Artificial intelligence Archives | Page 25 of 674

Australia introduces a national framework for digital health standards

Australia has introduced a National Framework for Digital Health Standards aimed at improving interoperability and consistency across healthcare systems. The framework is intended to support integration of digital tools and health records across healthcare settings.

According to the initiative, the framework addresses fragmentation caused by independently developed digital health standards. The framework provides guidance intended to support coordination between government agencies, healthcare providers, and industry participants.

Speaking at the Digital Health Festival, Digital Health Agency Chief Officer Peter O’Halloran referred to increasing use of digital health services and shared medical records. Officials said growing levels of data sharing are increasing demand for interoperable and reliable digital infrastructure.

The framework also supports use of internationally recognised clinical terminology standards and related training initiatives.

Standards including SNOMED CT, GS1, and FHIR were identified as important components of interoperability and future digital health applications.

Why does it matter?

Unified digital health standards are critical for ensuring that patient information can be shared accurately and securely across different healthcare providers, reducing fragmentation that can lead to delays or clinical errors. Standardisation also strengthens the foundation for advanced technologies such as AI, enabling safer, more scalable innovation in healthcare delivery.

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UK Pensions Regulator publishes AI governance plan for pension schemes

The UK Pensions Regulator (TPR) has published an AI plan outlining expectations for governance and oversight of AI use in pension schemes.

TPR said AI may support pension administration, decision-making, and member engagement, while also creating operational and cybersecurity risks. According to the regulator, accountability remains with trustees and scheme managers even when AI systems or third-party providers are involved.

TPR Chief Executive Nausicaa Delfas said:

‘AI has the potential to transform pensions for the better: improving how schemes are run, how members are supported, and how the system as a whole delivers value.’

She added: ‘But trust is the most valuable asset in our system, and that trust depends on the safe and responsible adoption of AI in members’ interests.’

The plan recommends governance measures, including system testing, risk monitoring, fraud prevention, data management, and compliance with data protection requirements.

TPR’s plan sets out four areas of focus:

Ensuring schemes are well run and governed
Strengthening data foundations
Supporting responsible innovation
Using AI to become a more effective regulator.

TPR said it will continue coordinating with the Financial Conduct Authority on regulatory alignment across the pensions sector.

The regulator also said it has used AI-supported processes to identify pension scam websites and support enforcement actions. Further guidance and industry engagement activities are planned later this year.

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EU lawmakers challenge confidentiality rules on data centre emissions data

A group of 35 Members of the European Parliament has called on the European Commission to review confidentiality rules affecting public access to environmental data from data centres. The request focused on the disclosure of information related to emissions, energy use, and water consumption.

According to reporting by Investigate Europe, the disputed wording was linked to proposals submitted during consultations by Microsoft and DIGITALEUROPE. The clause was later incorporated into the EU Energy Efficiency Directive and limits disclosure of certain information related to individual data centres.

Critics argue that the measure may reduce transparency regarding the environmental impact of expanding digital infrastructure. Some lawmakers and advocacy groups have also raised questions about compatibility with transparency principles under the Aarhus Convention. Reports said critics believe the rules reduce scrutiny of the environmental impact linked to expanding AI and cloud infrastructure.

The lawmakers called on the European Commission to reconsider the provision and publish more detailed environmental reporting data. The issue has contributed to broader discussions in the EU regarding environmental accountability and oversight of digital infrastructure.

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UK government launches cyber resilience measures amid AI-related risks

The UK Department for Science, Innovation and Technology has warned that cyber threats are becoming more frequent and complex, with AI contributing to faster and more scalable attacks. Digital Minister Baroness Lloyd of Effra said cyber resilience is increasingly important for national security and economic stability.

According to the government’s Cyber Security Breaches Survey, 43% of businesses reported experiencing a cyber breach or attack during the past year. The minister said AI tools are making some cyber capabilities more accessible by automating tasks such as vulnerability detection and reconnaissance.

The government also encouraged technology providers to adopt a ‘secure by design’ approach and referred to existing cybersecurity guidance frameworks.

The Department additionally announced a £90 million cyber resilience fund intended to support businesses, including SMEs and NHS suppliers. The government said a broader National Cyber Action Plan is expected later this summer.

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United Nations to hold first Global Dialogue on AI Governance in Geneva

The United Nations will hold the inaugural Global Dialogue on AI Governance in Geneva on 6 and 7 July 2026, bringing together governments and stakeholders to discuss international cooperation on AI.

Established by the United Nations General Assembly, the dialogue is intended as a multistakeholder platform for discussions on international AI governance cooperation.

The event will take place at the Palexpo International Exhibition and Congress Centre, alongside the AI for Good Global Summit and the annual World Summit on the Information Society meetings in Geneva.

