Artificial intelligence Archives | Page 8 of 670

Japan and US deepen AI science collaboration under Genesis Mission

Japan and the United States are expanding cooperation on AI-enabled scientific research, with Japan reported to become the first international partner in the US-led Genesis Mission.

The five-year initiative is expected to mobilise around $1 billion, with funding reportedly split between the two governments. The collaboration will focus on using AI to accelerate research in advanced fields, including quantum technologies, nuclear fusion, biotechnology, and other strategically important areas.

The Genesis Mission is a US Department of Energy initiative designed to use AI, scientific datasets, national laboratories, universities, and industry partners to accelerate discovery science, energy innovation, and national security research.

Japan’s participation builds on earlier cooperation between the US Department of Energy and Japan’s Ministry of Education, Culture, Sports, Science and Technology on AI-enabled scientific discovery, high-performance computing, and quantum technologies.

Joint projects are expected to involve US national laboratories and Japanese research institutions, including RIKEN and the University of Tokyo. The collaboration is also expected to support AI and robotics-powered autonomous laboratories capable of conducting experiments with limited human intervention.

The partnership reflects a broader shift towards AI for Science, where AI systems are used to generate hypotheses, analyse complex data, automate research workflows, and shorten development timelines in frontier research fields.

Why does it matter?

The collaboration shows how AI for Science is becoming part of strategic technology competition and international research diplomacy. By linking AI, high-performance computing, quantum technologies, fusion, and biotechnology, Japan and the United States are trying to accelerate scientific discovery while strengthening technological leadership in fields with economic, security, and industrial importance.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our chatbot!

Australia’s regulator warns of growing AI-powered sextortion threat

Australia’s eSafety Commissioner has launched a public awareness campaign warning that criminals are increasingly using AI and other digital tools in sextortion scams.

The initiative, titled ‘If sextortionists were honest’, uses generative AI to expose deceptive tactics used by online criminals targeting victims through dating apps and social media platforms.

According to eSafety, more than 3,300 reports of sexual extortion were received through its image-based abuse scheme in 2025. Eighty-six percent of reports came from males of all ages, while 42% of all sextortion reports involved males aged 18 to 24.

eSafety Commissioner Julie Inman Grant said offenders are already weaponising face-swapping and voice-cloning technologies, while using generative AI to create fake but convincing online characters and improve scam scripts that previously contained warning signs such as poor grammar or inconsistent messaging.

Reports made to eSafety show that first contact frequently occurs on platforms such as Tinder, Instagram, and Grindr, before conversations are moved to WhatsApp, Telegram, or other messaging apps. Offenders may then search victims’ social media accounts to identify family members and friends they can threaten to contact.

The regulator said overseas offenders often try to appear local and legitimate, including by spoofing Australian phone numbers, using intimate images taken from other victims, or using bank accounts belonging to previous victims to receive and move payments.

eSafety said the safest response is to stop contact, report the account to the platform, block the offender, preserve evidence where possible, and seek support rather than paying. The regulator also called on platforms to take proactive Safety by Design steps, including better language analysis, classifier-based detection, accessible reporting and blocking tools, swift removal pathways for image-based abuse, and cross-platform signal sharing.

Why does it matter?

The campaign shows how generative AI is making online coercion and scams harder to detect. Sextortion is no longer only a problem of fake accounts and blackmail messages: offenders can now use AI-generated personas, improved scripts, voice cloning, and deepfake-style techniques to build trust and pressure victims more effectively. That raises the importance of platform-level detection, user reporting tools, digital literacy, and victim support.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Dutch study explores how to scale AI across government organisations

Dutch research organisation TNO has conducted an exploratory study examining how AI applications can be scaled across government organisations in the Netherlands. The study was commissioned by the Ministry of the Interior and Kingdom Relations because AI offers opportunities for public sector services and operations.

The study supports the Netherlands’ Digitalisation Strategy, which calls for a more proactive government role in the development and adoption of AI. One option under consideration is an AI scaling facility that would support the reuse and further development of successful AI applications, helping deploy them more quickly and across a wider range of organisations.

