Artificial intelligence Archives | Page 11 of 673

UN warns of AI’s growing environmental footprint

As AI continues to reshape economies, industries and daily life, a new report from the United Nations University (UNU) highlights the environmental challenges associated with its rapid adoption. While discussions often focus on greenhouse gas emissions linked to AI systems, researchers argue that the technology’s impact on water resources, land use and electronic waste deserves equal attention.

According to the report, data centres supporting AI applications could consume up to 945 terawatt-hours of electricity annually by 2030. Beyond electricity demand, AI-related water consumption could reach levels equivalent to the annual household needs of 1.3 billion people, while the land footprint associated with AI infrastructure may exceed 14,500 square kilometres.

Researchers note that environmental pressures vary significantly depending on the technologies and energy sources used to power AI systems.

The UN report also finds that routine AI use, rather than model training alone, accounts for a significant share of resource consumption. Everyday activities such as generating images, videos and text require substantial computing power, with image generation demanding significantly more energy than basic text-based tasks. Growing adoption may further increase total resource consumption despite improvements in efficiency.

Researchers note that the environmental costs of AI infrastructure are often concentrated in specific regions, while the benefits of AI are distributed more broadly across the global economy. Expanding data centres, rising electricity demand, increasing water consumption and growing volumes of electronic waste could place additional pressure on communities and countries already facing resource constraints.

The report calls for responsible AI development supported by greater transparency, sustainable infrastructure planning, international cooperation and governance measures aimed at keeping technological progress within environmental limits.

Why does it matter?

Debates about AI sustainability often focus on carbon emissions, but the report argues that water consumption, land use and electronic waste are becoming equally important considerations as AI infrastructure expands. These impacts could become increasingly significant as governments and companies invest in larger data centres and more powerful AI systems.

The findings also highlight the need for environmental considerations to be integrated into AI governance and infrastructure planning. As AI adoption accelerates worldwide, policymakers face growing pressure to balance technological innovation with sustainability and resource management goals.

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Canada launches AI for All national strategy to accelerate adoption and digital sovereignty

Canada has launched AI for All, a new national AI strategy aimed at accelerating AI adoption, strengthening digital sovereignty, and positioning the country as a leading AI economy.

Announced by Prime Minister Mark Carney, the strategy combines proposed legislation, investments, and programmes intended to ensure AI is adopted responsibly and benefits businesses, workers, students, and communities across Canada.

The strategy targets an additional C$200 billion in economic growth, 250,000 new AI-related jobs over the next five years, and an increase in AI adoption from just over 12% today to 60% by 2034. The government also plans to provide up to 90,000 AI-related jobs and work placement opportunities for young Canadians.

The strategy is built around three principles: building trust, creating opportunities, and reinforcing Canadian sovereignty. To build trust, the government plans to modernise digital legislation, strengthen protections for personal information, address harms such as deepfakes and surveillance pricing, introduce an online safety regime, and expand the capabilities of the Canadian AI Safety Institute.

To create opportunities, the government will establish a National AI Literacy Initiative, provide access to trusted AI agents for post-secondary students, help small and medium-sized businesses adopt AI, support worker training, and launch an AI Missions Program with a flagship health mission focused on diagnostics, patient care, and system efficiency.

To reinforce sovereignty, Canada plans to build domestic AI foundations, including compute, cloud, connectivity, data, and talent. Measures include a world-leading public AI supercomputer, investments in sovereign compute and cloud infrastructure, better access to growth capital for Canadian AI companies, strategic public procurement, and expanded support for AI talent.

The government said the strategy is intended to ensure more AI value is created in Canada while strengthening privacy, data protection, public services, productivity, and economic security.

Why does it matter?

Canada’s AI for All strategy links AI adoption directly to economic growth, workforce development, public trust, and technological sovereignty. The strategy reflects a wider shift among governments: AI policy is no longer focused only on research excellence, but also on compute infrastructure, cloud sovereignty, data governance, safety institutions, business adoption, public procurement, and skills. Its success will depend on whether Canada can turn ambitious targets into measurable adoption across businesses, public services, and workers.

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OECD launches AI Policy Toolkit for governments

The Organisation for Economic Co-operation and Development (OECD) has launched the AI Policy Toolkit, a practical guide intended to help governments translate AI principles into policy action. Released by the OECD under the Global Partnership on Artificial Intelligence, the first version is designed as a non-prescriptive resource for policymakers working across the AI policy cycle.

