Artificial intelligence Archives | Page 25 of 711

UNICEF warns millions of children rely on AI for advice and learning

Millions of children worldwide are already using AI for learning, problem-solving and personal guidance, according to UNICEF, which warns that safeguards are not keeping pace with adoption. Data collected across 10 countries suggests that at least 20 million children have used AI tools, with adoption rates significantly higher than among adults.

UNICEF estimates that around 13 million children use AI to support schoolwork, while approximately two million turn to it for advice on personal concerns. The organisation warns that AI is becoming embedded in children’s lives faster than safeguards and oversight mechanisms are being developed.

Young users also reported concerns about misinformation, scams and AI-generated deepfakes. UNICEF is calling on governments and technology companies to strengthen regulation, improve digital literacy and ensure AI systems are designed with children’s rights and safety in mind.

Why does it matter?

The findings suggest that AI is already becoming part of children’s everyday lives, influencing how they learn, seek information and even look for personal support. As adoption accelerates, the gap between technological use and effective safeguards could expose young users to misinformation, manipulation, privacy risks and other online harms.

The report also highlights the growing importance of child-centred AI governance. Decisions made now on regulation, digital literacy and safety-by-design are likely to shape how future generations interact with AI, making children’s rights an increasingly important consideration in global AI policy.

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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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Saudi Arabia leads world in digital connectivity

Saudi Arabia has ranked first globally in the International Telecommunication Union’s 2025 ICT Development Index, which measures progress towards universal and meaningful connectivity.

The index assessed 164 economies using indicators grouped around universal and effective connectivity. Saudi Arabia’s Communications, Space and Technology Commission said the result reflects sustained investment in digital infrastructure and the country’s efforts to strengthen the competitiveness of its technology sector.

CST said advanced telecommunications networks have helped support digital economic growth, attract investment and expand the role of technology across the economy.

According to the regulator, Saudi Arabia’s digital economy reached SAR 495 billion in 2024, accounting for 15% of the national GDP. The country’s ICT market was valued at SAR 180 billion in 2024, according to CST, which described it as the largest and fastest-growing in the MENA region.

The regulator also said mobile subscriptions reached 212% of the population, while average monthly data use per person was more than three times the global average.

The ranking supports Saudi Arabia’s broader digital transformation agenda, which links connectivity investment to economic diversification, emerging technology adoption and the growth of digital services.

Why does it matter?

Connectivity is a foundation for digital transformation. High-performing broadband and mobile networks can support cloud services, AI adoption, digital public services and new business models. Saudi Arabia’s ranking also shows how Gulf states are using telecommunications infrastructure as part of wider economic diversification strategies, with digital markets increasingly tied to competitiveness, investment and technological sovereignty.

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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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World Bank links Poland’s growth outlook to AI adoption

A World Bank Group report says faster AI adoption could significantly raise Poland’s economic output by 2035, but only if firms, workers and institutions can absorb the technology effectively.

The report estimates that Poland’s real GDP could be between 1.3% and 12.1% higher by 2035 than in a scenario where AI adoption remains at current levels. It also suggests that gains of 2% to 3% could appear within the next three years.

The estimates are based on a scenario in which AI adoption expands from 8.4% of Polish firms today to close to 45% by 2035. The report says adoption remains far below Denmark, where 42% of firms use AI.

Poland has several strengths, including 607,000 IT specialists, the largest pool in Central and Eastern Europe, and a high level of government AI readiness. However, only 50.4% of individuals have digital skills, compared with 60.4% across the EU.

The report says 48% of Polish workers are in highly AI-exposed occupations, below the EU average of 53%. It stresses that AI exposure does not automatically imply job losses, but can lead to either displacement or augmentation depending on skills, firm adoption and institutional support.

According to the World Bank, the main challenge is not only access to AI technology but also integrating it into business processes and enabling workers to move into higher-productivity roles.

The report calls for stronger labour-market monitoring, reskilling, support for firm-level AI adoption and policies that help Poland convert AI exposure into productivity gains.

Why does it matter?

The report frames AI adoption as a strategic economic issue, not only a technology upgrade. Poland already has strong digital foundations, including a large IT workforce, but low firm-level AI use could limit productivity gains if adoption does not accelerate. The findings also show that skills, labour mobility and institutional support will determine whether AI exposure leads to better jobs and higher productivity or deeper labour-market frictions.

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Bank of England warns agentic AI threatens financial stability

Bank of England Deputy Governor Sarah Breeden has warned that rapidly advancing AI capabilities, particularly agentic AI systems capable of autonomously carrying out complex sequences of actions, pose growing risks to financial stability.

Breeden noted that open-source AI models may trail the most advanced proprietary models by only four to eight months. She warned that delays in applying security patches can allow attackers to reverse engineer newly disclosed vulnerabilities, echoing the Five Eyes cybersecurity agencies’ assessment that the relevant timeline for AI-enabled cyber threats is measured in months rather than years.

