Capacity development

Learnovate launches community of practice on AI for learning

The Learnovate Centre, a global innovation hub focused on the future of work and learning at Trinity College Dublin, is spearheading a community of practice on responsible AI in learning, bringing together educators, policymakers, institutional leaders and sector specialists to discuss safe, effective and compliant uses of AI in educational settings.

This initiative aims to help practitioners interpret emerging policy frameworks, including EU AI Act requirements, share practical insights and align AI implementation with ethical and pedagogical principles.

One of the community’s early activities includes virtual meetings designed to build consensus around AI norms in teaching, compliance strategies and knowledge exchange on real-world implementation.

Participants come from diverse education domains, including schools, higher and vocational education and training, as well as representatives from government and unions, reflecting a broader push to coordinate AI adoption across the sector.

Learnovate plays a wider role in AI and education innovation, supporting research, summits and collaborative programmes that explore AI-powered tools for personalised learning, upskilling and ethical use cases.

It also partners with start-ups and projects (such as AI platforms for teachers and learners) to advance practical solutions that balance innovation with safeguards.

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Tech firms push longer working hours to compete in AI race

Tech companies competing in AI are increasingly expecting employees to work longer weeks to keep pace with rapid innovation. Some start-ups openly promote 70-hour schedules, presenting intense effort as necessary to launch products faster and stay ahead of rivals.

Investors and founders often believe that extended working hours improve development speed and increase the chances of securing funding. Fast growth and fierce global competition have made urgency a defining feature of many AI workplaces.

However, research shows productivity rises only up to a limit before fatigue reduces efficiency and focus. Experts warn that excessive workloads can lead to burnout and make it harder for companies to retain experienced professionals.

Health specialists link extended working weeks to higher risks of heart disease and stroke. Many experts argue that smarter management and efficient use of technology offer safer and more effective paths to lasting productivity.

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AI in education reveals a critical evidence gap

Universities are increasingly reorganising around AI, treating AI-based instruction as a proven solution for delivering education more efficiently. This shift reflects a broader belief that AI can reliably replace or reduce human-led teaching, despite growing uncertainty about its actual impact on learning.

Recent research challenges this assumption by re-examining the evidence used to justify AI-driven reforms. A comprehensive re-analysis of AI and learning studies reveals severe publication bias, with positive results published far more frequently than negative or null findings. Once corrected, reported learning gains from AI shrink substantially and may be negligible.

More critically, the research exposes deep inconsistency across studies. Outcomes vary so widely that the evidence cannot predict whether AI will help or harm learning in a given context, and no educational level, discipline, or AI application shows consistent benefits.

By contrast, human-mediated teaching remains a well-established foundation of learning. Decades of research demonstrate that understanding develops through interaction, adaptation, and shared meaning-making, leading the article to conclude that AI in education remains an open question, while human instruction remains the known constant.

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Study questions reliability of AI medical guidance

AI chatbots are not yet capable of providing reliable health advice, according to new research published in the journal Nature Medicine. Findings show users gain no greater diagnostic accuracy from chatbots than from traditional internet searches.

Researchers tested nearly 1,300 UK participants using ten medical scenarios, ranging from minor symptoms to conditions requiring urgent care. Participants were assigned to use either OpenAI’s GPT-4o, Meta’s Llama 3, Command R+, or a standard search engine to assess symptoms and determine next steps.

Chatbot users identified their condition about one-third of the time, with only 45 percent selecting the correct medical response. Performance levels matched those relying solely on search engines, despite AI systems scoring highly on medical licensing benchmarks.

Experts attributed the gap to communication failures. Users often provided incomplete information or misinterpreted chatbot guidance.

Researchers and bioethicists warned that growing reliance on AI for medical queries could pose public health risks without professional oversight.

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Crypto exchange scrambles after $40bn Bitcoin payout error

South Korea’s second-largest cryptocurrency exchange, Bithumb, is attempting to recover more than $40bn in Bitcoin after a promotional payout error credited customers with Bitcoin rather than Korean won.

The mistake occurred on 6 February during a ‘random box’ event, when prize values were entered in Bitcoin rather than in Bitcoin. Intended rewards totalled 620,000 won for 695 users, yet 620,000 bitcoins were distributed.

Only 249 customers opened their boxes, but the credited sums exceeded the exchange’s holdings.

Most balances were reversed through internal ledger corrections. About 13bn won ($9m) remains unrecovered after some users sold or withdrew funds before accounts were frozen. Authorities said 86 customers liquidated roughly 1,788 Bitcoins within 35 minutes.