Building on the OECD AI Principles, the toolkit is intended to help governments identify policy priorities, compare international approaches and adapt guidance to national circumstances. The platform incorporates AI-powered semantic search to help users identify relevant policy examples and practical approaches drawn from real-world experience.

The OECD developed the AI Policy Toolkit through co-creation with end-users across regions, including targeted interviews and workshops in Southeast Asia, Latin America, and Africa. Policymakers, industry representatives and experts helped shape the platform around implementation challenges, including balancing innovation and regulation, addressing infrastructure gaps and supporting AI adoption in sectors such as agriculture, education and healthcare.

According to the OECD, the development process highlighted two key lessons: AI policy is heavily influenced by national context, institutional capacity and levels of digital maturity, while challenges such as advanced AI risks and linguistic and cultural representation often require international cooperation. Contributors included governments and organisations from Costa Rica, Italy, France, South Korea, Japan, the United Kingdom, the European Union, the French Development Agency, and the Inter-American Development Bank.

The OECD says the toolkit will continue to evolve through feedback, additional policy examples, and expanded coverage of emerging issues, including sector-specific guidance, infrastructure, and regulatory approaches. The OECD said the toolkit’s broader objective is to help governments move from high-level AI principles to practical implementation while managing risks and promoting trustworthy AI.

Why does it matter?

Many governments have adopted AI principles and strategies, but translating these commitments into practical policies remains a challenge. The OECD’s toolkit seeks to bridge that gap by providing policymakers with implementation guidance, real-world examples and policy options tailored to different national contexts.

The initiative also reflects growing recognition that effective AI governance requires both domestic policymaking capacity and international cooperation, particularly as countries confront shared challenges related to advanced AI systems, infrastructure needs and regulatory approaches.

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Brazil’s telecom regulator adopts AI governance framework

Brazil’s telecommunications regulator, Anatel, has approved a new AI governance policy aimed at ensuring the ethical, secure, and transparent use of AI across its regulatory and administrative activities. The framework positions the agency among public institutions in Brazil, proactively addressing the challenges and opportunities of AI-driven transformation.

Developed by the agency’s IA.lab research group, the policy establishes principles including human oversight, transparency, data security and the protection of fundamental rights. It also creates a permanent forum to monitor AI use, assess risks, and support decision-making, ensuring AI complements rather than replaces human judgment in regulation.

A key objective of the policy is to strengthen technological sovereignty by encouraging the development and adoption of AI solutions built in Brazil and, where appropriate, trained on local data and optimised for Portuguese-language use cases.

The policy also lays the groundwork for a broader national AI strategy within the agency, designed to expand responsible innovation across telecommunications regulation and public service delivery.

Anatel said the governance model is intended to balance innovation and accountability, enabling the use of AI to improve efficiency while maintaining security, trust and regulatory integrity.

Why does it matter?

The policy places Anatel among a growing number of public-sector regulators establishing formal governance frameworks for AI. As regulatory agencies increasingly adopt AI tools, questions around transparency, accountability, human oversight and risk management are becoming central to public trust.

The framework also reflects broader efforts by governments to promote technological sovereignty by supporting domestic AI capabilities while ensuring that innovation aligns with legal, ethical and public-interest objectives.

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UK Ofcom sets out AI safety and innovation strategy

Ofcom has outlined its approach to enabling safe and secure AI adoption across the UK communications sectors it regulates and within its own work.

The regulator said its approach is technology-neutral and outcomes-based, aligning AI oversight with its wider mission of making communications work for everyone while supporting innovation and growth.

Ofcom’s report uses case studies to show how AI is already shaping regulatory work and the sectors it oversees. Planned and recent initiatives include building a pilot data lake to make spectrum licensing and online safety data more accessible, engaging with innovators to identify regulatory uncertainty, and assessing public trust in AI chatbots.

The regulator is also examining the impact of AI on telecoms customer experience, exploring AI deployment in broadcasting, assessing AI use in cybersecurity for telecommunications networks, and considering how AI could support network management and optimisation.

Alongside innovation support, Ofcom said it is monitoring AI-related risks and emerging harms. Its work includes guidance on technology-led mitigation against deepfakes, research into chatbot-related harms, and action to address risks posed by AI systems to users.

Ofcom said it coordinated with the AI Security Institute and the National Cyber Security Centre to brief stakeholders on the frontier AI cybersecurity implications following Anthropic’s preview of Claude Mythos, which caused concern. It also said it launched a formal investigation into X’s Grok chatbot.

