Artificial intelligence Archives | Page 8 of 711

Illinois issues AI guidance for schools with AI-assisted drafting disclosed

The Illinois State Board of Education has published comprehensive guidance on the use of AI in schools, while also disclosing that the 409-page document was itself developed with assistance from multiple AI models alongside human review.

The guidance was prepared following legislation adopted in 2025, with contributions from education, technology and public policy experts. Initial drafts drew ChatGPT, Claude and Gemini, while human reviewers edited, verified and refined the final document.

The board detailed how AI was used throughout the drafting process, including producing early text, verifying publicly available resources, creating graphics and improving clarity. It stressed that all AI-generated information was independently reviewed and verified before publication.

The guidance emphasises that AI should support teaching and learning rather than replace human relationships or educational experiences. It also offers practical recommendations for selecting AI tools and promoting responsible, ethical and transparent AI use in schools.

The guidance is intended to help Illinois schools navigate both the opportunities and risks associated with AI adoption in education.

Why does it matter?

The guidance offers schools a practical framework for integrating AI while addressing issues such as academic integrity, privacy, transparency and the reliability of AI-generated content. As more education systems adopt AI, common governance principles may help schools use the technology more consistently and responsibly.

The document is also notable for openly disclosing how AI contributed to its own development. By documenting where AI was used and emphasising independent human verification, the Illinois State Board of Education models a level of transparency that could influence how other public institutions develop AI-assisted policies and guidance.

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South Korea showcases low-power AI networking technology

South Korea’s Ministry of Science and ICT has showcased low-power AI networking technology to an international audience as part of efforts to promote more energy-efficient communications infrastructure.

According to the ministry, the demonstration formed part of broader efforts to showcase domestic advances in AI and communications technologies and strengthen international cooperation.

The ministry released few technical details about the technology, instead presenting it as an example of South Korea’s research and development capabilities in AI networking and next-generation communications infrastructure.

Why does it matter?

Reducing the energy required to run AI infrastructure is becoming increasingly important as AI workloads expand. More efficient networking technologies could help lower operating costs and support wider deployment of AI systems while reducing their environmental impact.

Although the ministry released few technical details, the announcement reflects South Korea’s continued investment in AI and advanced communications technologies as part of its broader strategy to strengthen technological competitiveness and international collaboration.

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EU and India strengthen technology partnership through TTC

The European Union and India have strengthened their strategic partnership at the third meeting of the EU-India Trade and Technology Council (TTC) in Brussels, agreeing to deepen cooperation on advanced technologies, trade and resilient supply chains.

Both sides reaffirmed the TTC as their main platform for cooperation on technology, economic security and innovation, while agreeing to upgrade the framework by the end of 2026 under the Joint EU-India Comprehensive Strategic Agenda.

The meeting produced several concrete initiatives.

The EU and India agreed to begin formal negotiations on India’s association with Horizon Europe, establish the first EU-India Innovation Hub focused on electric vehicle charging technologies, and launch a startup partnership supporting deep tech and clean technology companies. They also expanded cooperation on semiconductors, AI, quantum technologies, high-performance computing, 6G and resilient supply chains covering clean energy technologies, pharmaceuticals and agri-food.

On digital technologies, the partners agreed to strengthen cooperation on AI innovation, including healthcare applications, and collaborate on high-performance computing for climate research, natural hazards and bioinformatics. They also committed to advancing interoperability between digital trust services, including digital wallets, building on their earlier agreement on electronic signatures and seals.

The meeting also reaffirmed the strategic importance of the broader EU-India relationship, including ongoing negotiations on a Free Trade Agreement, investment protection and geographical indications.

Ministers instructed TTC working groups to prioritise implementation ahead of the next ministerial meeting.

Why does it matter?

The EU and India are increasingly treating technology as a strategic pillar of their relationship alongside trade and investment. Expanding cooperation on AI, semiconductors, research and digital infrastructure reflects shared interests in strengthening technological competitiveness and reducing vulnerabilities in critical supply chains.

