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UNESCO summit advances AI ethics roadmap for Latin America and Caribbean

Countries in Latin America and the Caribbean have adopted a Ministerial Declaration and a regional roadmap on AI ethics for 2026–2027.

The documents were adopted at the Third Ministerial Summit and High-Level Authorities Meeting on the Ethics of Artificial Intelligence in Latin America and the Caribbean, held in the Dominican Republic.

The summit was organised by UNESCO, the Government of the Dominican Republic, the Development Bank of Latin America and the Caribbean and other partners, with support from the European Union.

Participants reaffirmed their commitment to implementing UNESCO’s Recommendation on the Ethics of Artificial Intelligence, adopted by UNESCO member states as a global normative framework for AI governance.

The roadmap sets priorities for technical cooperation, the exchange of regulatory experience and stronger institutional capacities for ethical and responsible AI policy.

It builds on earlier regional declarations adopted in Santiago in 2023 and Montevideo in 2024, moving the regional process from shared principles towards implementation.

The roadmap frames AI as a cross-cutting public policy issue, calling for participation from sectors including education, health, the economy, culture, the environment, justice, planning, budgeting and subnational government.

Participating states also identified capacity development as a regional priority, including digital literacy and training for public officials, educators, judicial practitioners, journalists, researchers, businesses and citizens.

The process will continue through five regional working groups, expanded technical exchanges and closer coordination with other international AI governance initiatives.

Why does it matter?

The roadmap gives Latin America and the Caribbean a more structured way to coordinate AI policy across countries, rather than developing national approaches in isolation. Its value will depend on whether regional working groups can turn broad ethical commitments into practical tools, stronger public institutions and shared regulatory capacity. The focus on education, environment, public administration and subnational government also shows that AI governance is being treated as a whole-of-society policy issue, not only a technology-sector concern.

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University of Wisconsin launches College of Computing & AI

The University of Wisconsin-Madison has launched its College of Computing & Artificial Intelligence (CAI), the institution’s first new college in more than four decades.

The new college brings together the departments of Computer Sciences, Statistics and the Information School, building on the School of Computer, Data & Information Sciences established in 2019.

The college will focus on computing and AI education and research while promoting collaboration across fields including health, engineering, business, the social sciences, the arts and the humanities.

The university also plans to launch new academic programmes, recruit 50 faculty members over the coming years and expand partnerships with industry and government to strenthen research, education and innovation.

Why does it matter?

The creation of a dedicated College of Computing & Artificial Intelligence reflects the growing importance universities are placing on AI as a cross-disciplinary field rather than a specialised area within computer science. By bringing together expertise from multiple disciplines, the university aims to prepare students and researchers to address the technical, social and ethical challenges of AI.

The investment also highlights intensifying competition among higher education institutions to attract talent, research funding and industry partnerships in AI. Expanding faculty, academic programmes and collaboration with government and business positions the university to play a larger role in developing the next generation of AI research and workforce skills.

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India marks 11 years of Digital India initiative

India has marked the 11th anniversary of the Digital India initiative, with Prime Minister Narendra Modi highlighting its role in transforming governance, public service delivery and access to digital services.

In a statement issued by the Prime Minister’s Office, Modi said the Digital India initiative had made governance more transparent, efficient and citizen-centric. He highlighted digital payments, Direct Benefit Transfers and the expansion of digital public infrastructure as key examples of technology improving public service delivery.

The government also linked the Digital India initiative to broader innovation across the country, including in villages and Tier-2 and Tier-3 cities. Modi said entrepreneurs, startups and innovators were developing technology-based solutions for sectors including education, healthcare, agriculture, commerce and public services.

The statement also highlighted India’s ambitions in emerging technologies. Modi said advances in AI, semiconductors and quantum computing would create new opportunities for economic growth, while reaffirming the government’s commitment to using technology to empower citizens and support sustainable development.

Why does it matter?

