European Commission launches AI cyber defence strategy

The European Commission has presented an Action Plan on Cybersecurity and Artificial Intelligence to strengthen Europe’s response to AI-related cyber risks.

The plan aims to help member states, businesses and public authorities use AI safely while addressing the cybersecurity risks created by advanced AI models.

The Commission said AI can help detect vulnerabilities, prevent cyberattacks and protect critical infrastructure. However, it warned that malicious actors can also use AI to automate attacks, identify weaknesses and carry out cyber operations at greater speed and scale.

The Action Plan focuses on three objectives: promoting the safe and responsible use of advanced AI, reinforcing EU cybersecurity and resilience, and scaling up Europe’s AI capabilities for cybersecurity.

The Commission said it will strengthen Europe’s capacity to evaluate AI models before they are placed on the EU market, in line with the AI Act.

It will also work with ENISA to develop a European Blueprint for secure access to advanced AI systems for cybersecurity purposes.

A secure testing platform will support organisations in critical sectors, including energy, transport, health, finance and public administration, in testing and deploying AI solutions safely.

The plan also encourages the use of AI, including open-source models where appropriate, to detect vulnerabilities faster and improve prevention and response to cyberattacks.

The Commission said it will launch an EU Grand Challenge on AI for cybersecurity to support the development of new AI-powered security solutions.

Why does it matter?

AI is becoming central to both cyber defence and cybercrime. The EU Action Plan recognises that advanced models can help defenders detect vulnerabilities and respond faster, but can also help attackers automate operations and scale incidents. By linking AI model evaluation, critical-sector testing, ENISA cooperation, existing cybersecurity laws and investment in sovereign AI capabilities, the Commission is trying to turn AI cybersecurity into a coordinated EU policy area rather than leaving it to fragmented national or private-sector responses.

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Claude Fable 5, frontier AI models and the future of cybersecurity

The release of Anthropic’s Claude Fable 5 may prove to be one of the most significant AI developments of 2026. At first glance, the launch appeared to be another milestone in the rapidly evolving frontier AI landscape, showcasing improvements in reasoning, software engineering and complex problem solving.

Yet within days, Fable 5 became the centre of an international debate involving cybersecurity, national security, export controls and technological sovereignty.

Anthropic introduced Fable 5 as a public-facing version of its more advanced Mythos 5 model, offering access to frontier-level capabilities while incorporating additional safeguards designed to limit misuse in sensitive domains.

Anthropic has launched Claude Fable 5

The company presented the model as a major step forward in AI performance, particularly in coding, reasoning and autonomous task completion. However, concerns surrounding its cybersecurity capabilities quickly caught the attention of policymakers and security agencies.

The situation escalated when the USA imposed export control restrictions, affecting access to Anthropic’s most advanced models. What began as a product launch rapidly evolved into a broader discussion about whether frontier AI systems should be treated as strategic technologies comparable to advanced semiconductors, encryption systems, or critical infrastructure.

The story, however, did not end there. Less than three weeks later, the US government lifted the restrictions after Anthropic introduced additional safeguards, strengthened collaboration with federal authorities, and agreed to participate in a broader framework for evaluating frontier AI security.

Rather than representing a simple regulatory dispute, the episode demonstrated how frontier AI governance is becoming an evolving process built upon continuous technical assessment, industry cooperation, and government oversight.

The Fable 5 episode highlights a reality that is increasingly difficult to ignore. AI is no longer simply a tool for productivity and innovation. Frontier models are emerging as technologies with profound implications for cybersecurity, national defence, economic competitiveness, and international relations.

As governments and companies struggle to understand the opportunities and risks associated with increasingly capable AI systems, Fable 5 offers an early glimpse into what could become one of the defining policy debates of the coming decade.

The rise of frontier AI models

The concept of a frontier AI model refers to the most advanced systems available at a given moment. These models represent the leading edge of AI capabilities and often demonstrate performance levels significantly beyond previous generations.

Claude Fable 5 belongs to this category. Anthropic designed the model to perform complex reasoning tasks, analyse large quantities of information, generate software code and assist users with sophisticated technical challenges.

Unlike earlier generations of AI assistants that primarily focused on conversational interactions, frontier models increasingly function as problem-solving systems capable of performing intricate tasks across multiple domains.

One of the most notable characteristics of Fable 5 is its ability to assist with software engineering and technical analysis. The model can review source code, identify patterns, suggest improvements and help users navigate highly complex technical environments.

Such capabilities are particularly valuable in cybersecurity, where analysts often face enormous volumes of code, logs and threat intelligence data.

Behind Fable 5 is Mythos 5, a model that Anthropic initially released only to trusted participants in Project Glasswing, a programme focused on defensive cybersecurity research.

