk that governments and technology firms will frame digital literacy as an individual responsibility, avoiding deeper questions about platform incentives, surveillance-based business models, and algorithmic amplification.

Citizens cannot realistically detect every deepfake, evaluate every manipulated narrative, or fully understand every AI system they encounter. Excessive reliance on individual vigilance may therefore create unrealistic expectations.

Educational inequalities present another major challenge. Wealthier regions often have stronger infrastructure, better-trained educators, and greater institutional capacity to adapt curricula. Less developed areas may struggle to implement sophisticated AI literacy programmes, potentially widening global and domestic divides.

In conclusion, digital literacy is gradually evolving into one of the defining governance challenges of the AI era. Connectivity alone no longer guarantees meaningful participation in digital societies shaped by algorithms, synthetic media, and automated systems.

Governments, regulators, and international organisations are now recognising that societies require more than infrastructure and access. Citizens need the capacity to critically evaluate information, understand AI systems, recognise manipulation, and participate responsibly in digital environments.

The next phase of digital transformation will therefore not be defined solely by technological sophistication. It will instead depend on whether societies can develop individuals capable of understanding, questioning, and shaping ever more powerful digital systems rather than passively consuming them.

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