The anniversary highlights how Digital India has evolved from a digital government programme into a broader strategy for economic development and technological innovation. By linking digital public infrastructure with AI, semiconductors and quantum computing, the government is positioning digital transformation as a foundation for India’s long-term competitiveness.

The initiative also illustrates the growing role of digital public infrastructure in national development. India’s experience with digital payments, identity systems and public services is increasingly influencing international discussions on digital governance and technology-enabled public service delivery.

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UAE and US deepen AI partnership under Pax Silica framework

The United Arab Emirates is expanding its AI cooperation with the United States, describing the partnership as a long-term strategic framework centred on investment, trusted technology and joint innovation across multiple sectors.

The UAE is investing across the US AI ecosystem, including semiconductors, AI applications, energy and digital infrastructure. Officials said the partnership reflects years of institutional cooperation, reinforced through continued policy alignment, economic collaboration and high-level engagement.

At the second Pax Silica Summit in Washington, UAE representatives joined international partners in advancing the Joint Statement on AI Opportunity, with 35 countries reaffirming their commitment to innovation-driven policies, private-sector research and resilient technology supply chains. The UAE joined the Pax Silica initiative in January 2026 as part of a broader US$1.4 trillion economic and technology framework.

The partnership also includes major infrastructure and investment projects, including advanced US semiconductor exports to the UAE, a joint AI campus in Abu Dhabi and expanding data centre capacity. Officials said cooperation will continue to deepen through long-term investment, research and technology integration.

Why does it matter?

The partnership illustrates how AI is increasingly shaping strategic relationships between countries, extending beyond research cooperation into semiconductors, computing infrastructure, investment and supply chains. Governments are treating AI capabilities as a foundation of long-term economic competitiveness and technological influence.

It also reflects the growing importance of trusted international technology partnerships. As countries seek secure access to advanced chips, data centres and AI infrastructure, collaborations such as the UAE-US partnership are becoming an important part of broader industrial, economic and geopolitical strategies.

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UN scientific panel publishes first global AI assessment ahead of Geneva governance dialogue

The United Nations’ Independent International Scientific Panel on Artificial Intelligence has published its first preliminary report, providing an evidence-based assessment of AI’s opportunities, risks, and societal impacts ahead of next week’s inaugural Global Dialogue on AI Governance in Geneva. Rather than prescribing specific policies, the report aims to inform international discussions by providing an independent scientific foundation for AI governance decision-making.

Established by the UN General Assembly in August 2025 following commitments made in the Global Digital Compact, the panel brings together 40 independent experts from academia, civil society, the private sector, and the technical community. It is the first permanent UN scientific body dedicated exclusively to assessing the development and societal implications of AI. The report will serve as a key input to the Global Dialogue on AI Governance, which takes place on 6–7 July alongside the World Summit on the Information Society (WSIS) Forum and the AI for Good Global Summit in Geneva.

The preliminary report examines AI through four broad dimensions:

Scientific and technological developments;
Opportunities for sustainable development;
Emerging risks;
Approaches to international governance.

Instead of advocating a particular regulatory model, the panel seeks to establish a shared evidence base that can support future policymaking and international cooperation on AI.

Rather than focusing solely on risks, the report examines AI’s growing role across sectors, including healthcare, education, agriculture, scientific research, and public administration. It describes AI as a general-purpose technology with the potential to accelerate innovation, improve productivity, and expand access to knowledge and public services. At the same time, the panel notes that these benefits remain unevenly distributed across countries and regions, with significant disparities in access to computing infrastructure, technical expertise, and digital resources.

The report estimates that more than one billion people now use AI-powered services each week, while frontier AI capabilities remain concentrated among a relatively small number of companies and countries. According to the panel, this concentration extends beyond AI models themselves to include computing infrastructure, specialised hardware, large-scale datasets, and technical talent, raising broader questions about equitable access to AI and the distribution of its benefits.