The regulator is also piloting responsible AI use internally, including tools to support policy development, research, consultation processes, tracking of technical standards, and operational efficiency. Ofcom said it will take a safety-first approach and roll out internal AI tools only once it is confident they are safe and secure.

Why does it matter?

Ofcom’s approach shows how AI governance is becoming operational inside sector regulators, not only debated at the government level. The strategy links innovation support with risk monitoring across online safety, telecoms, broadcasting, cybersecurity, spectrum management, and consumer protection. It also shows regulators experimenting with AI in their own workflows while trying to maintain safety, accountability, and public trust.

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EU and India deepen digital cooperation through Tech Business Forum

The European Union and India have concluded the first EU-India Tech Business Forum in New Delhi, advancing digital and trade cooperation under the framework of the EU-India Trade and Technology Council (TTC). The forum brought together businesses, policymakers, researchers, think tanks, and civil society to strengthen private-sector collaboration and identify opportunities for joint innovation.

The forum was organised by the EU Delegation to I n dia and Bhutan and India’s Ministry of Electronics and Information Technology, with support from industry organisations including the Federation of European Business in India and the National Association of Software and Service Companies (NASSCOM).

More than 100 European and Indian technology companies participated in discussions covering semiconductors, AI, cybersecurity, data governance and digital public infrastructure.

Participants explored opportunities to strengthen interoperability, advance cooperation on technical standards and improve market access for companies operating in both markets. The forum also aimed to operationalise wider EU-India cooperation, including the recently concluded Free Trade Agreement and the Administrative Arrangement on Advanced Electronic Signatures and Seals signed under the Trade and Technology Council in January 2026.

Speaking at the forum, EU Ambassador to India Hervé Delphin said:

‘In today’s fragmented world, working with trusted partners like India is essential to diversify supply chains and reduce over-reliance on certain sources and geographies.‘

He said Europe brings strengths in advanced technology, innovation, and regulation, while India offers scale, talent, and technological applications.

The forum’s outcomes are expected to shape the next steps in EU-India digital and trade cooperation. The Trade and Technology Council remains the primary framework for EU-India cooperation on strategic technologies, digital governance and connectivity, covering areas such as digital public infrastructure, semiconductors, data governance and emerging technologies.

Why does it matter?

The EU and India are seeking to deepen cooperation on strategic technologies at a time when governments are prioritising supply chain resilience, digital sovereignty and secure technology partnerships. Closer collaboration in areas such as AI, semiconductors and cybersecurity could help both sides reduce dependencies and strengthen innovation ecosystems.

The forum also demonstrates the growing role of technology diplomacy in trade relations, with policymakers and businesses working together to address standards, interoperability and market access challenges that increasingly shape the global digital economy.

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Mayo Clinic and Microsoft partner to build frontier AI model for healthcare

Mayo Clinic and Microsoft have announced a strategic collaboration to develop and deploy a frontier AI model designed specifically for healthcare.

The initiative combines Mayo Clinic’s clinical expertise, de-identified health data, and longitudinal medical insights with Microsoft’s AI, cloud, engineering, and superintelligence capabilities.

The model is intended to support a broad range of clinical reasoning and healthcare use cases by synthesising diverse clinical information. Mayo Clinic said it could support earlier diagnoses, more personalised treatment decisions, and improved patient outcomes.

Unlike general-purpose AI systems, the model is being developed for healthcare environments that require deep clinical context, longitudinal understanding, rigorous governance, and real-world validation.

Mayo Clinic will own the model, which it said reflects its commitment to patient trust, clinical rigour, safety, and responsible stewardship of clinical data and AI.

The system will initially be deployed within Mayo Clinic’s clinical environment, where physicians and researchers can test, refine, and improve it through real-world use.

Microsoft plans to make the model available through Azure Foundry APIs, enabling healthcare organisations worldwide to access advanced medical AI capabilities designed to support patients, clinicians, and consumers.

Why does it matter?

The partnership shows how major health institutions and technology companies are moving towards domain-specific frontier AI models rather than relying only on general-purpose systems. Healthcare AI requires specialised data governance, clinical validation, longitudinal patient understanding, and robust safeguards, as errors can directly affect diagnosis, treatment, and patient trust. Mayo Clinic’s ownership of the model is also important because it signals an attempt to keep clinical accountability and data stewardship closer to the healthcare institution.

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European Commission unveils roadmap for AI and digitalisation in energy

The European Commission has published a Strategic Roadmap for Digitalisation and AI in the Energy Sector, outlining how digital technologies could support a more resilient, competitive and secure European energy system.

