UNESCO has renewed calls for stronger international cooperation to ensure AI supports rather than undermines climate goals, as environmental pressures linked to AI continue to grow.
The message was delivered at the Adopt AI Summit in Paris, where sustainability and ethics featured prominently in discussions on future AI development.
At a Grand Palais panel, policymakers, industry leaders, and UN officials examined AI’s growing energy, water, and computing demands. The discussion focused on balancing AI’s climate applications with the need to reduce its environmental footprint.
Public sector representatives highlighted policy tools such as funding priorities and procurement rules to encourage more resource-efficient AI.
UNESCO officials stressed that energy-efficient AI must remain accessible to lower-income regions, mainly for water management and climate resilience.
Industry voices highlighted practical steps to improve AI efficiency while supporting internal sustainability goals. Participants agreed that coordinated action among governments, businesses, international organisations, and academia is essential for meaningful environmental impact.
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Generative AI has rapidly entered classrooms worldwide, with students using chatbots for assignments and teachers adopting AI tools for lesson planning. Adoption has been rapid, driven by easy access, intuitive design, and minimal technical barriers.
A new OECD Digital Education Outlook 2026 highlights both opportunities and risks linked to this shift. AI can support learning when aligned with clear goals, but replacing productive struggle may weaken deep understanding and student focus.
Research cited in the report suggests that general-purpose AI tools may improve the quality of written work without boosting exam performance. Education-specific AI grounded in learning science appears more effective as a collaborative partner or research assistant.
Early trials also indicate that GenAI-powered tutoring tools can enhance teacher capacity and improve student outcomes, particularly in mathematics. Policymakers are urged to prioritise pedagogically sound AI that is rigorously evaluated to strengthen learning.
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Lawmakers in the EU are moving closer to forcing technology companies to pay news publishers for the use of journalistic material in model training, according to a draft copyright report circulating in the European Parliament.
The text forms part of a broader effort to update copyright enforcement as automated content systems expand across media and information markets.
Compromise amendments also widen the scope beyond payment obligations, bringing AI-generated deepfakes and synthetic manipulation into sharper focus.
MEPs argue that existing legal tools fail to offer sufficient protection for publishers, journalists and citizens when automated systems reproduce or distort original reporting.
The report reflects growing concern that platform-driven content extraction undermines the sustainability of professional journalism. Lawmakers are increasingly framing compensation mechanisms as a corrective measure rather than as voluntary licensing or opaque commercial arrangements.
If adopted, the position of the Parliament would add further regulatory pressure on large technology firms already facing tighter scrutiny under the Digital Markets Act and related digital legislation, reinforcing Europe’s push to assert control over data use, content value and democratic safeguards.
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Several major AI companies appear slow to meet EU transparency obligations, raising concerns over compliance with the AI Act.
Under the regulation, developers of large foundation models must disclose information about training data sources, allowing creators to assess whether copyrighted material has been used.
Such disclosures are intended to offer a minimal baseline of transparency, covering the use of public datasets, licensed material and scraped websites.
While open-source providers such as Hugging Face have already published detailed templates, leading commercial developers have so far provided only broad descriptions of data usage instead of specific sources.
Formal enforcement of the rules will not begin until later in the year, extending a grace period for companies that released models after August 2025.
The European Commission has indicated willingness to impose fines if necessary, although it continues to assess whether newer models fall under immediate obligations.
The issue is likely to become politically sensitive, as stricter enforcement could affect US-based technology firms and intensify transatlantic tensions over digital regulation.
Transparency under the AI Act may therefore test both regulatory resolve and international relations as implementation moves closer.
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A new report by Anthropic suggests fears that AI will replace jobs remain overstated, with current use showing AI supporting workers rather than eliminating roles.
Analysis of millions of anonymised conversations with the Claude assistant indicates technology is mainly used to assist with specific tasks rather than full job automation.
The research shows AI affects occupations unevenly, reshaping work depending on role and skill level. Higher-skilled tasks, particularly in software development, dominate use, while some roles automate simpler activities rather than core responsibilities.
Productivity gains remain limited when tasks grow more complex, as reliability declines and human correction becomes necessary.
Geographic differences also shape adoption. Wealthier countries tend to use AI more frequently for work and personal activities, while lower-income economies rely more heavily on AI for education. Such patterns reflect different stages of adoption instead of a uniform global transformation.