The panel also highlights the challenges facing developing countries, warning that many risk becoming primarily consumers rather than producers of AI technologies if investment in local infrastructure, research ecosystems, digital skills, and governance capacity does not keep pace with global developments. It identifies multilingual AI, locally relevant datasets, and stronger scientific capabilities as important factors in ensuring that AI systems better reflect diverse societies and languages rather than reinforcing existing global disparities.

Alongside these opportunities, the report identifies a range of emerging risks associated with increasingly capable AI systems. These include the use of AI for cyberattacks, fraud, disinformation, election interference, and other malicious activities, as well as broader concerns related to market concentration, transparency, and the growing dependence of many countries on a limited number of AI providers. The panel also notes that many governments currently lack the technical capacity to evaluate the most advanced frontier AI models independently.

Beyond security-related concerns, the report identifies environmental sustainability as an increasingly important governance issue. It notes that the rapid expansion of AI requires increasing amounts of computing power, electricity, water, and specialised hardware, and argues that future AI development should balance technological progress with efficient resource use and broader sustainable development objectives.

Speaking at the report’s launch, UN Secretary-General António Guterres said that the pace of AI development requires stronger international cooperation grounded in scientific evidence and inclusive dialogue.

Panel co-chair Maria Ressa described the publication as an independent scientific assessment designed to inform, rather than replace, intergovernmental decision-making. The report itself states that ‘effective AI governance requires international cooperation,’ while recognising that governance approaches will continue to reflect different national circumstances and policy priorities.

The publication marks the first major output of the Independent International Scientific Panel on AI since its establishment under the Global Digital Compact. Future reports are expected to provide regular scientific assessments of AI capabilities, impacts, and governance challenges as the technology continues to evolve.

Why does it matter?

As governments, international organisations, researchers, and industry representatives gather in Geneva next week for the inaugural Global Dialogue on AI Governance, the preliminary report is expected to provide an important reference point for discussions on the future of AI. By combining scientific evidence with a broad assessment of opportunities, risks, and governance considerations, it seeks to support a more informed international conversation on how AI can contribute to sustainable development, human rights, and shared global prosperity.

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Claude Science launches AI workbench for researchers

Claude Science has been launched as an AI workbench designed to streamline scientific research by bringing data analysis, coding and research tools into a single integrated environment. The platform is designed to help researchers analyse data, run multi-step workflows, and generate publication-ready outputs with full transparency.

The platform consolidates research tools such as databases, coding environments and analysis software, enabling scientists to work across disciplines without switching between applications. Outputs are fully auditable, with embedded code, workflow histories and documentation to support validation and reproducibility.

Claude Science also uses a multi-agent architecture comprising specialist agents and a reviewer agent that verifies calculations and citations. It can be deployed on local infrastructure or high-performance computing systems, allowing institutions to scale AI-assisted research while keeping sensitive data within their own environments.

Why does it matter?

Claude Science reflects a broader evolution of AI from a standalone assistant to an integrated research platform. By combining specialised AI agents, computational tools and transparent workflows in a single environment, it aims to simplify scientific research while improving reproducibility and collaboration.

The platform also raises broader questions about the future of AI in science. As researchers increasingly rely on AI to support data analysis and experimentation, ensuring transparency, validation and institutional control over sensitive research data will be essential to maintaining scientific integrity and trust.

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Canada and Germany strengthen semiconductor supply chains

Canada and Germany have signed a joint declaration of intent to strengthen semiconductor supply chains and deepen industrial cooperation, reinforcing collaboration in a technology that underpins AI, advanced computing and the digital economy.

The declaration was signed on the sidelines of the International Energy Agency’s (IEA) Annual Global Conference on Energy Efficiency by Carlos Leitão, Parliamentary Secretary to Canada’s Minister of Industry, and Stefan Rouenhoff, Parliamentary State Secretary at Germany’s Federal Ministry for Economic Affairs and Energy.