The invitation letter was issued by the co-chairs of the Global Dialogue on AI Governance, Egriselda López, Permanent Representative of El Salvador to the United Nations, and Rein Tammsaar, Permanent Representative of Estonia to the United Nations.

The programme will include high-level governmental plenary segments, multistakeholder exchanges, thematic discussions, side events, and the presentation of the report of the multidisciplinary Independent International Scientific Panel on Artificial Intelligence.

The discussions will be organised around four clusters:

AI opportunities and implications
Bridging AI divides through capacity-building, access, and digital foundations
Safe, secure, and trustworthy AI
And human rights, transparency, accountability, and human oversight.

According to the organisers, the dialogue aims to support international cooperation on AI governance and address issues related to digital inclusion and sustainable development. Registration is open until 25 June 2026.

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New Stanford scaling method could make AI training cheaper

Researchers at Stanford University have introduced a new approach to scaling laws that could significantly reduce the computational cost of predicting how large language models will perform as they grow.

Scaling laws are used to estimate how smaller models will behave before developers commit to expensive large-scale training runs. These predictions are central to modern AI development, where training advanced models can require enormous computing resources and financial investment.

A research team led by Sanmi Koyejo and Sang Truong developed a framework called Item Response Scaling Laws, or IRSL, which draws on measurement science and educational testing methods. The approach adapts techniques similar to those used in standardised exams to evaluate model capabilities with far fewer test queries.

According to Stanford HAI, IRSL can reduce computational demand by more than 99% while maintaining or improving predictive accuracy. Instead of running every model through large evaluation sets, the method uses carefully selected questions to estimate capability more efficiently.

Researchers argue that the approach could make AI development more accessible, particularly for academic institutions and smaller research teams that lack the computing budgets of major technology companies. It could also help large commercial developers reduce the cost of experimentation before training larger models.

The method remains a research advance rather than a direct reduction in the full cost of training frontier models. However, by making performance prediction cheaper and more statistically rigorous, it could change how developers plan and evaluate future AI systems.

Why does it matter?

AI development is increasingly shaped by access to computing power, which gives the largest technology companies a major advantage. If methods such as IRSL can make model evaluation and scaling predictions far cheaper, they could lower barriers for researchers, universities and smaller developers, while making AI experimentation faster and less resource-intensive.

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Switzerland advances National Cyberstrategy implementation

Switzerland has reported progress in implementing its National Cyberstrategy, with more than 90 projects underway and new measures addressing the role of AI in cybersecurity.

The Federal Council was informed of the 2025 implementation report. The implementation report was prepared by the National Cyberstrategy Steering Committee together with the National Cyber Security Centre. The report tracks work across five objectives:

Empowering the public
Securing digital services and critical infrastructure
Managing cyberattacks
Combating cybercrime
Strengthening international cooperation

The report identifies AI as an important area influencing both cybersecurity risks and defensive capabilities. The report describes measures related to AI-assisted cyber threats, AI-supported cyberdefence, research projects, and public awareness activities.

The report also refers to regulatory safeguards linked to Switzerland’s ratification of the Council of Europe Convention on AI. The report frames those steps as part of a broader response to the growing importance of AI in cybersecurity.

According to the report, the National Cyber Security Centre has received 222 reports since mandatory reporting requirements for cyberattacks on critical infrastructure entered into force in April 2025. Authorities say the reports improve national cyber situational awareness and support coordinated responses to threats.

The report also highlights developments involving sector-specific cybersecurity centres, information-sharing initiatives, and vulnerability management programmes. Switzerland also continued its federal bug bounty programme and other vulnerability management initiatives.

Capacity-building programmes include the Cyber-Defence Campus Fellowship, the Cyber Startup Challenge, and the national S-U-P-E-R.ch awareness campaign. The report also notes information-sharing work through Cyber-CASE, Cyber-STRAT, and NEDIK to support faster handling of digital crimes.

International activities included participation in cyber diplomacy and capacity-building initiatives linked to Geneva Cyber Week and UN and OSCE processes.

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Singapore and Google expand partnership on frontier AI deployment

Google and Singapore’s Ministry of Digital Development and Information have announced an expanded National AI Partnership to accelerate the deployment of frontier AI across the economy and public sector.

The partnership builds on earlier collaboration between Google and Singapore’s digital authorities and aims to support healthcare innovation, scientific research, workforce development, enterprise transformation and AI governance. The Ministry said the initiative supports Singapore’s National AI Strategy by deploying AI at scale for economic growth and public good.

A major focus is on healthcare and life sciences. Google DeepMind is exploring collaboration with Singapore’s public health clusters on AI co-clinician research, including systems that could support doctors and patients during care journeys under the clinical authority of physicians.

Google DeepMind will also work with the National Research Foundation to train local researchers on agentic AI tools for science, while Google and A*STAR will collaborate on AI-enabled tools for scientific research and analysis in materials and life sciences. The partnership also includes work on a Gemma-powered running assistant for blind and low-vision athletes, in collaboration with SG Enable.

