Development

OECD maps AI and citizen participation

The OECD has published a report examining how AI could support citizen participation and democratic innovation while highlighting the safeguards needed for its responsible use.

The report, Artificial Intelligence and the Future of Citizen Participation, was approved and declassified by the OECD Public Governance Committee on 22 June 2026. It was produced as part of the OECD Public Governance Reviews series in collaboration with the Bertelsmann Stiftung.

The report says public participation can help governments design better policies and strengthen trust. It cites OECD trust findings showing that people who feel they have a say in government decisions are far more likely to report high trust in government.

The OECD notes that governments have long relied on digital technologies, including online platforms and civic tech tools, to expand public participation. AI represents the next stage of this evolution, with governments increasingly experimenting with tools for consultation, deliberation, communication and policy analysis.

The report is based on desk research and analysis of 50 AI use cases in participation processes from 22 OECD member and partner countries. It proposes a typology to help public officials and practitioners understand where AI tools may be useful and what challenges they may address.

Based on an analysis of 50 AI use cases from 22 OECD member and partner countries, the report proposes a typology covering nine categories of AI applications, including information development, sense-making, translation, transcription, virtual assistance, moderation, facilitation, simulation and participation architecture.

These tools can support both front-office activities, where citizens interact directly with government, and back-office activities, where public administrations design, analyse and manage processes internally.

According to the OECD, AI could make participation processes more accessible and efficient by helping governments analyse large volumes of public input, improve communication, reduce administrative costs and broaden participation.

Sense-making tools can help analyse large amounts of text submitted during consultations. Translation and transcription tools can make processes more accessible across languages and formats, while virtual assistants can help people navigate information about citizen participation opportunities.

AI can also support moderation and facilitation. The report says such tools may help prevent spam, hate speech or manipulation in online discussions, and could support live deliberation by identifying common ground or structuring debate.

However, the OECD cautions against treating AI as a simple fix for democratic challenges. It says technology alone cannot solve problems such as weak links between participation processes and actual policy decisions.

The report also highlights ethical, operational and societal risks, including algorithmic bias, opaque decision-making, hallucinations, cybersecurity threats, digital exclusion and declining public trust if AI systems are poorly designed or deployed.

The OECD also highlights the risks of inaction, noting that governments may miss valuable opportunities if they avoid AI tools even when they could be applied responsibly.

The report says governments should establish guardrails for AI use in citizen participation, including transparency, compliance with democratic values, protection of civic space, attention to data divides and low-tech alternatives for citizens with limited digital access.

It also calls for stronger enablers, including AI literacy, skills development, citizen engagement in the design and governance of AI systems, open standards where appropriate, and support for scaling successful pilots.

The OECD concludes that most public-sector use of AI in citizen participation remains experimental. It argues that lasting benefits will depend on transparent governance, human oversight and continued efforts to strengthen democratic participation beyond technology alone.

Why does it matter?

Governments are increasingly exploring AI as a way to make public participation more accessible, scalable and responsive. The OECD’s report shows that AI can support consultation, deliberation and policy analysis, but only when accompanied by safeguards that protect transparency, inclusion and democratic accountability.

The report also reinforces a broader shift in AI governance from technical capability to institutional design. By emphasising human oversight, civic participation, digital inclusion and democratic values, the OECD argues that AI should enhance, not replace, the processes that underpin public trust and democratic decision-making.

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South Korea unveils national AI infrastructure strategy

South Korea’s Ministry of Science and ICT has announced a comprehensive whole-of-government strategy to expand the country’s AI computing infrastructure and strengthen national AI capabilities.

The strategy is built around three pillars: expanding AI computing infrastructure, developing next-generation AI models, and accelerating AI adoption across public services. To strengthen computing capacity, the government aims to secure 18,000 high-performance GPUs by the first half of 2026, with 10,000 acquired through a public-private National AI Computing Centre and another 8,000 deployed as part of a sixth national supercomputer.

To advance domestic AI development, the government plans to launch a flagship initiative provisionally named the ‘World’s Best LLM’ project. Selected AI teams will receive dedicated access to computing resources, datasets and research funding. A Global AI Challenge will also be launched to attract leading domestic and international researchers, with winners offered startup support or positions within flagship AI projects.

