Artificial intelligence Archives | Page 10 of 673

UK project tests how legal data can support AI use in government

The UK Government Digital Service has highlighted data maturity as a key requirement for preparing public sector data for AI use.

The findings come from a project conducted with The National Archives, part of GDS’s wider work to ensure public sector data is managed as a strategic national asset.

During a discovery phase completed in April 2026, the organisations assessed whether legal data, including legislation and case law, could be prepared for AI applications. The work focused on governance, data quality, organisational readiness, and the risks of exposing government data to AI systems, rather than building a specific AI tool.

GDS found that The National Archives’ legal data is already close to AI-ready, thanks to high data quality, strong leadership, relevant skills, and mature governance practices. It said that good data alone is not enough; public sector organisations also need the right people, processes, and culture to use data safely, ethically, and responsibly.

The project also identified the evaluation and validation of AI-generated outputs as a significant future opportunity for the government. GDS said public bodies could add value by developing tools and standards to assess whether AI outputs are trustworthy, rather than replicating services already developed by major technology companies.

The next phase will explore how data maturity can reduce the risks of using AI with public sector data. It will also examine technologies such as the Model Context Protocol, an open-source standard for connecting AI applications to external systems, including databases, tools, and documents.

Why does it matter?

The project shows that AI readiness in government depends on more than deploying new tools. Public bodies need high-quality data, strong governance, clear accountability, and the ability to evaluate AI-generated outputs before relying on them in services that affect citizens and businesses. The work also points to a useful role for government: setting standards for trustworthy AI outputs, rather than simply building public-sector versions of commercial AI products.

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RCC meeting focuses on AI, roaming and regional connectivity

The Regional Commonwealth in the Field of Communications and the CIS Coordination Council for Informatization held a joint meeting in St Petersburg on 5 June, bringing together communications officials, international organisations and industry representatives.

The meeting was chaired by Sherzod Shermatov, Minister of Digital Technologies of Uzbekistan, in his role as Chair of the RCC Board of Heads of Communications Administrations and the CIS Coordination Council.

Participants discussed preparations for the 2026 International Telecommunication Union Plenipotentiary Conference in Doha, the development of non-geostationary orbit communication systems, interstate roaming across RCC and CIS countries, IT parks, start-ups and regional cooperation in communications and information technologies.

AI was also among the key themes. Participants discussed the application of AI and the creation of a regional expert council on AI and digital technologies.

The meeting also addressed the establishment of a Regional Fund for the Development of the RCC Sovereign Digital Space and broader efforts to strengthen digitalisation and technological development across the region.

Representatives from ITU, the Universal Postal Union, the Eurasian Economic Commission, CIS bodies and other international organisations also took part. The next joint meeting is scheduled to September 2026 in Dushanbe, Tajikistan.

Why does it matter?

The meeting shows how regional communications bodies are linking traditional telecom issues, such as roaming, satellite systems and IT parks, with newer digital policy priorities, including AI governance and sovereign digital infrastructure. The proposed regional expert council on AI and digital technologies is the strongest governance angle, while the RCC Sovereign Digital Space fund points to growing regional interest in digital autonomy and infrastructure coordination.

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Microsoft urges stronger biosecurity safeguards as AI transforms biotechnology

Microsoft has argued that rapid advances in AI and biotechnology are creating new biosecurity challenges that require stronger safeguards and closer cooperation between governments, industry, and the scientific community.

The company said AI is accelerating scientific discovery across areas such as healthcare, drug development, and materials science, while also increasing concerns about accidental harm and deliberate misuse of biological technologies.

Microsoft identifies a growing convergence between general-purpose AI models, specialised biological design tools, laboratory automation systems, and agentic AI technologies. The company argues that these capabilities can accelerate legitimate research but also complicate the biosecurity policy landscape.

A central focus of Microsoft’s recommendations is nucleic acid synthesis screening. The company describes synthetic DNA providers as a critical checkpoint in the biotechnology ecosystem because they are often where digital biological designs are translated into physical materials.

Microsoft said current DNA synthesis screening practices remain largely voluntary and unevenly applied across providers. It warned that gaps in screening become more consequential as AI-enabled biological design tools become more powerful.