More organisations gain access through Anthropic to advanced AI cyber defence tools.

While Mythos offers stronger offensive cybersecurity capabilities for vetted organisations, Fable 5 was designed for broader public use with significantly stronger safeguards that limit potentially dangerous behaviour without substantially reducing its usefulness for legitimate applications.

Anthropic has emphasised that Fable 5 was subjected to extensive testing and red teaming before its release. In the weeks preceding its launch, the company reportedly reassigned researchers and engineers from multiple teams to strengthen its cybersecurity protections, reflecting a growing recognition that frontier models require safety engineering on a scale previously unseen in commercial AI development.

The challenge is that the same qualities that make frontier models like the Fable 5 valuable also make them strategically important. As AI capabilities continue to advance, governments increasingly view these systems not merely as software products but as assets with potential national security implications.

Why the USA intervened

The US decision to restrict access to Anthropic’s most advanced models marked a significant turning point in the AI governance debate.

Historically, the release of AI systems has largely been managed by technology companies themselves. Governments have generally focused on regulation and oversight rather than direct intervention in model availability.

The response to Fable 5 suggests that such an approach may be changing.

The primary concern involved cybersecurity capabilities. Mythos-class models demonstrated the ability to identify software vulnerabilities and assist with highly advanced technical analysis. While such capabilities offer substantial defensive benefits, they also raise concerns about potential misuse.

The immediate trigger came after Amazon researchers identified a technique capable of bypassing some of Fable 5’s cybersecurity safeguards.

During testing, the model successfully identified several software vulnerabilities and, in one instance, generated code illustrating how one of those vulnerabilities could be exploited.

Although Anthropic argued that comparable outputs could also be obtained from several existing AI models and that the behaviour did not expose Mythos-level offensive capabilities, the incident convinced US authorities that additional safeguards were necessary before wider deployment.

From a national security perspective, policymakers increasingly fear that highly capable AI systems could assist malicious actors in discovering vulnerabilities, developing exploits or conducting cyber operations at a scale that exceeds existing defensive capabilities.

As a result, access to frontier models is beginning to resemble access to other strategically important technologies.

The restrictions also generated controversy because they affected not only geopolitical competitors but also close allies.

Since Anthropic had no practical method for verifying users’ nationality in real time, it temporarily suspended access to both Fable 5 and Mythos 5 for all users rather than attempting selective enforcement.

The incident highlighted the growing reality that access to frontier AI may increasingly become subject to geopolitical considerations.

Yet the restrictions ultimately proved temporary. Following intensive collaboration between Anthropic, Amazon, and US government agencies, the Department of Commerce lifted the export controls after Anthropic implemented stronger safeguards.

US Commerce Department Anthropic Claude Fable 5

The company introduced a new safety classifier capable of blocking reported behaviour in more than 99% of tested cases while redirecting potentially dangerous requests to its less capable Opus 4.8 model.

The episode represents a significant shift in frontier AI governance. Rather than relying solely on regulation or voluntary commitments, governments and developers increasingly appear to favour continuous technical evaluation, rapid safeguard improvements and close operational cooperation.

AI as a cybersecurity defender

Despite concerns about misuse, the defensive potential of frontier AI models is immense.

Cybersecurity professionals face an increasingly difficult environment. Organisations must defend against ransomware groups, state-sponsored actors, supply chain attacks, phishing campaigns and countless other threats.

At the same time, many organisations struggle with cybersecurity talent shortages and limited resources.

Frontier models offer a potential solution.

Systems such as Fable 5 can analyse software code, identify vulnerabilities, process threat intelligence and support incident response activities at speeds that would be impossible for human analysts alone. Tasks that previously required days of manual effort can often be completed in minutes.

The implications extend well beyond private sector organisations. Governments, healthcare providers, financial institutions, energy companies and critical infrastructure operators could all benefit from AI-assisted security capabilities.

Frontier models may help defenders identify vulneabilities before attackers discover them, improving overall resilience across digital ecosystems.

Anthropic argues that Mythos 5 was specifically developed to support trusted organisations engaged in defensive cybersecurity. Rather than serving as an offensive cyber tool, the model is intended to accelerate vulnerability discovery, strengthen software security and improve defensive research.

In many respects, it illustrates the central dilemma surrounding frontier AI. The same capability that appears dangerous in one context may become invaluable when deployed responsibly by trusted defenders.

The US government has increasingly recognised the potential. Recent policy initiatives encourage frontier AI developers to collaborate with federal agencies through pre-release testing, shared evaluations and coordinated threat intelligence.

Anthropic has now committed to expanding that cooperation by providing designated government partners with early access to future frontier models, supporting joint research efforts and participating in security evaluations before broader public deployment.

