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Slovenia sets out an ambitious AI vision ahead of global summit

Ambitions for AI were outlined during a presentation at the Jožef Stefan Institute, where Slovenia’s Prime Minister Robert Golob highlighted the country’s growing role in scientific research and technological innovation.

He argued that AI has moved far beyond a supportive research tool and is now shaping the way societies function.

He called for deeper cooperation between engineering and the natural sciences instead of isolated efforts, while stressing that social sciences and the humanities must also be involved to secure balanced development.

Golob welcomed the joint bid for a new national supercomputer, noting that institutions once competing for excellence are now collaborating. He said Europe must build a stronger collective capacity if it wants to keep pace with the US and China.

Europe may excel in knowledge, he added, yet it continues to lag behind in turning that knowledge into useful tools for society.

Government officials set out the investment increases that support Slovenia’s long-term scientific agenda. Funding for research, innovation and development has risen sharply, while work has begun on two major projects: the national supercomputer and the Centre of Excellence for Artificial Intelligence.

Leaders from the Jožef Stefan Institute praised the government for recognising Slovenia’s AI potential and strengthening financial support.

Slovenia will present its progress at next week’s AI Action Summit in Paris, where global leaders, researchers, civil society and industry representatives will discuss sustainable AI standards.

Officials said that sustained investment in knowledge remains the most reliable route to social progress and international competitiveness.

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Growing reliance on AI sparks worries for young users

Research from the UK Safer Internet Centre reveals nearly all young people aged eight to 17 now use artificial intelligence tools, highlighting how deeply the technology has entered daily life. Growing adoption has also increased reliance, with many teenagers using AI regularly for schoolwork, social interactions and online searches.

Education remains one of the main uses, with students turning to AI for homework support and study assistance. However, concerns about fairness and creativity have emerged, as some pupils worry about false accusations of misuse and reduced independent thinking.

Safety fears remain significant, especially around harmful content and privacy risks linked to AI-generated images. Many teenagers and parents worry the technology could be used to create inappropriate or misleading visuals, raising questions about online protection.

Emotional and social impacts are also becoming clear, with some young people using AI for personal advice or practising communication. Limited parental guidance and growing dependence suggest governments and schools may soon consider stronger oversight and clearer rules.

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Structural friction, not intelligence, is holding back agentic AI

CIO leadership commentary highlights that many organisations investing in agentic AI, autonomous AI agents designed to execute complex, multi-step tasks, encounter disappointing results when deployments focus solely on outcomes like speed or cost savings without addressing underlying system design challenges.

The so-called ‘friction tax’ arises from siloed data, disjointed workflows and tools that force employees to act as manual connectors between systems, negating much of the theoretical efficiency AI promises.

The author proposes an ‘architecture of flow’ as a solution, in which context is unified across systems and AI agents operate on shared data and protocols, enabling work to move seamlessly between functions without bottlenecks.

This approach prioritises employee experience and customer value, enabling context-rich automation that reduces repetitive work and improves user satisfaction.

Key elements of such an architecture include universal context layers (e.g. standard protocols for data sharing) and agentic orchestration mechanisms that help specialised AI agents communicate and coordinate tasks across complex workflows.

When implemented effectively, this reduces cognitive load, strengthens adoption, and makes business growth a natural result of friction-free operations.

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Is AI eroding human intelligence?

The article reflects on the growing integration of AI into daily life, from classrooms to work, and asks whether this shift is making people intellectually sharper or more dependent on machines.

Tools such as ChatGPT, Grok and Perplexity have moved from optional assistants to everyday aids that generate instant answers, summaries and explanations, reducing the time and effort traditionally required for research and deep thinking.

While quantifiable productivity gains are clear, the piece highlights trade-offs: readily available answers can diminish the cognitive struggle that builds critical thinking, problem-solving and independent reasoning.

In education, easy AI responses may weaken students’ engagement in learning unless teachers guide their use responsibly. Some respondents point to creativity and conceptual understanding eroding when AI is used as a shortcut. In contrast, others see it as a democratising tutor that supports learners who otherwise lack resources.

The article also incorporates perspectives from AI systems themselves, which generally frame AI as neither inherently making people smarter nor dumber, but dependent on how it’s used.