The company pointed to its Paraphrase Project, which stress-tested existing screening systems against AI-designed biological sequences. Microsoft said the project showed where safeguards could fail and how they could be improved through responsible disclosure, red teaming, and rapid deployment of fixes.

Microsoft also highlighted growing bipartisan attention to biosecurity in the United States, including a 2025 executive order on biological research safety and the proposed Biosecurity Modernization and Innovation Act. The company said stronger screening requirements, conformity assessments, enforcement mechanisms, and public-private collaboration could help reduce risk while sustaining scientific innovation.

Why does it matter?

AI is becoming part of the biotechnology research pipeline, from biological design tools to automated laboratories. Microsoft’s intervention shows that AI safety debates are expanding beyond model behaviour and content safeguards into the physical infrastructure of science, including DNA synthesis providers, laboratory workflows, technical standards, and biosecurity screening. The key policy question is how to preserve scientific openness while preventing AI-enabled misuse of biological capabilities.

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UNICEF warns of AI risks to child online safety

UNICEF Vietnam has warned that rapid advances in AI are creating new risks for child online safety, including AI-generated child sexual abuse material and deepfakes.

The UNICEF Vietnam Representative, Silvia Danailov, issued a warning to mark International Children’s Day and Vietnam’s Month of Action for Children, which is held under the theme ‘Happy, safe and confident children in the digital world.’

Danailov said digital technologies can help children learn, connect, and develop future skills, but also create new forms of harm. She warned that generative AI can now be used to create highly realistic sexual images or videos of children without their knowledge or consent.

UNICEF, ECPAT, and INTERPOL research across 11 countries found that at least 1.2 million children reported that their images had been manipulated into sexually explicit deepfakes in the past year. Danailov said such harms can have lasting effects, even when images are digitally created, because children experience fear, shame, and loss of trust.

Nearly nine in ten children aged 12 to 17 in Vietnam are online, with many spending five to seven hours a day on the internet. Danailov said AI-driven risks add a new layer to existing challenges, such as cyberbullying and online exploitation, while also exposing inequalities between children who are supported online and those who are not.

Vietnam has strengthened its legal and policy framework, including a new government decree effective from 16 May 2026 that reinforces children’s right to privacy by prohibiting the disclosure of a child’s personal information without the child’s consent, when aged seven or older, and with the consent of their parents or caregivers.

The country has also approved the National Programme on Child Online Protection and Support for Development for 2026–2030, aimed at protecting children and empowering them as confident digital citizens through stronger legal frameworks, improved systems, education, and coordinated action.

UNICEF called for laws and enforcement to keep pace with technology, stronger child protection systems, safer platform design by technology companies, and better support for schools and families. Danailov also stressed that children must be heard and involved in creating safer digital environments.

Why does it matter?

The warning shows how generative AI is changing the landscape of child online safety. Children can now be harmed even without direct interaction with an offender, including through manipulated images and deepfake abuse. That makes child protection harder for families, schools, platforms, and regulators, and increases the need for safety-by-design, stronger reporting systems, legal safeguards, and trusted support channels for children.

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EU launches digital energy system initiatives for data centres and AI grids

The EU policymakers and high-level industry representatives have launched two flagship initiatives to prepare the EU energy system for a more digitalised future.

The first initiative brings together data centre operators, the energy sector, and public authorities to support the sustainable integration of data centres into the EU energy system. In the presence of Energy Commissioner Dan Jørgensen, 14 European associations signed a Declaration of Intent, while six companies signed a Declaration of Support indicating readiness to begin implementation.

The event also marked the launch of the AI.grids project, which will develop the EU sovereign AI models for energy grids. The project brings together 48 partners, including grid operators and research institutes, to improve grid management and planning.

Both initiatives coincide with the Commission’s Tech Sovereignty Package, published on the same day. The package includes a Strategic Roadmap for Digitalisation and AI in the energy sector, aimed at preparing the future energy system and supporting the deployment of AI solutions across the energy value chain.

Why does it matter?

The initiatives show how AI infrastructure and energy policy are becoming increasingly interconnected. Data centres are expanding rapidly as demand for AI computing grows, while electricity grids need more advanced digital tools to manage decentralised generation, demand, and resilience. By linking data centre sustainability with the EU sovereign AI models for grid management, the Commission is treating digitalisation as both a pressure on the energy system and a tool for managing it.

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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.

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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.

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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.

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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.

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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.

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