Perhaps most importantly, the Fable 5 episode demonstrates that cybersecurity is becoming one of the primary drivers of frontier AI development.

While public attention often focuses on conversational abilities or creative applications, governments increasingly judge advanced models by their ability to strengthen national cyber resilience.

As cyber threats continue to grow in scale and sophistication, frontier AI like Fable 5 may become an indispensable component of future defensive strategies.

The emergence of the AI-enabled attacker

The problem is that cybersecurity has always been a dual-use domain. Every major defensive innovation has historically created new opportunities for offensive actors, and frontier AI models are unlikely to be an exception.

Ironically, the same capabilities that help defenders can often help attackers.

A model capable of identifying vulnerabilities can potentially assist malicious actors in locating weaknesses within software systems. A system that helps defenders analyse code can also support offensive security research.

Likewise, a model capable of generating scripts for legitimate automation may also assist with harmful activities if appropriate safeguards are bypassed.

Frontier AI cybersecurity

Such a reality has led many experts to describe frontier AI as both a shield and a sword.

Security agencies have repeatedly warned that AI is lowering the barriers to entry for cybercriminals. Activities that once required extensive technical expertise may become increasingly accessible through AI assistance.

Phishing campaigns, malware development, reconnaissance operations, exploit research, and vulnerability discovery could all become faster and considerably more efficient.

The concern that extends beyond individual hackers is that organised cybercriminal groups and state-sponsored actors already possess substantial technical expertise.

Frontier AI does not necessarily replace that expertise, but it has the potential to amplify it significantly. Operations that previously required specialised teams and considerable preparation may eventually be conducted more rapidly, with greater precision, and at a much larger scale.

The emergence of AI agents further increases these concerns. Unlike traditional chat-based assistants, autonomous agents are increasingly capable of performing multi-step tasks with limited human supervision.

In a cybersecurity context, Fable 5 and similar systems could theoretically identify vulnerabilities, gather intelligence, write software, execute defensive workflows, or assist with incident response almost autonomously. The same autonomy, however, could also be abused if deployed for malicious purposes.

Rather than eliminating cyber threats, frontier AI may fundamentally change the nature of digital conflict. Success may increasingly depend not only on technological capability but also on who can adapt more quickly as AI systems continue to evolve.

The limits of safety guardrails

Recognising the risks associated with powerful AI systems, Anthropic implemented extensive safeguards within Fable 5.

The company sought to make the model widely accessible while limiting its ability to assist with highly sensitive activities. Certain cybersecurity, biological and other high-risk requests are subject to additional restrictions. Anthropic has argued that such measures significantly reduce the likelihood of misuse.

Unlike previous generations of AI models, Fable 5 relies on multiple overlapping layers of protection rather than a single safety mechanism. Anthropic describes this approach as defence in depth.

Fable 5 Anthropic multilayer protection AI model

The model combines behavioural training, specialised safety classifiers, continuous monitoring, and post-deployment analysis to detect potentially harmful cybersecurity requests before they reach the model itself.

One of the most important components of the system is the use of dedicated safety classifiers. These smaller AI systems analyse prompts in real time to determine whether they involve potentially dangerous cybersecurity activities.

Requests that appear harmful or sufficiently ambiguous are blocked before the model generates a response.

Following the June export control directive, Anthropic introduced an improved classifier specifically designed to detect the jailbreak technique identified by Amazon researchers. According to the company, the updated safeguard blocks the reported behaviour in more than 99 per cent of tested cases.

An additional layer of protection redirects blocked requests away from Fable 5 altogether. Instead of simply refusing to respond, certain requests are automatically transferred to Anthropic’s less capable Opus 4.8 model, allowing legitimate users to continue working while preventing access to Fable 5’s more advanced cybersecurity capabilities.

Yet the broader AI industry has learned that no safeguard system is perfect.

Researchers continue to demonstrate that even highly protected frontier models remain vulnerable to sophisticated jailbreak techniques and adversarial attacks. Determined users often find creative ways to circumvent restrictions, particularly when motivated by financial gain or malicious intent.

Anthropic itself acknowledges that it is probably impossible to develop a frontier AI model that is completely immune to jailbreaks. Rather than pursuing absolute protection, the company aims to make successful attacks sufficiently difficult, resource-intensive, and technically demanding enough to make the overwhelming majority of malicious attempts impractical.

Such a philosophy represents an important evolution in AI safety. Security is no longer viewed as a binary condition in which systems are either safe or unsafe. Instead, it is increasingly understood as a continuous process of risk reduction, rapid adaptation, and ongoing improvement.

Does it mean that safeguards are ineffective?

On the contrary, they play a critical role in reducing risk and raising barriers to misuse. However, the Fable 5 debate illustrates that AI safety should be understood as an ongoing process rather than a final destination.