Canada said resilient and diversified semiconductor supply chains are becoming increasingly important as global demand grows for AI, advanced computing and connected technologies.

The declaration establishes a framework for policy dialogue and cooperation on investment, industrial development, technology and research. It also aims to support start-ups, scale-ups and small and medium-sized enterprises while building on both countries’ semiconductor expertise to strengthen competitiveness.

Canada described semiconductors as foundational technologies for the digital economy, highlighting their role in enabling AI and other emerging technologies.

The declaration also supports Canada’s National Artificial Intelligence Strategy: AI for All, particularly its focus on infrastructure, international partnerships and long-term competitiveness. It builds on a series of bilateral initiatives launched since late 2025, including the Canada-Germany Digital Alliance, a joint AI declaration, the Sovereign Technology Alliance, and cooperation on automotive manufacturing, batteries and critical minerals.

A separate February 2026 declaration also expanded bilateral industrial cooperation in auto and battery manufacturing and critical minerals. Officials from both countries said stronger semiconductor supply chains can support innovation, economic resilience and long-term prosperity.

The partnership adds semiconductor supply chains to a wider Canada-Germany agenda focused on trusted advanced technologies, economic security and the next generation of AI-enabled digital infrastructure.

Why does it matter?

Semiconductors have become strategic assets that underpin AI, advanced computing, telecommunications and many other digital technologies. By strengthening cooperation on chip supply chains, Canada and Germany aim to reduce supply chain vulnerabilities, encourage investment and support long-term technological competitiveness.

The agreement also reflects a broader trend of trusted technology partnerships among like-minded countries. Rather than focusing solely on trade, governments are increasingly coordinating industrial policy, research and supply chains to strengthen economic security and reduce dependence on concentrated sources of critical technologies.

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OpenAI launches GeneBench-Pro for AI biology research

OpenAI has introduced GeneBench-Pro, a research benchmark designed to assess whether AI agents can perform the complex, judgment-intensive analysis required in real-world computational biology.

Unlike conventional benchmarks that focus on factual recall or routine workflows, GeneBench-Pro is designed to measure what OpenAI calls ‘research taste‘, the sequence of judgement calls involved in scientific analysis, from interpreting ambiguous data and revising assumptions to deciding whether findings are robust enough to inform downstream research.

The benchmark comprises 129 problems spanning ten domains within computational biology, including statistical genetics, cancer genomics, clinical diagnostics, and pharmacogenomics. Each problem presents an AI agent with a realistic and deliberately messy dataset, brief experimental context, and a target to estimate.

To answer correctly, the model must explore the data iteratively, select an appropriate analytical approach, and supply a final answer without exploiting shortcuts or matching arbitrary author preferences. To prevent common benchmark shortcuts, every problem uses synthetically generated data whose underlying causal structure is fully known, allowing performance to be measured against a controlled ground truth.

OpenAI said its flagship model, GPT-5.6 Sol, achieved a pass rate of 28.7% at the highest reasoning setting, increasing to 31.5% in Pro mode. By comparison, the strongest model available when the original GeneBench was introduced scored below 5%.

External reviewers estimated that completing a typical GeneBench-Pro task would require 20 to 40 hours of expert work and cost thousands of dollars, whereas AI inference currently costs only a few dollars per run. OpenAI argues this suggests substantial economic potential even before models achieve expert-level performance.

OpenAI acknowledged that frontier models still solve fewer than one-third of the benchmark problems, often making partial progress but failing to complete the full chain of scientific reasoning expected from experienced researchers. To encourage independent evaluation, the company is open-sourcing ten representative tasks on Hugging Face and providing a 50-question subset to Artificial Analysis for third-party benchmarking.

Why does it matter?