Talent development is another key pillar. South Korea plans to expand its AI Frontier Labs beyond New York into Europe and other regions, establish AI Transformation graduate schools through industry-university partnerships and offer competitive salaries, research funding and relocation support to attract leading international AI experts.

The third pillar focuses on deploying domestically developed AI models across public services, including healthcare, education, the legal system, public administration, disaster management and content creation.

Why does it matter?

South Korea’s strategy reflects a growing global shift towards treating AI as strategic national infrastructure rather than simply a commercial technology. By combining investments in computing capacity, foundation models, talent development and public-sector deployment, the government is pursuing a comprehensive approach to strengthening technological competitiveness and digital sovereignty.

The plan also illustrates how competition in AI increasingly extends beyond model development alone. Access to high-performance computing, skilled researchers and coordinated industrial policy is becoming just as important as algorithmic innovation, with governments playing a more active role in shaping national AI ecosystems.

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UNESCO advances AI ethics training in Mexico’s judiciary

UNESCO has delivered the first specialised in-person training programme on the ethical use of AI for judicial professionals in Mexico City, aiming to support the responsible adoption of AI across the country’s justice system.

More than 50 civic judges, mediators and public defenders took part in the programme, which focused on ensuring AI supports judicial processes in Mexico while respecting transparency, accountability and human rights.

The programme introduced participants to the opportunities and risks associated with AI in judicial decision-making while providing practical guidance on applying ethical safeguards in courts and public institutions.

The training was based on UNESCO’s Recommendation on the Ethics of Artificial Intelligence, adopted by all UNESCO Member States in 2021, and incorporated the organisation’s newly published Guidelines for the Use of AI Systems in Courts and Tribunals.

The initiative forms part of a broader UNESCO and European Commission project supporting countries in implementing AI governance frameworks through capacity building, technical assistance and policy tools.

Participants were also introduced to UNESCO’s practical governance tools, including the Readiness Assessment Methodology, the Ethical Impact Assessment framework and Global Toolkit on AI and the Rule of Law for the Judiciary.

UNESCO emphasised that although AI is increasingly being incorporated into judicial and administrative processes, human oversight must remain central. The organisation said well-trained judicial professionals are essential to ensuring AI improves access to justice without replacing human judgement or undermining fundamental rights.

Why does it matter?

As AI becomes more common in courts and public administration, effective governance depends not only on regulation but also on the ability of judges and other legal professionals to understand the technology’s capabilities, limitations and risks. Training programmes such as this can help ensure AI supports judicial work without compromising due process, transparency or fundamental rights.

The initiative also demonstrates UNESCO’s broader approach to AI governance, combining international ethical principles with practical implementation tools. By equipping judicial institutions with guidance, assessment frameworks and technical expertise, the organisation aims to help countries translate high-level AI principles into everyday public-sector practice.

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OpenAI previews GPT-5.6 Sol model with stronger safeguards

OpenAI has begun a limited preview of GPT-5.6 Sol, a new flagship model in its new GPT-5.6 family, which also includes Terra and Luna. The company said all three models are expected to become generally available in the coming weeks.

The company said the preview is initially limited to a small group of trusted partners. OpenAI said it shared its release plans and model capabilities with the US government before launch and is initially limiting access at the government’s request.

The company said it does not consider government pre-release access an appropriate long-term default. Instead, it described the limited preview as a temporary measure while working with the US administration on a repeatable release framework linked to a cybersecurity Executive Order.

OpenAI described GPT-5.6 Sol as its most capable model to date, highlighting improvements in agentic coding, biology and cybersecurity while saying a broader set of evaluation results will be published when the model becomes generally available.

For coding, OpenAI said GPT-5.6 Sol set a new state of the art on Terminal-Bench 2.1, which tests command-line workflows involving planning, iteration and tool coordination.

The company also reported improvements in biology workflows. On GeneBench v1, which evaluates long-horizon genomics and quantitative biology tasks, OpenAI said the model performed better than GPT-5.5 while using fewer tokens.

Cybersecurity is a major focus of the preview. OpenAI said GPT-5.6 Sol is its most capable model yet for cybersecurity tasks, including vulnerability research and exploitation-related workflows.

OpenAI said the model performs better at identifying and helping remediate vulnerabilities than at carrying out end-to-end offensive cyber operations. According to the company, GPT-5.6 Sol did not exceed the Cyber Critical threshold under its Preparedness Framework.