As frontier models become increasingly capable, organisations will need to invest continuously in monitoring, testing and improving security measures. The challenge is not simply to build safeguards but to adapt them within an environment where both AI capabilities and attack techniques evolve rapidly.

AI sovereignty and strategic dependence

Perhaps the most unexpected consequence of the Fable 5 controversy was the renewed focus on AI sovereignty.

AI sovereignty security infrastructure

For years, discussions about technological sovereignty centred on semiconductors, telecommunications infrastructure and cloud computing. Frontier AI models are now becoming part of this debate.

The temporary disruption of access to Anthropic’s most advanced systems demonstrated how governments, businesses and research institutions can become dependent on technologies they do not control.

If access to frontier AI can be restricted through export controls or national security directives, organisations may face strategic vulnerabilities similar to those associated with dependence on foreign energy supplies or critical infrastructure.

Although the restrictions were ultimately lifted, the episode served as an important reminder that access to frontier AI increasingly depends not only on technological capability but also on trust between governments, developers and international partners.

Anthropic’s decision to strengthen safeguards, deepen cooperation with US authorities and expand information sharing became central to restoring global access to Fable 5.

The issue is particularly relevant for the EU and other allied nations. Many countries possess strong AI research communities but remain dependent on a relatively small number of companies for access to the world’s most advanced models.

As a result, policymakers are increasingly discussing sovereign AI capabilities, domestic model development and technological autonomy. What once seemed like a long-term aspiration is now viewed by many as an urgent strategic consideration.

The Fable 5 episode revealed that access to AI itself could become a geopolitical issue.

Frontier models and the future of cybersecurity

Looking ahead, frontier AI models are likely to transform cybersecurity in ways that far exceed current debates.

Future defensive systems could continuously monitor networks, analyse software, identify vulnerabilities, and recommend mitigations with minimal human intervention.

AI-powered assistants could become standard components of security operations centres, helping analysts respond to threats more effectively.

At the same time, offensive capabilities are likely to evolve. Adversaries may use AI to automate reconnaissance, analyse targets and adapt attack strategies dynamically. Cybersecurity may increasingly involve interactions between competing AI systems rather than interactions solely between human operators.

Some experts argue that the future of cyber conflict will be defined by machine-versus-machine competition, with humans providing oversight and strategic direction rather than performing every operational task themselves.

Equally significant is the emerging effort to establish common security standards for frontier AI.

One of the most important outcomes of the Fable 5 controversy has been Anthropic’s collaboration with Amazon, Microsoft, Google and other Project Glasswing partners to develop a shared framework for evaluating AI jailbreaks.

The proposed methodology assesses capability gains, breadth of misuse, ease of weaponisation, and discoverability, creating a common language through which developers and governments can evaluate the severity of newly identified vulnerabilities.

If successful, such a framework could play a role similar to the Common Vulnerability Scoring System, which has long provided the cybersecurity community with a common method for assessing software vulnerabilities.

Standardising how AI jailbreaks are evaluated would enable developers to prioritise responses more consistently while allowing governments to better understand the actual level of risk posed by newly discovered attacks.

The initiative also reflects a broader shift in frontier AI governance. Rather than relying exclusively on post-deployment regulation, governments and developers are increasingly cooperating during the development process through pre-release testing, shared evaluations, coordinated threat intelligence, and continuous red teaming.

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Such a future offers enormous potential benefits. It could significantly improve security outcomes, reduce response times, and strengthen resilience across critical infrastructure sectors.

Yet it also introduces new challenges involving accountability, transparency, control, and governance. Ensuring that increasingly autonomous systems remain aligned with human objectives will become one of the central cybersecurity questions of the AI era.

Conclusion

The release of Claude Fable 5 may ultimately be remembered as more than a technological milestone. It represents one of the clearest examples to date of how AI, cybersecurity, national security, and technological sovereignty are becoming deeply interconnected.

For defenders, frontier AI models offer unprecedented opportunities to strengthen security, improve resilience, and respond more effectively to an increasingly complex threat environment. For attackers, many of the same capabilities create opportunities to automate, scale, and enhance malicious operations.

The resulting tension lies at the heart of the Fable 5 debate. Frontier AI is neither inherently beneficial nor inherently harmful. Its impact depends on how it is developed, governed, and deployed.

Perhaps the most important lesson from the Fable 5 episode is that frontier AI governance is beginning to move from theory to practice.

The rapid sequence of export controls, technical reviews, stronger safeguards, renewed deployment and closer cooperation between Anthropic and the US government demonstrates that innovation and security do not necessarily have to be in opposition.

Instead, they increasingly depend on continuous collaboration between governments, researchers, technology companies, and the broader cybersecurity community.