The agreement also illustrates how trade partnerships are evolving into broader technology partnerships. By linking research, innovation, standards and digital trust, the TTC provides a framework that could deepen long-term cooperation while supporting both sides’ economic security and strategic autonomy.

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UNESCO highlights Learning Cities on World Youth Skills Day

UNESCO has highlighted how cities across its Global Network of Learning Cities are helping young people develop the skills needed for employment, active citizenship and sustainable development to mark World Youth Skills Day.

Through lifelong learning ecosystems, local governments, schools, training centres, employers and community organisations are working together to equip young people with practical, digital, entrepreneurial and leadership skills that respond to changing labour markets and wider societal needs.

The initiative highlights examples from Learning Cities around the world.

In Dakar, Senegal, programmes focus on digital entrepreneurship and employability, while Quezon City in the Philippines offers vocational education and technical certification to improve employment opportunities. Nairobi, Kenya, supports young entrepreneurs through business training, and Bouaké, Côte d’Ivoire, demonstrates how community engagement can strengthen sustainable development.

UNESCO also emphasises that youth skills extend beyond employment. Learning Cities promote leadership, civic participation and community engagement, with examples from Colombia and Ireland illustrating how lifelong learning helps young people become active contributors to their communities.

UNESCO also highlights how lifelong learning can support sustainability and cultural preservation. Initiatives linking young people with local heritage, environmental conservation and sustainable development demonstrate how education can strengthen both community resilience and future opportunities.

Why does it matter?

UNESCO’s initiative reflects a growing recognition that preparing young people for the future requires more than technical or digital skills alone. Lifelong learning is increasingly viewed as essential for supporting employment, civic participation, adaptability and resilience in societies shaped by rapid technological change.

The examples from Learning Cities also show how local governments can play a central role in skills development by bringing together education providers, employers and communities. As AI and digital transformation reshape labour markets, place-based lifelong learning policies may become an increasingly important part of workforce and development strategies.

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Canada invests CAD 13.9 million in Quebec AI projects

The Government of Canada has announced nearly CAD 13.9 million (approximately €8.8 million) in funding for 63 AI projects across Quebec under the Regional Artificial Intelligence Initiative (RAII), aiming to accelerate AI adoption among small and medium-sized enterprises (SMEs).

The funding will support projects focused on both developing AI technologies and integrating AI into existing business operations. The government said the initiative will help SMEs improve productivity, develop innovative solutions and strengthen regional economic growth.

According to the government, the programme is expected to support more than 1,700 jobs across Quebec while helping businesses innovate more quickly, improve operational efficiency and seize new commercial opportunities. The announcement was made by Minister of Artificial Intelligence and Digital Innovation Evan Solomon on behalf of Industry Minister Mélanie Joly.

The investment forms part of Canada’s broader ‘AI for All’ strategy, launched in June 2026, which aims to expand access to AI, promote responsible adoption, strengthen domestic innovation and reinforce Canada’s digital sovereignty.

The Regional Artificial Intelligence Initiative will continue operating in Quebec until March 2031. Canadian officials said the programme is intended to strengthen regional innovation ecosystems, expand AI capabilities among businesses and position Quebec as a leading centre for AI talent and technological development.

According to the government, combining responsible AI adoption with targeted regional investment will strengthen competitiveness while ensuring the benefits of AI are shared more broadly across businesses and communities.

Why does it matter?

The initiative reflects Canada’s growing focus on regional AI development rather than concentrating investment solely in major technology hubs. Supporting AI adoption among SMEs could help spread productivity gains more widely across the economy while strengthening local innovation ecosystems.

The programme also illustrates how industrial policy is becoming an important component of national AI strategies. By combining public funding, regional development and responsible AI governance, Canada is seeking to strengthen long-term competitiveness while reinforcing domestic technological capacity.

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AI is reshaping physics but raising new questions

AI is becoming an increasingly important tool in physics, helping researchers analyse large datasets, accelerate simulations and identify patterns that may be difficult to detect through conventional methods.