Anthropic argues that understanding how AI is used matters as much as measuring adoption rates. The report suggests future economic impact will depend on experimentation, regulation and the balance between automation and collaboration, rather than widespread job displacement.
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New US tariffs on advanced AI chips are drawing scrutiny over their impact on global supply chains, with South Korea monitoring potential effects on its semiconductor industry.
The US administration has approved a 25 percent tariff on advanced chips that are imported into the US and then re-exported to third countries. The measure is widely seen as aimed at restricting the flow of AI accelerators to China.
The tariff thresholds are expected to cover processors such as Nvidia’s H200 and AMD’s MI325X, which rely on high-bandwidth memory supplied by Samsung Electronics and SK hynix.
Industry officials say most memory exports from South Korea to the US are used in domestic data centres, which are exempt under the proclamation, reducing direct exposure for suppliers.
South Korea’s trade ministry has launched consultations with industry leaders and US counterparts to assess risks and ensure Korean firms receive equal treatment to competitors in Taiwan, Japan and the EU.
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Scientists in China developed an error-aware probabilistic update (EaPU) to improve neural network training on memristor hardware. The method tackles accuracy and stability limits in analog computing.
Training inefficiency caused by noisy weight updates has slowed progress beyond inference tasks. EaPU applies probabilistic, threshold-based updates that preserve learning and sharply reduce write operations.
Experiments and simulations show major gains in energy efficiency, accuracy and device lifespan across vision models. Results suggest broader potential for sustainable AI training using emerging memory technologies.
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Rising AI-driven electricity demand is straining power grids and renewing focus on nuclear energy as a stable, low-carbon solution. Data centres powering AI systems already consume electricity at the scale of small cities, and demand is accelerating rapidly.
Global electricity consumption could rise by more than 10,000 terawatt-hours by 2035, largely driven by AI workloads. In advanced economies, data centres are expected to drive over a fifth of electricity-demand growth by 2030, outpacing many traditional industries.
Nuclear energy is increasingly positioned as a reliable backbone for this expansion, offering continuous power, high energy density, and grid stability.
Governments, technology firms, and nuclear operators are advancing new reactor projects, while long-term power agreements between tech companies and nuclear plants are becoming more common.
Alongside large reactors, interest is growing in small modular reactors designed for faster deployment near data centres. Supporters say these systems could ease grid bottlenecks and deliver dedicated power for AI, strengthening nuclear energy’s role in the digital economy.
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US regulators have closed a loophole that allowed Elon Musk’s AI company, xAI, to operate gas-burning turbines at its Memphis data centre without full air pollution permits. The move follows concerns over emissions and local health impacts.
The US Environmental Protection Agency clarified that mobile gas turbines cannot be classified as ‘non-road engines’ to avoid Clean Air Act requirements. Companies must now obtain permits if their combined emissions exceed regulatory thresholds.
Local authorities had previously allowed the turbines to operate without public consultation or environmental review. The updated federal rule may slow xAI’s expansion plans in the Memphis area.
The Colossus data centre, opened in 2024, supports training and inference for Grok AI models and other services linked to Musk’s X platform. NVIDIA hardware is used extensively at the site.
Residents and environmental groups have raised concerns about air quality, particularly in nearby communities. Legal advocates say xAI’s future operations will be closely monitored for regulatory compliance.
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The European Commission plans to revise the Cybersecurity Act to expand certification schemes beyond ICT products and services. Future assessments would also cover companies’ overall risk-management posture, including governance and supply-chain practices.
Only one EU-wide scheme, the Common Criteria framework, has been formally adopted since 2019. Cloud, 5G, and digital identity certifications remain stalled due to procedural complexity and limited transparency under the current Cybersecurity Act framework.
The reforms aim to introduce clearer rules and a rolling work programme to support long-term planning. Managed security services, including incident response and penetration testing, would become eligible for EU certification.
ENISA would take on a stronger role as the central technical coordinator across member states. Additional funding and staff would be required to support its expanding mandate under the newer cybersecurity laws.
Stakeholders broadly support harmonisation to reduce administrative burden and regulatory fragmentation. The European Commission says organisational certification would assess cybersecurity maturity alongside technical product compliance.
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