OpenAI said the GPT-5.6 release includes its most robust safeguards to date, with configurations tailored to each model’s capabilities. The company said these safeguards are intended to constrain prohibited offensive use while preserving access for legitimate work such as code review, vulnerability research, patch development, debugging, security education and defensive testing.

Safeguards include model-level protections, real-time generation checks, account-level monitoring, differentiated access controls, enforcement mechanisms and ongoing testing. OpenAI said some higher-risk requests may be delayed or blocked during the preview period.

The company said it devoted more than 700,000 A100-equivalent GPU hours to automated red-teaming, complemented by third-party expert testing, to evaluate the model’s resilience against jailbreak attempts.

During the preview, GPT-5.6 models will initially be available through the API and Codex to selected trusted partners and organisations. OpenAI said broader access for ChatGPT, Codex and API users is planned soon.

During the preview, GPT-5.6 models will be available through the API and Codex to selected partners. OpenAI said broader access across ChatGPT, Codex and the API is planned soon. It also announced pricing for the model family and said GPT-5.6 Sol will launch on Cerebras in July, initially for a limited group of customers.

Why does it matter?

GPT-5.6 Sol illustrates how frontier AI releases are becoming increasingly governed by phased deployment, targeted access and extensive safety testing rather than immediate public availability. OpenAI’s emphasis on cybersecurity evaluations, automated red-teaming and layered safeguards reflects growing efforts to manage the risks associated with increasingly capable foundation models.

The rollout also highlights the evolving relationship between AI companies and governments. By combining limited pre-release access, enterprise deployment and structured safety frameworks, OpenAI is helping shape emerging norms for how advanced AI systems are evaluated, governed and introduced into real-world use.

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Spain calls for stronger AI rules in labour relations

Spain’s Second Vice President and Minister of Labour and Social Economy, Yolanda Díaz, has called for stronger regulation of AI and algorithmic decision-making in the workplace.

Speaking at the University of Oxford, Díaz said the debate should no longer focus on whether AI should be used, but on how to organise its deployment so that labour rights and fundamental rights are protected.

She argued that AI and algorithms already influence recruitment, hiring, performance evaluation, promotion, contract changes, dismissals and pension-related decisions. According to Díaz, stronger oversight is needed to ensure transparency and accountability where algorithmic management affects workers.

Spain’s Rider Law was presented as an early example of algorithmic transparency in labour relations, requiring digital labour platforms to disclose information about algorithms that affect working conditions and access to work.

Díaz also criticised proposals to deregulate AI, arguing that technological development should serve the public good rather than concentrate power among a small number of technology companies.

Her intervention comes as the EU rules for high-risk AI systems in areas including employment are set to apply later than initially expected. The European Commission says these rules will apply from 2 December 2027 under the new AI Omnibus enforcement timeline.

Díaz said governments should actively shape how AI is used in the workplace through regulation and public policy, rather than leaving the future of work to market forces alone.

Why does it matter?

AI is increasingly used to manage recruitment, performance assessment, scheduling, promotion and dismissal decisions. Spain’s position places algorithmic transparency and worker rights at the centre of the European AI debate, especially as the EU’s employment-related high-risk AI obligations are delayed. The intervention also shows how member states may move ahead with stricter national rules when they believe EU-level protections are too slow or insufficient.

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OECD proposes policy priorities for AI use in SME sustainable finance

The Organisation for Economic Co-operation and Development (OECD) has published a policy paper examining how AI and digital tools can help small and medium-sized enterprises (SMEs) gain better access to sustainable finance, where they remain significantly underrepresented.

The paper maps practical applications of AI and digital tools across the entire financing lifecycle, from sustainability data generation and reporting by SMEs to loan origination, credit assessment and portfolio monitoring by financial institutions. The OECD notes that AI has the potential to support the front, middle and back office of lending operations rather than a single stage of the financing process.

Drawing on country examples and recent initiatives, the OECD argues that technological adoption must be accompanied by appropriate governance. It identifies four policy priorities: developing interoperable data infrastructure, strengthening verification mechanisms, creating incentives for SME sustainability reporting and ensuring accountable use of AI in financing decisions.

Why does it matter?