A Physics World feature examines how machine learning is already embedded in particle physics, including work at CERN’s Large Hadron Collider, where researchers have used AI techniques in Higgs boson analyses and searches for new physics.

Newer approaches are also being used to detect unexpected anomalies in collider data, potentially helping physicists look beyond predictions based on existing theories.

The growing use of AI has renewed concern about the so-called black-box problem, in which researchers cannot fully explain how a system reaches its conclusions.

Physicists interviewed in the article argue that reproducibility, verification and rigorous review remain central to trust, even when AI models are not fully interpretable.

Applications now extend beyond particle physics into materials science, where autonomous systems and robotic laboratories can design, test and refine new materials.

Such systems could increasingly help decide which experiments to perform, speeding up discovery while shifting scientists towards more supervisory and interpretive roles.

Researchers caution, however, that AI should remain a tool for scientific inquiry rather than a substitute for reasoning, curiosity and critical judgement.

Why does it matter?

AI is changing how scientific knowledge is produced. In physics, it can help researchers process data at scales humans cannot manage alone, improve simulations and suggest new experimental directions. That could accelerate discoveries with wider technological impact, from advanced materials to energy systems and medical technologies. Greater reliance on AI also raises governance questions inside science itself. If results depend on systems that are difficult to interpret, scientific communities need strong methods for reproducibility, validation, peer review and accountability. The issue is not only whether AI can find patterns, but whether scientists can verify, explain, and responsibly build knowledge from them.

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Companies face new questions over AI control and governance

Enterprise AI adoption is moving beyond questions of which model to use towards deeper concerns about infrastructure, governance and ownership.

A Forbes Technology Council article argues that companies entering production with AI need to ask whether systems can operate securely inside their own environments and who controls the intelligence those systems generate over time.

It frames enterprise AI as requiring a new trust layer across the stack.

At the infrastructure level, businesses need visibility into how compute is accessed and governed. At the model level, they need control over data, operational knowledge and business value. At the application level, agents and workflows need clear permissions, access controls and safeguards.

Reasoning models and autonomous agents are also changing the economics of AI deployment. More advanced systems require continuous inference, more tokens and persistent access to business context, making compute capacity, latency and cost central to scaling AI beyond pilots.

The article warns that enterprises risk building long-term value outside their own systems if operational knowledge is generated and stored on external platforms without sufficient control.

It argues that the next phase of enterprise AI will depend less on access to individual models and more on secure, governed systems for owning and reusing operational intelligence.

Why does it matter?

The article captures a broader shift in enterprise AI: competitive advantage may come less from using the same general-purpose models as everyone else and more from how organisations govern the data, workflows and operational knowledge created around those models. That matters for digital sovereignty, vendor lock-in, security and long-term business value. As AI agents become embedded in daily operations, companies will need clearer rules on permissions, auditability, infrastructure dependence and ownership of AI-generated knowledge.

Meta employees sue over alleged AI-assisted layoff decisions

A group of 26 Meta employees has sued the company, alleging that AI-assisted systems used in layoff decisions disproportionately affected workers who had taken medical, parental, or family leave.

The lawsuit was filed in federal court in Oakland, California, and relates to Meta’s May announcement that it would cut about 8,000 jobs, or roughly 10% of its workforce.

According to the complaint, Meta used internal AI systems, activity-monitoring data, token-usage dashboards and algorithmically assisted performance rankings to help select workers for layoffs.

The plaintiffs argue that those metrics could not be fairly accumulated by employees on protected leave or by workers whose output was affected by disability-related accommodations.

All 26 plaintiffs had taken protected leave and had requested or received disability-related accommodations. They have been notified of their layoffs but remain employed, with separations expected to begin on 22 July.

The complaint alleges violations of US labour and civil rights laws, including the Family and Medical Leave Act, the Americans with Disabilities Act, the Pregnancy Discrimination Act and the Pregnant Workers Fairness Act.

Meta denied the allegations, saying the claims lack merit and that people, not AI, made workforce decisions.

The case adds to broader scrutiny of algorithmic systems in employment decisions, especially where performance metrics may have a disparate impact on workers who exercise protected rights.

