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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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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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China’s latest supercomputer strengthens AI ambitions

China has regained the world’s leading position in supercomputing after the LineShine system became the fastest computer in the latest TOP500 ranking, replacing the US’s El Capitan at the top of the list.

The achievement marks China’s return to first place for the first time since 2017 and highlights the growing strategic importance of high-performance computing in the AI era.

Unlike many recent AI-focused supercomputers that rely heavily on graphics processing units (GPUs), LineShine achieves exascale performance using conventional central processing units (CPUs).

Beyond topping benchmark rankings, the system is expected to support scientific research, advanced simulations, climate modelling, pharmaceutical development and the training of increasingly sophisticated AI models.

The announcement also reflects the broader ambition of China to strengthen technological leadership while presenting its innovation ecosystem as a contributor to global technological development.

Europe also remains a major player in high-performance computing. Four European systems rank among the world’s ten fastest supercomputers, while the EU continues to invest in AI factories, next-generation supercomputing infrastructure and collaborative research centres.

The growing investment in supercomputers reflects how computing infrastructure is increasingly being treated as a strategic asset alongside semiconductors, cloud infrastructure and advanced data centres.

As governments increasingly link AI capabilities with economic competitiveness, scientific leadership and national security, access to world-class computing resources is becoming one of the defining factors shaping the global technology balance.

Why does it matter?

The latest TOP500 ranking underline that computing capacity is becoming a defining factor in AI development and scientific competitiveness. As frontier AI models require ever-greater computational resources for training and inference, access to world-class supercomputers is emerging as a strategic advantage alongside semiconductor manufacturing and cloud infrastructure.

China’s return to the top of the rankings also highlights the geopolitical dimension of high-performance computing. At the same time, continued European investment in AI factories and supercomputing infrastructure reflects a broader effort to strengthen technological sovereignty and reduce dependence on external computing resources as countries compete for leadership in AI and advanced research.

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UN secretary-general calls for greater transparency on AI’s climate impact

UN Secretary-General António Guterres has called on AI companies to publicly disclose the environmental impact of their operations, including carbon emissions, water consumption, and land use. Speaking at London Climate Action Week, Guterres proposed an AI Environmental Transparency Initiative, arguing that communities are often left without clear information about the environmental impact of nearby data centre developments.

Citing a UN study, Guterres said data centres consumed more electricity in 2025 than all but ten countries, accounting for around 1.5% of global electricity demand. That share could approach 3% by 2030, while AI-related water consumption and pollution are also projected to rise significantly. By 2030, that figure is projected to nearly double to close to 3 per cent, while the water use and pollution associated with AI are also expected to double within four years.

Guterres noted that coal still provides around 30% of the electricity used by data centres globally, while renewables account for approximately 27%. He called on AI companies to power their facilities entirely with renewable energy by 2030. Guterres called on AI firms to commit to powering their facilities entirely from renewable sources such as wind and solar by 2030, though existing clean energy commitments from major tech companies have already been complicated by the rapid pace of AI deployment.

Guterres linked the proposal to broader concerns about climate change and energy security, arguing that both are rooted in continued dependence on fossil fuels. He noted that the planet has just endured its eleven hottest years on record, and that last year marked the first time the three-year global temperature average broke through the 1.5 degrees Celsius threshold set by the 2015 Paris Agreement.

He also noted that renewable energy surpassed one-third of global electricity generation in 2025 for the first time, while coal’s share fell below one-third, although he cautioned that rising AI-related electricity demand could complicate progress.

Coal’s share of global generation also fell below one-third for the first time, though significant challenges remain, particularly given policy reversals in the US under President Donald Trump, who has embraced fossil fuels and cut support for renewables.

Guterres, whose term ends in December 2026, will convene world leaders again at the annual COP climate summit later this year. He reiterated calls for every major emitter to accelerate action, reduce methane emissions, and move away from coal, oil, and gas, with the speech delivered during a heatwave affecting much of London and Europe.

Why does it matter?

The rapid expansion of AI infrastructure is bringing its environmental footprint under increasing scrutiny. As data centres consume growing amounts of electricity and water, policymakers are beginning to ask whether AI companies should be subject to the same transparency expectations applied to other carbon-intensive industries. Standardised reporting could provide governments, investors and local communities with a clearer understanding of AI’s environmental impact.

The proposal also highlights the growing intersection between AI governance and climate policy. As countries seek to expand AI capabilities while meeting emissions targets, the availability of clean energy, sustainable infrastructure and transparent environmental reporting is likely to become an increasingly important part of discussions on responsible AI development.

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European Commission explores scaling AI in agriculture

The European Commission’s Directorate-General for Agriculture and Rural Development (DG AGRI) and Directorate-General for Communications Networks, Content and Technology (DG CONNECT) jointly organised an online expert workshop on 24 June to explore how to accelerate AI adaption and scale trusted AI solutions across the agriculture sector.

The workshop was organised within the framework of the Commission’s Apply AI Strategy, which aims to accelerate AI adoption in strategic sectors, including agri-food, while strengthening European competitiveness, technological sovereignty and uptake among small and medium-sized enterprises. Participants discussed AI applications already being deployed in farm management, precision agriculture, crop and livestock monitoring, advisory services, agricultural robotics and the simplification of administrative processes.

The workshop focused on three priorities: assessing the current level of AI adoption in EU agriculture, identifying barriers to wider deployment and exploring policy measures that could support greater uptake. An interactive session also examined what is needed to ensure AI solutions in agriculture are developed, tested, and validated in a trustworthy and responsible manner.

The workshop’s findings will inform a stakeholder input note identifying priority AI use cases, barriers to adoption, infrastructure and data requirements, and potential follow-up actions under the Apply AI Strategy and related EU programmes supporting the digital transition of agriculture.

Why does it matter?

The workshop illustrates how the European Commission is moving from promoting AI in principle to addressing the practical conditions needed for large-scale deployment. In agriculture, AI has the potential to improve productivity, reduce resource use and simplify administrative tasks, but broader adoption will depend on access to high-quality data, digital infrastructure, trusted solutions and support for farmers and SMEs.

The initiative also reinforces the EU’s wider strategy of linking AI deployment with competitiveness and technological sovereignty. By connecting the Apply AI Strategy with the Common Agricultural Policy, the Common European Agricultural Data Space and Horizon Europe, the Commission is seeking to build an ecosystem in which AI can be adopted responsibly while supporting the long-term digital transformation of Europe’s agri-food sector.

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