Small and medium-sized enterprises account for much of economic activity and employment but often struggle to access sustainable finance because they lack the resources to produce the data and reporting required by lenders and investors. AI could reduce these costs by automating data collection, reporting and credit assessment, making green finance more accessible to smaller businesses.

The OECD also emphasises that technology alone will not close the financing gap. Real progress depends on reliable data infrastructure, effective verification and clear governance to ensure AI-supported financing decisions are transparent, accountable and fair, preventing existing inequalities from being reinforced.

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UNESCO summit backs ethical AI governance in Latin America and the Caribbean

Representatives from more than 20 Latin American and Caribbean countries have met in Santo Domingo for a regional summit on AI ethics and governance.

The Third Ministerial and High-Level Authorities Summit on the Ethics of Artificial Intelligence in Latin America and the Caribbean took place on 25 and 26 June in the Dominican Republic. It was organised by UNESCO, the Dominican Republic’s Government Office of Information and Communication Technologies (OGTIC), and CAF – Development Bank of Latin America and the Caribbean.

The summit brought together ministers, senior government officials, multilateral organisations, academics, private-sector representatives and civil society to strengthen regional cooperation and accelerate the implementation of public policies aligned with the UNESCO Recommendation on the Ethics of Artificial Intelligence.

UNESCO said the meeting builds on earlier summits held in Santiago in 2023 and Montevideo in 2024, as well as ongoing work to develop a shared regional roadmap for responsible AI governance.

Anne Lemaistre, Director of the UNESCO Regional Office in Havana, said AI presents significant opportunities but also challenges that require coordinated regional action.

Raquel Peña, Vice President of the Dominican Republic, said the region had decided to come together to address one of the greatest challenges of the time. She said the task is to harness AI’s potential while upholding the principles that should guide its development and use.

Peña also reaffirmed the Dominican Republic’s commitment to a human-centred approach to AI. She said AI must be developed and governed with ethics, responsibility, and a profoundly human vision.

Christian Asinelli, Corporate Vice President of Strategic Programming at CAF, said Latin America and the Caribbean should play a stronger role in shaping global AI governance rather than simply adapting to international developments.

Raúl Fuentes, European Union Ambassador to the Dominican Republic, said the EU wants to work with the region on practical solutions as well as shared principles. He said the AI component of the EU-Latin America and the Caribbean Digital Alliance is supporting knowledge exchange, innovation, sovereignty, and a human-centred approach.

During the summit, Dominican authorities announced the forthcoming adoption of a national Artificial Intelligence Code of Ethics, developed with input from government, academia, civil society and the private sector, and aligned with international standards.

Edgar Batista, Director General of OGTIC, said the initiative reinforces the Dominican Republic’s commitment to digital transformation centred on public value. He said the country will contribute actively to the development of regional standards for digital governance.

Delegations are discussing AI governance, institutional capacity, responsible innovation, and regional cooperation. The talks aim to support ethical and regulatory frameworks for safe, inclusive, and trustworthy technological development.

The Dominican Republic will also assume the Pro Tempore Presidency of the regional mechanism, reinforcing its role in promoting ethical, inclusive and sustainable AI governance across Latin America and the Caribbean.

Why does it matter?

The summit reflects growing efforts by Latin American and Caribbean countries to develop a shared approach to AI governance based on ethics, inclusion and sustainable development. Regional cooperation can help governments build institutional capacity, align regulatory approaches and ensure AI policies reflect local priorities rather than relying solely on frameworks developed elsewhere.

The meeting also highlights the increasing importance of regional voices in global AI governance. By grounding discussions in UNESCO’s Recommendation on the Ethics of Artificial Intelligence and strengthening collaboration among governments, international organisations and other stakeholders, the region is seeking to play a more active role in shaping international norms for trustworthy AI.

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ECB highlights gap between AI adoption and productivity

Firms across the euro area are increasingly adopting AI, but only a small share are integrating it deeply enough to generate meaningful productivity gains. Data from the European Central Bank’s SAFE survey shows that although more than 70% of firms report using AI in some form, only 7% have integrated it deeply into their core operations.

Firms that use AI intensively are more likely to embed it in core business processes rather than limiting it to routine or experimental tasks. They are also more likely to innovate, expand their product offerings and align AI investments with long-term growth strategies.

Competitive pressure is also driving deeper AI adoption, particularly among established firms responding to technologically advanced rivals. However, skills shortages, legacy systems and financing constraints continue to limit many companies’ ability to scale AI effectively.