Education and workforce development are another pillar. Google has enabled advanced AI features in Google Workspace for Education for educators from primary schools to junior colleges, while the Ministry of Education and Google will expand collaboration on teacher training, upskilling and AI-supported teaching and learning.

The partnership also covers enterprise transformation and AI governance. Google Cloud’s Forward Deployed Engineers will support Singapore-based companies working on agentic enterprise transformation, while Singapore agencies and Google are testing how ‘computer use’ AI agents behave in real-world settings through an AI Agents Sandbox.

Singapore and Google will also collaborate on AI safety, including the development of multimodal and multilingual safety benchmarks with IMDA and MLCommons. The work is intended to support responsible AI deployment that reflects local languages, cultures and governance needs.

Why does it matter?

The partnership shows how frontier AI is moving from experimentation into national deployment strategies. Singapore is using public-private collaboration to test AI in healthcare, research, education, enterprise workflows and governance, while also building safeguards around agentic systems and multilingual safety. The initiative could strengthen Singapore’s position as a regional AI hub, yet its impact will depend on how effectively these tools are governed in sensitive areas such as healthcare, education and public-sector services.

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NASA develops AI system to track harmful algal blooms using satellite data

NASA researchers have developed an AI system designed to combine satellite datasets to improve monitoring of harmful algal blooms.

The system uses self-supervised machine learning to analyse patterns across five satellite missions and instruments, helping researchers identify blooms in regions including western Florida and Southern California. According to researchers, the approach could support environmental monitoring and earlier identification of marine health risks.

Harmful algal blooms can affect ecosystems, wildlife, coastal environments, and public health. In parts of Florida, blooms caused by Karenia brevis have disrupted coastal communities for decades, while toxic blooms along the US West Coast have harmed dolphins, sea lions, and other marine species.

NASA researchers said the system combines information from multiple satellite observation technologies. Instruments such as the PACE satellite and the TROPOMI monitoring instrument help identify algae characteristics, including pigment, fluorescence, and biological activity across ocean surfaces.

The researchers said the self-supervised AI model identifies relationships between datasets without relying heavily on manually labelled data. The system was trained using satellite observations collected during 2018 and 2019 before being tested on later bloom events.

Michelle Gierach of NASA’s Jet Propulsion Laboratory said the system could help environmental agencies identify areas for water sampling earlier during bloom development. Researchers said combining satellite observations with field data may improve coordination between scientific and public health teams.

The project team said the system is being expanded using additional coastal and freshwater datasets.

Why does it matter?

NASA’s development highlights growing use of AI and satellite intelligence for environmental monitoring and climate-related risk management. Harmful algal blooms are becoming an increasing concern for coastal economies, fisheries, tourism, biodiversity, and public health systems worldwide.

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Australia’s regulator targets AI-nudify platform over child safety and deepfake risks

Australia’s eSafety Commissioner has begun enforcement action against another AI-powered ‘nudify’ service accused of failing to protect children from exposure to sexually explicit deepfake images.

The regulator issued a formal Direction to Comply to one of the most visited nudify services in Australia, giving the provider 14 days to implement stronger protections preventing children from accessing the platform. eSafety said the service allows users to upload images of real people and generate sexually explicit deepfake content on demand.

The regulator warned that such technologies can facilitate non-consensual exploitation, cyberbullying, sexual extortion, image-based sexual abuse, misogynistic harassment and exploitation of minors. The service had attracted nearly 40,000 Australian visits per month as of March 2026, following a sharp increase in traffic over the previous six months.

The enforcement action was taken under Australia’s Age-Restricted Material Codes, which came into force in March 2026. The codes are designed to prevent children from accessing or being exposed to age-restricted material, including pornography, high-impact violence, self-harm, suicide or disordered eating content.

eSafety said the Argentina-based provider failed to respond to earlier engagement after the codes took effect and had not committed to improving protections for children. The regulator chose not to name the service to avoid inadvertently promoting it.

If the service does not meet the requirements within the 14-day timeframe, eSafety may pursue further action, including civil penalties of up to AU$49.5 million and delisting notices to search engine providers that help facilitate access to the site.

The action follows earlier enforcement in late 2025 that led three widely used nudify services, which had reportedly been used to generate child sexual exploitation material in schools, to withdraw from Australia. Those services have since relaunched under new ownership with additional safety measures, including mandatory age assurance.

Why does it matter?

The case shows how online safety regulators are beginning to apply age-assurance and child protection rules directly to generative AI services. Nudify platforms are treated as high-risk because they can enable non-consensual sexualised deepfakes, image-based abuse and exploitation involving minors at scale. Australia’s enforcement approach also signals that regulators may target foreign-based AI services when they are accessible to local users and fail to implement safeguards.

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