It concludes that the impact of AI on human cognition is not predetermined by the technology, but shaped by user choice: whether AI is a partner that augments thinking or a crutch that replaces it.

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AI drives robots from labs into industry

The International Federation of Robotics says AI is accelerating the move of robots from research labs into real world use. A new position paper highlights rapid adoption across multiple industries as AI becomes a core enabler.

Logistics, manufacturing and services are leading AI driven robotics deployment. Warehousing and supply chains benefit from controlled environments, while factories use AI to improve efficiency, quality and precision in sectors including automotive and electronics.

The IFR said service robots are expanding as labour shortages persist, with restaurants and hospitality testing AI enabled machines. Hybrid models are emerging where robots handle repetitive work while humans focus on customer interaction.

Investment is rising globally, with major commitments in the US, Europe and China. The IFR expects AI to improve returns on robotics investment over the next decade through lower costs and higher productivity.

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Coal reserves could help Nigeria enter $650 billion AI economy

Nigeria has been advised to develop its coal reserves to benefit from the rapidly expanding global AI economy. A policy organisation said the country could capture part of the projected $650 billion AI investment by strengthening its energy supply capacity.

AI infrastructure requires vast and reliable electricity to power data centres and advanced computing systems. Technology companies worldwide are increasing energy investments as competition intensifies and demand for computing power continues to grow rapidly.

Nigeria holds nearly five billion metric tonnes of coal, offering a significant opportunity to support global energy needs. Experts warned that failure to develop these resources could result in major economic losses and missed industrial growth.

The organisation also proposed creating a national corporation to convert coal into high-value energy and industrial products. Analysts stressed that urgent government action is needed to secure Nigeria’s position in the emerging AI-driven economy.

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AI redefines criminal justice decision making

AI is increasingly being considered for use in criminal justice systems, raising significant governance and accountability questions. Experts warn that, despite growing adoption, there are currently no clear statutory rules governing the deployment of AI in criminal proceedings, underscoring the need for safeguards, transparency, and human accountability in high-stakes decisions.

Within this context, AI is being framed primarily as a support tool rather than a decision maker. Government advisers argue that AI could assist judges, police, and justice officials by structuring data, drafting reports, and supporting risk assessments, while final decisions on sentencing and release remain firmly in human hands.

However, concerns persist about the reliability of AI systems in legal settings. The risk of inaccuracies, or so-called hallucinations, in which systems generate incorrect or fabricated information, is particularly problematic when AI outputs could influence judicial outcomes or public safety.

The debate is closely linked to wider sentencing reforms aimed at reducing prison populations. Proposals include phasing out short custodial sentences, expanding alternatives such as community service and electronic monitoring, and increasing the relevance of AI-supported risk assessments.

At the same time, AI tools are already being used in parts of the justice system for predictive analytics, case management, and legal research, often with limited oversight. This gap between practice and regulation has intensified calls for clearer standards and disclosure requirements.

Proponents also highlight potential efficiency gains. AI could help ease administrative burdens on courts and police by automating routine tasks and analysing large volumes of data, freeing professionals to focus on judgment and oversight.

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Writing as thinking in the age of AI

In his article, Richard Gunderman argues that writing is not merely a way to present ideas but a core human activity through which people think, reflect and form meaning.

He contends that when AI systems generate text on behalf of users, they risk replacing this cognitive process with automated output, weakening the connection between thought and expression.

According to the piece, writing serves as a tool for reasoning, emotional processing and moral judgment. Offloading it to AI can diminish originality, flatten individual voice and encourage passive consumption of machine-produced ideas.

Gunderman warns that this shift could lead to intellectual dependency, where people rely on AI to structure arguments and articulate positions rather than developing those skills themselves.

The article also raises ethical concerns about authenticity and responsibility. If AI produces large portions of written work, it becomes unclear who is accountable for the ideas expressed. Gunderman suggests that overreliance on AI writing tools may undermine trust in communication and blur the line between human and machine authorship.

Overall, the piece calls for a balanced approach: AI may assist with editing or idea generation, but the act of writing itself should remain fundamentally human, as it is central to critical thinking, identity and social responsibility.

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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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