Why does it matter? 

The findings suggest that simply adopting AI is not enough to generate significant economic benefits. Productivity gains appear to depend on integrating AI into core business functions, innovation strategies and long-term investment plans rather than using it only for isolated or experimental tasks.

The survey also highlights structural challenges facing Europe’s digital transformation. Without investment in skills, financing and modern digital infrastructure, many firms may struggle to move beyond basic AI adoption, potentially widening the productivity gap between AI leaders and businesses that lack the resources to scale the technology.

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China links AI data centre to direct green electricity supply

China has launched what state media described as the country’s first AI data centre powered entirely through a direct green electricity connection, linking AI infrastructure more closely with renewable energy supply.

The facility has started operations in Zhongwei, in the Ningxia Hui Autonomous Region, a western region that has become central to China’s computing and clean-energy strategy.

Operated by China Telecom Ningxia Branch, the data centre is built to a wind-powered liquid-cooling standard. According to the company, the facility achieves a Power Usage Effectiveness rating of 1.15, supporting high-performance AI computing while reducing energy use compared with conventional data centres.

The project is part of China’s wider effort to connect computing capacity with renewable energy resources. Ningxia has already hosted large-scale projects that directly supply green electricity to data centre clusters, including a 500 MW solar facility in Zhongwei linked to China’s computing-electricity coordination model.

Zhongwei is also a key node in China’s ‘Eastern Data, Western Computing’ initiative, which aims to shift data-intensive workloads from eastern economic centres to western regions with more land and renewable-energy resources.

The new facility is expected to support AI computing, data processing and industrial digital transformation. It could also increase demand for servers, AI chips, liquid-cooling equipment and other parts of China’s domestic technology supply chain.

The project highlights how energy availability and efficiency are becoming central to AI infrastructure policy, as countries and companies face rising power demand from data centres and advanced AI systems.

Why does it matter?

AI infrastructure is becoming an energy-policy issue. China’s green-powered data centre model shows how governments may try to match growing AI compute demand with renewable-energy deployment, regional data-centre planning and industrial supply-chain development. For China, the project also supports a broader strategy of moving compute workloads westward, reducing pressure on eastern cities and using renewable resources in regions such as Ningxia. The challenge will be proving that such facilities can deliver reliable AI computing at scale while genuinely reducing emissions across the full power and data-centre system.

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Google proposes a balanced approach to AI governance in the US

Google has published a policy paper proposing a two-track approach to AI governance in the United States, separating oversight of frontier AI models from rules for widely deployed AI applications.

The paper argues that AI policy should avoid what Google describes as a false choice between over-regulation and no regulation. Instead, the company calls for a pragmatic, evidence-based framework that treats the most advanced AI systems differently from everyday AI tools such as chatbots.

For frontier AI, Google proposes the creation of a Frontier AI Regulatory Organisation, or FARO. The industry-funded body would operate under federal oversight and develop standards for safety, security, incident reporting and transparency.

Google says FARO could set scientific benchmarks for frontier capabilities, particularly in areas such as cybersecurity and chemical, biological, radiological and nuclear risks. It could also oversee independent audits and require frontier AI companies to publish and follow safety frameworks before releasing highly capable models.

For widely deployed AI applications, Google argues that the federal government should rely mainly on existing legal frameworks, with targeted updates where needed. The paper says policy should focus on real-world harms and outputs rather than micromanaging AI development.

The company identifies several priority areas, including workforce preparedness, child safety, information integrity, copyright, privacy and energy infrastructure for data centres.

Google supports measures such as AI interaction guidelines for children, disclosures that chatbots are not sentient, rules for self-harm-related queries, watermarking and provenance standards for generative AI, privacy-enhancing technologies and workforce reskilling.

The paper presents the model as a way to address national security and consumer protection risks while preserving US leadership in AI development.

Why does it matter?

Google’s paper is a significant industry intervention in the US AI policy debate. Its two-track model reflects a broader governance trend: frontier AI is increasingly being treated as a national security and safety issue, while everyday AI applications are being handled through consumer protection, child safety, privacy, copyright and labour policy. The proposal could influence federal discussions, but it also reflects Google’s own regulatory preferences, including industry-funded oversight, confidential audit reports and reliance on existing law for many AI applications.

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