According to the study, scaling AI is not a linear or one-size-fits-all process. Depending on their goals, context, and partnerships, organisations may follow different approaches, including scaling within one organisation, replicating solutions across similar organisations, adapting them to new sectors or tailoring broad solutions to local needs.

TNO identifies seven approaches to AI scaling: scaling in, scaling out, scaling beyond, scaling together, scaling down, scaling up and scaling deep. The strategies cover internal adoption, cross-organisational reuse, sectoral adaptation, collaborative development, localisation, policy and standards work, and cultural or behavioural change inside organisations.

A related ‘Conversation starter’ has also been developed to help organisations assess AI scaling initiatives at the outset. The recommendations include treating scaling as a strategic decision, selecting an approach aligned with intended outcomes, addressing governance and organisational culture, reusing existing solutions where possible, investing in AI literacy and documentation, clarifying ownership and funding arrangements, and regularly assessing whether scaling remains desirable, feasible and legally appropriate.

Why does it matter?

Many governments are moving beyond AI experimentation and focusing on how successful projects can be deployed at scale. However, expanding AI use across public institutions often involves organisational, governance and cultural challenges that extend beyond technology itself.

The Dutch study highlights the need for structured approaches to AI adoption, emphasising reuse, collaboration and institutional capacity. Its findings could help governments accelerate AI deployment while maintaining accountability, effectiveness and compliance with legal requirements.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!

UK regulator launches AI-assisted review of gambling advertising

The UK Gambling Commission has announced a new compliance initiative targeting gambling advertising, following an enforcement notice issued by the Committee of Advertising Practice (CAP). The measure aims to prevent gambling advertisements from having a strong appeal to people under 18.

From 11 June, CAP will conduct a monitoring exercise using its AI-powered Active Ad Monitoring System in collaboration with social media platforms. The review will assess whether gambling advertisements comply with rules intended to protect children and other vulnerable audiences.

Under the enforcement notice, businesses found to be in breach of the rules may be required to amend or remove advertisements without delay. Failure to comply could lead to sanctions, including referrals to hosting platforms or the Gambling Commission.

The Gambling Commission said operators must ensure that all advertising, including content published on social media, remains socially responsible and complies with CAP and Broadcast Committee of Advertising Practice (BCAP) requirements.

Why does it matter?

Regulators are increasingly using AI tools to monitor online advertising at scale, particularly in areas where consumer protection concerns are significant. Gambling advertising remains a sensitive issue because of its potential impact on children and other vulnerable groups.

The initiative signals a more proactive approach to enforcement, combining automated monitoring with platform cooperation to identify problematic content more quickly and strengthen compliance with advertising standards.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Cambridge researchers test AI-designed vaccine in human trial

Researchers at the University of Cambridge have developed an experimental vaccine using AI, marking what they describe as the first human test of a vaccine component designed entirely by AI. The experimental approach aims to provide broad protection against entire families of viruses, including coronaviruses with pandemic potential.

The AI system analysed genetic data from multiple coronaviruses and designed a ‘super-antigen’ intended to help the immune system recognise and respond to a broad range of viral variants, including those that may emerge through future mutations. An initial trial involving 39 volunteers focused primarily on safety, while a larger follow-up study is planned to evaluate immune responses and effectiveness in greater detail.

Researchers say the approach could help vaccine development keep pace with rapidly evolving threats, including influenza, emerging COVID-19 variants and viruses with the potential to spread from animals to humans. The team is also exploring similar AI-designed vaccines for influenza, bird flu, and Ebola-like viral haemorrhagic fevers, where current protection options remain limited.

Researchers describe the findings as an early but significant step towards using AI to accelerate vaccine design and strengthen preparedness for future disease outbreaks. The study highlights growing expectations that AI may become a central tool in global pandemic prevention strategies.

Why does it matter?

Traditional vaccine development often focuses on responding to specific pathogens after they emerge. By contrast, AI-assisted design could help researchers develop vaccines that provide protection against entire families of viruses before outbreaks occur.

If successful, the approach could shorten development timelines, improve preparedness for future pandemics and support efforts to address rapidly evolving infectious diseases. The research also highlights the growing role of AI in scientific discovery and biomedical innovation.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our chatbot!

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.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

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.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

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.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!

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.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our chatbot!

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.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our chatbot!