Why does it matter?

The lawsuit puts algorithmic management directly into the employment-discrimination debate. If AI-assisted performance metrics do not account for protected leave, disability accommodations or caregiving responsibilities, they can appear neutral while producing unequal outcomes. The case could therefore become an important test of how existing labour and civil rights laws apply when companies use AI systems, productivity data and automated rankings in workforce decisions.

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Australia unveils AI framework for data centres, copyright and infrastructure

The Australian government has announced plans for a national AI framework centred on new Australian AI Standards, enforceable rules for large AI data centres and stronger protections for creative works.

The framework aims to support AI investment while addressing its impact on energy infrastructure, water resources, local communities, national sovereignty and intellectual property.

Under the proposed standards, large AI data centres would be legally required to underwrite their additional power supply and pay the full cost of connecting to the electricity network. The government said this would prevent AI infrastructure expansion from increasing household energy bills.

Operators would also be required to reduce electricity consumption when necessary to support grid stability and make their facilities as water-efficient as possible.

The federal government plans to work with states and territories on locating large data centres in suitable areas, with local communities given opportunities to contribute to planning decisions.

An Office of AI has been established within the Department of the Prime Minister and Cabinet to oversee the implementation of the Australian AI Standards. The framework will be considered by the National Cabinet in August, with legislation planned for early 2027.

According to the government, the standards will create a consistent regulatory framework for large AI data centres and training infrastructure. It described the legislation as the first government framework of its kind globally.

The framework is also intended to simplify approvals and provide a clearer process for checking compliance with energy, water, safety and other requirements. The government argues that greater regulatory certainty could support investment while ensuring AI infrastructure contributes to Australia’s wider economic and strategic interests.

The framework also addresses copyright. The government said Australian writers, artists and journalists should retain control over their work and that AI companies should not train models on Australian creative content without the creators’ consent.

Further government-wide AI consumer safety priorities are expected to be announced in the coming weeks. These measures will build on the establishment of Australia’s AI Safety Institute.

Prime Minister Anthony Albanese said the framework was intended to ensure Australia actively shapes AI development while protecting national interests, employment and investment.

Industry, Innovation and Science Minister Tim Ayres linked the Australian AI Standards to the government’s wider industrial strategy, arguing that AI investment should strengthen Australia’s resilience, security and economy.

Assistant Minister for Science, Technology and the Digital Economy Andrew Charlton said the framework would create an enforceable social licence for AI and support safer, more inclusive and environmentally sustainable growth.

Why does it matter?

Australia is linking AI governance directly to the physical infrastructure needed to support AI, including electricity, water, land use and data centres, while also addressing copyright and national sovereignty. This represents a broader approach to AI regulation than frameworks focused solely on model safety or transparency.

If adopted, the Australian AI Standards could influence how other countries balance AI investment with infrastructure planning, environmental sustainability and protection of creative industries. The proposal reflects a growing international trend towards integrating AI governance with industrial, energy and digital policy.

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South Korea to launch free national AI service

South Korea’s Ministry of Science and ICT has announced plans to launch the ‘AI for Everyone’ project this year, providing a homegrown AI service that anyone in the country can use free of charge without usage limits.

The ministry will select participating companies through an open call for proposals. A beta version is scheduled for late September, followed by the launch of a general-purpose AI chatbot and an AI agent to help users search for and apply for public services.

According to the ministry, the project aims to reduce reliance on overseas AI services while narrowing the digital divide. It also responds to concerns about restrictions on free AI services and possible changes by global technology companies. The nationwide service is expected to launch before the end of 2026.

Why does it matter?

The initiative combines digital inclusion with technological sovereignty by offering unrestricted access to a domestically developed AI service. Removing cost and usage limits could broaden AI adoption while integrating generative AI more closely into public services.

The project also reflects a wider international trend of governments investing in national AI capabilities to reduce dependence on foreign providers. As AI becomes part of essential digital infrastructure, countries are increasingly seeking greater control over the services, platforms and data that underpin public-sector AI deployment.

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