Regulators have opened a full investigation, and lawmakers have scheduled an emergency hearing. Legal uncertainty remains over liability, while the exchange confirmed no hacking was involved and pledged stronger internal controls.

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Pakistan pledges major investment in AI by 2030

Pakistan plans to invest $1 billion in AI by 2030, Prime Minister Shehbaz Sharif said at the opening of Indus AI Week in Islamabad. The pledge aims to build a national AI ecosystem in Pakistan.

The government in Pakistan said AI education would expand to schools and universities, including remote regions. Islamabad also plans 1,000 fully funded PhD scholarships in AI to strengthen research capacity in Pakistan.

Shehbaz Sharif said Pakistan would train one million non IT professionals in AI skills by 2030. Islamabad identified agriculture, mining and industry as priority sectors for AI driven productivity gains in Pakistan.

Pakistan approved a National AI Policy in 2025, although implementation has moved slowly. Officials in Islamabad said Indus AI Week marks an early step towards broader adoption of AI across Pakistan.

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Educators turn to AI despite platform fatigue

Educators in the US are increasingly using AI to address resource shortages, despite growing frustration with fragmented digital platforms. A new survey highlights rising dependence on AI tools across schools and universities in the US.

The study found many educators in the US juggle numerous digital systems that fail to integrate smoothly. Respondents said constant switching between platforms adds to workload pressures and burnout in the US education sector.

AI use in the US is focused on boosting productivity, with educators applying tools to research, writing and administrative tasks. Many also use AI to support student learning as budgets tighten in the US.

Concerns remain in the US around data security, ethics and system overload. Educators said better integration between AI and learning tools could ease strain and improve outcomes in the US classroom.

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New AI breakthrough unlocks complex protein structures

AI is reshaping protein research, enabling scientists to decode complex molecular structures with greater speed and precision. Researchers at the National University of Singapore are using AI to accelerate biomedical discovery and disease research.

Protein function depends on three-dimensional structure, yet experimental mapping remains slow and resource-intensive. A team led by Zhang Yang developed D-I-TASSER, an AI tool that predicts 3D structures of complex multi-domain proteins.

The system combines AI with physics simulations, predicting protein segments before assembling a full structural model. Testing showed roughly 13 percent higher accuracy than existing leading methods, while enabling structural modelling across much of the human proteome.

Future development will expand the framework to RNA structures and protein-protein interactions, including antibody-antigen complexes, with the long-term goal of modelling dynamic protein folding processes inside living cells.

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Shadow AI becomes a new governance challenge for European organisations

Employees are adopting generative tools at work faster than organisations can approve or secure them, giving rise to what is increasingly described as ‘shadow AI‘. Unlike earlier forms of shadow IT, these tools can transform data, infer sensitive insights, and trigger automated actions beyond established controls.

For European organisations, the issue is no longer whether AI should be used, but how to regain visibility and control without undermining productivity, as shadow AI increasingly appears inside approved platforms, browser extensions, and developer tools, expanding risks beyond data leakage.

Security experts warn that blanket bans often push AI use further underground, reducing transparency and trust. Instead, guidance from EU cybersecurity bodies increasingly promotes responsible enablement through clear policies, staff awareness, and targeted technical controls.

Key mitigation measures include mapping AI use across approved and informal tools, defining safe prompt data, and offering sanctioned alternatives, with logging, least-privilege access, and approval steps becoming essential as AI acts across workflows.

With the EU AI Act introducing clearer accountability across the AI value chain, unmanaged shadow AI is also emerging as a compliance risk. As AI becomes embedded across enterprise software, organisations face growing pressure to make safe use the default rather than the exception.

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Winter Olympics spotlight immersive AI tech from Alibaba

Alibaba Group has launched ‘Wonder on Ice,’ an interactive AI showcase at the Milano Cortina 2026 Olympic Winter Games, blending AI and cloud computing to enhance fan engagement. The installation sits in Milan’s Piazza del Castello, set against the historic Castello Sforzesco.

Designed as an immersive space, the showcase highlights AI-powered virtual retail and interactive Olympic experiences. Visitors enter a snow-globe-inspired pavilion where AI guides them through tailored content based on their individual interests.

The opening featured IOC President Kirsty Coventry and Alibaba Chairman Joe Tsai, underscoring a focus on accessibility, sustainability, and global connectivity. The activation also unveiled AIGC Championship winners, with AI-generated winter sports artworks displayed throughout the Games.

Alibaba’s broader Olympic technology programme includes cloud-based broadcasting, AI-driven 360-degree replays, and sustainability systems for energy and carbon optimisation, powered by its Qwen AI models.

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