Ultimately, we may remember Fable 5 not simply as another AI product launch, but as one of the first moments when the world began to recognise that access to advanced AI could become a strategic issue in its own right.

As governments, organisations, and citizens, each of us is becoming part of that transition.

The challenge is no longer whether AI will reshape cybersecurity, but whether we can establish the trust, standards and international cooperation necessary to ensure that frontier models like Fable 5 strengthen digital resilience rather than undermine it for generations to come.

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Spain leads international coalition on child safety and AI

Spain has launched the International Coalition for Children’s Rights and Protection in the Age of AI with a group of countries and international organisations.

The initiative was presented during the first UN Global Dialogue on AI Governance in Geneva and is intended to ensure that AI respects children’s safety, healthy development and rights.

Spain said the coalition was promoted with support from France, Kenya and the EU.

Participating countries include Austria, Brazil, Bulgaria, Canada, Czechia, South Korea, El Salvador, Estonia, France, Indonesia, Italy, Japan, Kenya, Luxembourg, Morocco and the Netherlands.

UNICEF, UNESCO, the Office of the UN High Commissioner for Human Rights, the International Telecommunication Union and the UN Office for Digital and Emerging Technologies have also joined the coalition.

The coalition aims to coordinate action between governments, UN bodies, technology companies, civil society, child well-being experts and educators.

Signatories warned that rapid AI deployment is transforming the digital environments in which children learn, communicate and interact. They said AI can create opportunities, but can also amplify risks such as manipulation, harmful content, sexual deepfakes, AI-generated child sexual abuse material and algorithmic profiling of minors.

Coalition members are committed to promoting safe, reliable and trustworthy AI systems that respect children’s rights and include children’s views in the design, deployment and governance of AI systems that affect them.

Why does it matter?

The coalition places child protection at the heart of the emerging UN AI governance agenda. AI-related risks for children now include not only harmful content and cyberbullying, but also sexual deepfakes, AI-generated child sexual abuse material, manipulative algorithms and profiling of minors. A UN-based coalition could help align national approaches around safe-by-design systems, age-appropriate safeguards and children’s participation. However, its impact will depend on whether members move from declarations to practical standards and enforcement.

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China and Denmark expand cooperation on AI and innovation

Chinese Foreign Minister Wang Yi has expressed China’s readiness to strengthen cooperation with Denmark in areas including the green economy, innovation and AI during a visit to Copenhagen. Wang made the remarks in a meeting with Danish King Frederik X, alongside separate talks with Danish Foreign Minister Lars Lokke Rasmussen.

During a meeting with King Frederik X, Wang highlighted the longstanding relationship between China and the Danish royal family, noting previous state visits and describing them as a symbol of mutual respect and friendship.

King Frederik X said bilateral relations continue to develop positively, highlighting active trade and people-to-people exchanges. He added that the Danish royal family is ready to support closer cooperation, including in AI and other areas of mutual interest.

Wang also stressed the importance of people-to-people exchanges as the foundation of bilateral friendship during his visit to Copenhagen.

Why does it matter?

The discussions illustrate how AI is becoming a regular feature of bilateral diplomacy alongside trade, innovation and green technologies. Governments are increasingly treating cooperation on emerging technologies as part of broader economic and strategic partnerships rather than as a standalone technology issue.

The talks also reflect China’s continued effort to strengthen relations with individual EU member states despite broader tensions between Beijing and the European Union over trade, technology and economic security. Cooperation in areas such as AI and innovation offers a channel for engagement even as wider geopolitical differences persist.

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ENISA warns frontier AI is compressing cyberattack timelines

The European Union Agency for Cybersecurity has warned that frontier AI models are compressing cyberattack timelines and challenging traditional defence practices.

In a July 2026 paper, ENISA said advanced AI models are reducing the time between vulnerability discovery and exploitation, creating new pressure on vulnerability management, patching and incident response.

The agency said open-weight models may reach similar capabilities within 9 to 12 months, while existing models combined with skilled security experts can already produce comparable results.

ENISA warned that attackers may gain access to exploits before fixes are available, while legacy systems and end-of-life products could become more exposed to AI-assisted vulnerability discovery.

The agency also said more frequent patch releases may increase the risk of service disruption, while open-source maintainers could be overwhelmed by AI-generated vulnerability reports.

Security fundamentals still matter, but ENISA said defenders must apply them faster. It recommended shifting resources from vulnerability discovery towards risk-based prioritisation, rapid triage, remediation and risk reduction.

The paper also calls for defensive AI tools to be integrated into software development, incident response and threat modelling, with human-gated workflows and stronger workforce skills.

At the EU level, ENISA said existing frameworks, including NIS2, the Cyber Resilience Act, and the EU AI Act, should be used to assess and mitigate systemic risks linked to advanced AI models.