Turning to financial markets, Breeden warned that AI trading agents responding to similar prompts or market signals could reinforce one another during periods of stress, amplifying volatility. She also cautioned that autonomous systems could drift from their original objectives or from broader public policy goals.

She said the Bank of England is working with the Bank for International Settlements Innovation Hub and Germany’s Bundesbank to simulate how different agent designs could contribute to herd behaviour. The work also explores safeguards comparable to market circuit breakers or kill switches that could halt AI-driven trading if faulty models threatened financial stability.

Breeden also highlighted the implications of agentic AI for payments, where autonomous systems could increasingly initiate transactions on behalf of users. She said this raises questions about consent, authorisation, liability for erroneous payments and interoperability as different organisations develop competing technical standards. The Bank is leading a public-private initiative to design the next generation of UK retail payments infrastructure with these emerging use cases in mind.

Breeden concluded by calling for stronger international cooperation, arguing that AI presents cross-border systemic risks comparable to those exposed during the global financial crisis. She suggested that the shared technology dependencies underpinning advanced AI warrant closer international coordination among financial authorities.

Why does it matter?

The speech reflects a growing shift in financial regulation from focusing on AI adoption to preparing for systemic AI risks. By highlighting autonomous decision-making, cyber threats and market dynamics, the Bank of England is signalling that agentic AI presents challenges that extend beyond individual firms to the stability of the financial system as a whole.

It also illustrates how central banks are beginning to rethink financial infrastructure for an AI-enabled economy. Questions around autonomous payments, liability, market safeguards and international coordination suggest that existing regulatory frameworks may need to evolve as AI agents become more capable of acting independently across financial markets and payment systems.

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Ericsson report says global 5G subscriptions pass 3 billion

Global 5G subscriptions passed 3 billion in the first quarter of 2026, according to Ericsson’s latest Mobility Report.

The report says 162 million 5G subscriptions were added during the quarter, bringing the global total to 3.1 billion. Ericsson expects 5G subscriptions to more than double to 6.4 billion by the end of 2031.

5G will also carry around half of global mobile data traffic by the end of 2025. Ericsson projects that 5G networks will account for 85% of mobile data traffic by 2031.

The report highlights the continued deployment of 5G Standalone networks and the growth of commercial network slicing services, which allow operators to offer differentiated connectivity for specific use cases.

Ericsson also points to changing traffic patterns. For many service providers, uplink traffic is already growing faster than downlink traffic, driven by collaboration tools, cloud storage and emerging services that require more data to be sent from devices to networks.

The company says AI-powered devices, augmented reality applications and connected technologies are likely to increase demand for real-time data processing and uplink capacity.

Ericsson said existing 5G networks can support early AI and extended reality services, while 6G is expected to enable larger-scale AI-native applications, with the first commercial services expected around 2030.

Why does it matter?

The report shows that 5G is becoming a core layer of digital infrastructure for AI-enabled services, cloud applications and connected devices. As AI moves from centralised data centres into devices, vehicles, workplaces and industrial systems, mobile networks will need to support higher uplink capacity, lower latency and more differentiated connectivity. Growth in 5G Standalone and network slicing also matters because these technologies give operators more tools to support specialised services, from enterprise automation to future AI and XR applications.

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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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OECD explores AI-powered regulatory inspections

The Organisation for Economic Co-operation and Development (OECD) has published a working paper examining how data-driven regulation and digital technologies, including AI and data analytics, can help authorities carry out more targeted, risk-based and effective inspections.

The paper identifies licensing, permitting and inspections as the three pillars of regulatory delivery, arguing that these mechanisms are most effective when supported by risk-based approaches that minimise unnecessary administrative burdens while improving regulatory outcomes. The core argument is that by adopting risk-based approaches supported by technology, regulators can concentrate their efforts where they are most needed rather than applying uniform enforcement across all actors.

The OECD highlights practical uses for AI and data analytics, including identifying high-risk areas, prioritising inspections, streamlining enforcement and allocating resources more efficiently. The aim is to improve compliance while reducing unnecessary interventions for lower-risk businesses and activities.

The paper also argues that technologies can strengthen public trust in regulation by making inspections more transparent, consistent and evidence-based, improving both the effectiveness and legitimacy of regulatory enforcement.

The project forms part of broader EU efforts to modernise regulatory delivery. Drawing on Italy’s pilot experience, the OECD aims to identify lessons that can be applied across member states and other jurisdictions pursuing evidence-based regulatory reform.

Why does it matter?

The paper illustrates how AI and data analytics could help regulators move away from one-size-fits-all enforcement towards more targeted, risk-based oversight. By focusing inspections where they are most needed, authorities could improve compliance while reducing unnecessary administrative burdens, particularly for smaller businesses.

The report also reflects a wider shift towards evidence-based regulation. As governments seek to modernise public administration without weakening regulatory standards, technologies such as AI are increasingly being viewed as tools for improving both regulatory efficiency and public trust through more transparent and proportionate enforcement.

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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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