The roadmap outlines how digital tools and AI could help consumers and businesses reduce energy costs through greater efficiency, smarter energy consumption and improved management of electricity demand. It also highlights the role of digital technologies in supporting the integration of renewable energy into electricity grids.

The Commission has structured the roadmap around three main priorities. These priorities include integrating data centres into energy systems in a sustainable manner, accelerating the deployment of digital and AI-enabled technologies such as smart meters and intelligent grid solutions, and establishing a framework for secure cross-border energy data sharing.

The Commission said the plan will also focus on cybersecurity, AI trust, digital skills and international cooperation. As part of the next phase, the Commission plans to support industry cooperation initiatives and launch the AI.grids community, which will focus on developing AI models for energy network management across the EU.

Why does it matter?

The energy sector is becoming increasingly dependent on digital technologies to manage growing electricity demand, integrate renewable energy sources and maintain grid stability. AI and advanced data analytics could help improve efficiency, reduce costs and support more flexible energy systems.

At the same time, greater digitalisation introduces new challenges related to cybersecurity, data governance and infrastructure resilience. The roadmap signals the EU’s intention to ensure that digital transformation in the energy sector supports both sustainability goals and long-term energy security.

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ILO calls for stronger EU action on mental health, AI and climate risks at work

The International Labour Organization has called for occupational disease prevention, mental health risks, AI, and climate change to become central elements of the European Union’s future workplace health and safety agenda.

The intervention was delivered during a European Parliament hearing on the EU strategic framework on occupational safety and health after 2027.

The ILO stressed that while Europe has reduced fatal workplace accidents, occupational diseases now account for more than 98% of work-related deaths in the EU. Cancer, respiratory diseases, and circulatory diseases remain the leading causes, underscoring the need for stronger prevention, better labour inspection, and improved recognition of work-related illness.

The organisation also highlighted emerging risks linked to digitalisation and environmental change. AI-driven systems are reshaping working conditions through algorithmic management, surveillance, and automated decision-making, while psychosocial pressures and mental health risks are becoming a growing concern for workers.

Climate change was also identified as a major occupational safety and health challenge, with rising temperatures and extreme weather events increasing risks across European workplaces.

The ILO urged the EU policymakers to integrate these evolving risks into a renewed strategic framework, alongside stronger international cooperation and prevention-based approaches. It said Europe can help shape global workplace safety standards through coordinated regulation, effective prevention, and sustainable working conditions.

Why does it matter?

The ILO’s intervention shows how workplace safety policy is expanding beyond traditional accident prevention. AI systems, algorithmic management, psychosocial risks, occupational disease, and climate-related hazards are becoming part of the same strategic debate. For the EU, the post-2027 framework will be a test of whether workplace regulation can adapt to technology-driven work organisation, demographic pressures, and climate volatility.

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European Central Bank warns banks to strengthen resilience as AI reshapes cyber threats

Europe’s banking sector must strengthen its operational resilience as AI transforms the cyber threat landscape and increases systemic risks, according to the European Central Bank (ECB). Speaking at a financial conference, Executive Board member Frank Elderson warned that technological disruption and geopolitical fragmentation are increasing pressure on financial infrastructure.

The ECB said Europe’s reliance on external providers for technology, energy and financial services creates vulnerabilities that could expose critical functions to operational disruptions. While banks remain financially stable, their ability to maintain critical services during cyberattacks or system failures has become key to long-term competitiveness and stability.

According to the ECB, AI is accelerating cyber risks by lowering barriers to sophisticated attacks, enabling faster identification of vulnerabilities and expanding the range of actors capable of conducting cyber operations. While supervisors have strengthened oversight through measures such as stress testing and the implementation of the Digital Operational Resilience Act (DORA), the ECB warned that cyber and operational risks continue to evolve rapidly.

Authorities are now urging banks to invest more heavily in systems, governance, and third-party risk management to ensure continuity of services under stress. The ECB emphasised that operational resilience should be viewed not only as a technical challenge but as a strategic priority for maintaining trust in financial services and supporting Europe’s wider economic transformation.

Why does it matter?

Financial stability increasingly depends not only on the financial health of banks but also on their ability to maintain critical services during cyber incidents, technology failures and operational disruptions.

As AI enables more sophisticated cyberattacks and financial institutions become more dependent on complex digital infrastructure and third-party providers, regulators are placing greater emphasis on operational resilience as a core component of financial stability, economic competitiveness and public trust.

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