For defenders, the agency recommended near-real-time security operations, AI-assisted threat modelling, dynamic incident response pipelines and single-digit-minute detection and response targets.

Why does it matter?

ENISA’s paper frames frontier AI as a structural cybersecurity challenge, not just another tool for attackers or defenders. If vulnerability discovery, exploit development, and lateral movement happen at machine speed, organisations will need faster triage, stronger automation and clearer human oversight. The report also connects AI cybersecurity to the EU’s wider regulatory framework, showing that NIS2, the Cyber Resilience Act and the AI Act will all matter in managing systemic cyber risks from advanced models.

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ECB researchers use LLMs to measure geoeconomic tension

The European Central Bank (ECB) researchers have published a working paper introducing a Large Language Model-based method for measuring geopolitical and geoeconomic tensions in the euro area.

The paper develops the LLM Geoeconomic and Geopolitical Tension index, or LGPT, using a large dataset of European newspaper articles in local languages.

Researchers analysed almost 20 million articles from newspapers in France, Germany, Italy and Spain, covering the period from 1999 to 2025.

The methodology combines a fine-tuned multilingual BERT model with GPT-4o in a two-stage classification process.

BERT is used to filter articles likely to relate to geopolitical or geoeconomic tension, while GPT-4o classifies relevant articles and extracts structured information.

The index distinguishes narrower geopolitical tensions from geoeconomic tensions, including economic policy or the use of resources for geopolitical purposes.

It also breaks geoeconomic tension into four sources: trade, energy, finance and technology.

The authors argue that the multilingual LLM approach can capture nuance that dictionary-based methods may miss, while providing more granular data for economic analysis.

They also show how the index can be integrated into macroeconomic modelling to assess the effects of geoeconomic tensions on output and inflation in the euro area.

Why does it matter?

The paper shows how LLMs can be used as analytical tools for economic policymaking, not only as chatbots or productivity software. Measuring geoeconomic tension more precisely matters because trade conflict, energy security, financial fragmentation and technology restrictions can affect inflation, output and financial stability in different ways. A multilingual approach is especially relevant for the euro area because it captures local-language reporting from major member states rather than relying only on English-language media or keyword lists.

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Australia’s National AI Centre lists Microsoft Copilot training sessions for workers

Australia’s National AI Centre has listed two in-person Microsoft Copilot training sessions in Queensland aimed at helping participants build practical workplace AI skills.

The first session, Intro to Copilot, is scheduled for 7 July from 10:00 to 11:00 at The Precinct in Fortitude Valley. It is designed as an introductory session covering Microsoft Copilot Chat features, strengths and practical workplace uses for people with personal or business accounts.

The second session, Microsoft Copilot Workshop, will be held later the same day from 17:30 to 19:00 at the same venue. It is intended for people who already have access to Copilot at work but use it infrequently or want to build confidence using the tool.

Both Microsoft Copilot training sessions cover the fundamentals of generative AI, Copilot access, interface features, differences between personal and business versions, chat management, prompting techniques, Pages, Agents and responsible AI use. Participants in the workshop are asked to bring a device for hands-on exercises.

The events are hosted by the Queensland Government, with early-bird tickets priced at AUD 25 and general admission at AUD 40. The National AI Centre notes that registration is handled through third-party websites and that it does not endorse or take responsibility for their content.

Why does it matter?

The training sessions reflect a broader shift from introducing generative AI to helping employees use it effectively in day-to-day work. As tools such as Microsoft Copilot become more widely available, organisations are increasingly investing in practical skills such as prompting, workflow integration and responsible AI use.

The initiative also highlights the growing importance of AI literacy as a workforce capability. Building confidence in using AI tools may help organisations improve productivity while encouraging safer and more informed adoption across different sectors.

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NVIDIA unveils RTX Spark for the AI-powered PC era

NVIDIA and Microsoft have introduced RTX Spark, a new Windows PC platform designed for personal AI agents.

NVIDIA describes RTX Spark as a 1-petaflop superchip that combines its AI and graphics stack with Windows-native agent capabilities.

NVIDIA’s Blackwell architecture powers the platform and supports up to 128GB of unified memory.

According to NVIDIA, RTX Spark will allow users to run local AI agents, large language models, creative workflows and advanced games on laptops and compact desktop PCs.

The company said the platform can run 120-billion-parameter large language models with up to 1 million tokens of context locally.

NVIDIA and Microsoft are also introducing new Windows security primitives and NVIDIA OpenShell to help agents run securely on primary devices.

OpenShell will allow users to define what agents can and cannot do, route queries to local models according to privacy policies and mask personal information when cloud models are used.

RTX Spark-powered laptops and compact desktops are expected to be available this autumn from manufacturers including ASUS, Dell, HP, Lenovo, Microsoft Surface and MSI, with Acer and GIGABYTE models to follow.