GeneBench-Pro reflects a broader shift in AI evaluation from testing factual knowledge and coding ability to assessing whether models can support complex scientific reasoning. As computational biology increasingly becomes limited by data interpretation rather than data generation, reliable AI assistance in analytical workflows could accelerate research in areas such as genomics, drug discovery and precision medicine.

The benchmark also highlights the importance of rigorous evaluation methods for frontier AI. By using controlled synthetic datasets with known ground truth, GeneBench-Pro seeks to measure not only whether models reach the correct answer but also how well they make the sequence of judgements required in real-world scientific research.

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Anthropic redeploys Claude Fable 5

Anthropic will restore global access to Claude Fable 5 after the US government lifts export controls on the model.

The company said the controls were applied on 12 June to Claude Fable 5 and Claude Mythos 5, requiring access restrictions for foreign nationals inside and outside the United States. Anthropic suspended access to both models for all users because it said it had no reliable way to verify nationality in real time.

Anthropic said the controls were lifted on 30 June. Fable 5 will become available globally from 1 July on the Claude Platform, Claude.ai, Claude Code and Claude Cowork, with access on AWS, Google Cloud and Microsoft Foundry to be restored as quickly as possible.

Access to Mythos 5 has been restored only for a set of US organisations following government approval. Anthropic said Fable 5 and Mythos 5 share the same underlying model, but Fable 5 has stronger safeguards for general use, while Mythos 5 has fewer safeguards and is limited to trusted partners working on defensive cybersecurity.

The export control directive followed a report by Amazon researchers describing a method for bypassing Fable 5 safeguards. Anthropic said the reported behaviour involved identifying software vulnerabilities and, in one case, producing code showing how a vulnerability could be exploited.

The company said its review found that the technique did not expose unique Mythos-level cyber capabilities. It has trained an improved safety classifier to block the behaviour described in the report, and said blocked requests will be redirected to Claude Opus 4.8.

Anthropic also called for a shared industry framework to assess the severity of AI jailbreaks. It said it is working with Amazon, Microsoft, Google and other Glasswing partners on criteria including capability gain, breadth of capability gain, ease of weaponisation and discoverability.

The company said it is expanding cooperation with the US government on frontier AI security, including pre-release evaluation, faster information sharing and joint research on safeguards.

Why does it matter?

The case shows how frontier AI releases are becoming part of national security and export-control policy, especially when models have advanced cybersecurity capabilities. Anthropic’s response also highlights a broader governance gap: governments and companies still lack a shared standard for judging when a jailbreak is minor, serious or urgent enough to justify intervention. The outcome could influence how advanced AI models are tested, released and restricted across borders.

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EU launches three new digital skills academies

The European Commission has launched three new Digital Skills Academies focused on AI, quantum technologies and virtual worlds.

The academies were announced during Digital Skills EU Days, an annual event bringing together digital skills projects, national coalitions, policymakers, industry representatives and education organisations from across the EU.

Funded under the Digital Europe Programme, the academies are intended to establish specialised training in critical technology areas and help the EU meet its Digital Decade targets.

The Commission said Europe’s competitiveness and leadership depend on digital talent, linking the initiative to the Union of Skills, the AI Continent Action Plan, the Apply AI Strategy and the Digital Decade Policy Programme.

The new academies add to wider Digital Europe Programme investments in skilling, upskilling and reskilling. The programme has invested more than €294 million in the EU digital skills initiatives covering areas such as data, cloud, cybersecurity and AI.

During the event, the Commission also presented the 2026 European Digital Skills Awards, recognising projects focused on AI literacy, cybersecurity education, digital inclusion, research data management and women’s participation in ICT.

Why does it matter?

The new academies show that the EU is treating digital skills as part of its strategic technology agenda, alongside regulation, infrastructure and industrial policy. AI, quantum technologies and virtual worlds all require specialised expertise, and shortages in these areas could slow deployment across businesses, research institutions and public services. The initiative also supports the EU’s broader goal of strengthening technological competitiveness and reducing dependence on external talent and capabilities.

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