Why does it matter?

RTX Spark reflects the industry shift towards AI-native personal computers, where more AI processing happens locally on the device. Running agents and large models on PCs could improve privacy, reduce latency and make advanced AI tools less dependent on cloud access. The governance question is whether local agents can operate with clear user permissions, strong containment and meaningful accountability as they gain the ability to search files, interact with apps and execute tasks across a personal device.

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AI is reshaping work more through job transformation than job loss, WSIS panel hears

AI is changing the world of work in more complex ways than simply replacing workers, according to experts speaking at the WSIS Forum 2026. Panellists from the International Labour Organization (ILO) and the International Telecommunication Union (ITU) argued that while AI will automate some tasks, its broader impact will be felt through changing job quality, workplace surveillance, recruitment practices and skills requirements, making human-centred policies essential to ensure workers benefit from the digital transition.

The discussion highlighted that governments, employers and workers all have a role in shaping the future of work, with speakers calling for stronger labour protections, social dialogue and investment in digital skills to prevent AI from deepening existing inequalities.

AI is changing tasks and working conditions more than eliminating jobs

Sher Verick, Head of the Employment Strategies Unit in the Employment Policy Department of the ILO, challenged the widespread narrative that AI will trigger mass unemployment. Presenting findings from the ILO’s AI exposure index, he said around one in four workers worldwide are exposed to AI, yet only 3.3% of global employment falls into occupations that are highly vulnerable to automation.

‘The focus shouldn’t only be on job losses,’ Verick argued, explaining that AI is transforming how work is organised rather than simply eliminating occupations. Jobs involving a diverse range of tasks are more likely to change than disappear, while new roles are already emerging across AI supply chains, including data annotation and other support functions.

He stressed that the most significant impact may be on job quality rather than job numbers. Automated recruitment systems, algorithmic task allocation and AI-driven performance monitoring are already reshaping working conditions across sectors, while productivity gains could eventually create new employment opportunities through wider economic growth.

Algorithmic management raises new concerns for workers

Uma Rani Amara, Senior Economist at the Research Department of the ILO, argued that the conversation about AI should extend well beyond generative AI tools such as ChatGPT to include the algorithmic management systems increasingly used across workplaces.

Drawing on examples from manufacturing and healthcare, she explained that AI-powered surveillance tools, CCTV systems and digital performance dashboards are allowing employers to monitor workers more closely than ever before. While companies often present these technologies as efficiency tools, she warned that they can increase workplace stress, intensify workloads and reduce workers’ autonomy.

In hospitals, digital workflow management systems may improve patient scheduling and resource allocation, but they also place nurses and doctors under greater pressure by increasing workload intensity and extending on-call responsibilities. Even commonly used tools such as messaging applications can create new privacy risks when sensitive information is shared outside secure systems.

Rani also drew attention to what she described as AI’s ‘invisible workforce’, the millions of people, largely based in the Global South, who label data, moderate content, and perform other essential tasks that allow AI systems to function.

‘We should stop calling it AI and start calling it ‘human-in-the-loop intelligence’,’ she said, arguing that AI’s apparent autonomy obscures the human labour underpinning every stage of its development.

She called for stronger protections for these workers through measures such as fair labour standards, mandatory disclosure of AI supply chains and certification systems showing where training data originates and under what working conditions it was produced.

Governments must shape the future of work

Juan Chacaltana, Senior Employment Policies Specialist at ILO, argued that technological change should not be viewed as an inevitable force to which societies simply adapt.

‘The future of work should be shaped through policy,’ he said, presenting findings from an ILO review of 75 employment policy documents that found governments increasingly integrating digital technologies into employment services, labour market information systems and skills programmes.

However, he cautioned against viewing digital tools as a solution in themselves. While technologies can help modernise public employment services and support labour market formalisation, they cannot replace traditional drivers of economic development such as productivity growth, investment and strong institutions.

Chacaltana also warned that governments should avoid using digital tools primarily for surveillance or enforcement. Instead, introducing digital identity systems, AI-assisted public services and labour market technologies should involve workers, employers and other stakeholders through meaningful social dialogue.

The discussion also highlighted groups facing particular risks during the AI transition. Rani warned that young workers could lose the entry-level jobs that traditionally provide experience and career progression, while women risk a ‘double whammy’ of displacement from automation alongside discrimination embedded in biassed AI recruitment systems. Older workers and people in informal employment could also face new forms of exclusion or reduced autonomy as algorithmic systems increasingly influence workplace decisions.

Skills and cooperation are key to an inclusive AI transition

Praachi Kumar, Capacity Development Officer at ITU, said demand for AI-related training has grown rapidly, with interest in AI courses through ITU Academy tripling over the past five years.

The Academy now serves more than 115,000 ICT professionals, the majority from developing countries, while ITU’s Digital Transformation Centres initiative has reached around 700,000 people in underserved communities through digital skills programmes.

Kumar said lifelong learning must remain human-centred, combining technical knowledge with practical experience and peer learning. She also highlighted new multilingual AI governance courses developed in partnership with UNESCO to help address widening skills gaps.

Throughout the discussion, speakers agreed that preparing workers for AI requires far more than technical training. They called for coordinated action across labour, education and technology ministries, alongside stronger partnerships between governments, employers, trade unions and international organisations.

Closing the session, moderator Maria Prieto Berhouet said the debate had consistently returned to one central principle: AI should serve people, not the other way around. Rather than allowing technological change to dictate the future of work, participants argued that governments and social partners must actively shape AI’s role so it enhances productivity while protecting workers’ rights, dignity and opportunities.

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WSIS panel calls for a broader approach to youth mental health online

A WSIS Forum 2026 session called for a broader approach to young people’s mental health online, warning that screen time alone is an insufficient measure of digital well-being.

The session, ‘Young people’s mental health in an online world’, examined the impact of digital devices and social media on young people’s mental health, with speakers addressing regulation, education, psychological support and legal remedies.

Alexandre Carette, Information Specialist at the UN in Geneva and moderator of the session, said digital use is not only a concern for young people or experts, but for everyone who relies on digital tools. He linked the discussion to wider UN debates on access, privacy and the role of digital technologies in everyday life.

Niels Weber, a psychologist and psychotherapist in Switzerland specialising in hyperconnectivity, said screen time gives only limited information about young people’s mental health. He argued that the more important questions are what young people do on screens, what they do away from screens, and how digital practices fit into their wider development.

Weber also cautioned against describing most problematic digital use as addiction. He said many platforms are designed to prolong use, but that such a design should be understood as a retention problem rather than automatically as addiction. In clinical terms, he said the more relevant marker is suffering, either for the young person or for families who experience digital use as a constant source of conflict.

Tatiana Debrabandere, Project Manager at the High Council for Media Literacy in Belgium, said that francophone Belgium’s media education framework allows authorities and educators to study children’s and young people’s digital practices across life stages. She said young people are often informed and can have positive online experiences, but that policy debates still focus too much on limiting time online rather than understanding what they actually do there.

Debrabandere said media education should start from young people’s own practices, including what they watch, whom they follow and how they access information. She pointed to influencers and content creators as an important area for media literacy, especially where young people may struggle to distinguish journalism, opinion and commercial promotion.

Daniella Esi Darlington, CEO and co-founder of Alleina AI in Ghana and a member of ITU Secretary-General’s Youth Advisory Board, said young people are among the most active internet users and are therefore often exposed to digital harms. She argued that many platforms are not designed safely enough for young users and that algorithms are built to keep people engaged for long periods.

Darlington also stressed that technology can be part of the response. She cited awareness-raising, advocacy, reporting tools, access to counsellors and AI systems that can help identify cyberbullying as examples of how digital tools can support young people when combined with human oversight.

The panel also discussed loneliness and AI companions. Darlington warned that chatbots should not replace qualified professionals when young people discuss depression, anxiety or other forms of distress. Instead, she said systems should redirect users towards appropriate support and keep humans involved.

Speakers favoured education, dialogue and co-created policy over blanket bans. Debrabandere described political moves in Belgium towards smartphone bans in schools and possible social media restrictions, while Darlington argued that banning social media or internet access would not address the root causes of harm. She said young people also use the internet for research, business, opportunities and communication.

Darlington called for stronger governance frameworks, including child-specific human rights impact assessments in AI and digital policy. She said young people, parents, schools, governments, industry and other stakeholders should be involved in designing safer digital environments.

Weber gave a practical example from therapy, explaining that video games can sometimes help rebuild dialogue between young people and families. By opening a game during a therapy session, he said adults can better understand young people’s emotions, relationships and digital experiences.

Audience interventions raised additional concerns, including neurodivergent children, cyberbullying, individualised media consumption and peer accompaniment models. A participant from Colombia’s regulator asked whether there is sufficient evidence about technology’s impact on mental health and how platforms could be made to take greater responsibility.

Carette said science often shows correlation rather than clear causality, but warned that waiting for definitive proof could delay action. He argued that the lack of transparency in platform business models and algorithms is already a sufficient reason for regulatory attention, not only for young people but for society as a whole.

The session concluded that young people’s digital well-being should be understood in context, taking account of platform design, family life, education, loneliness, social pressure and access to support. Rather than relying only on bans or addiction labels, speakers pointed to media literacy, dialogue, youth participation and stronger accountability for technology providers.

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