Artificial intelligence Archives | Page 32 of 708

AI is reshaping employment patterns across the US labour market

AI is increasingly influencing the structure of the US labour market, although its impact on overall employment growth remains limited so far. Evidence suggests that the impact is concentrated in specific occupational groups rather than evenly distributed across the economy.

Employment in occupations considered highly exposed to AI-driven substitution has declined in recent years, while occupations viewed as less vulnerable to automation have continued to expand. Since 2019, lower-exposure occupations such as electricians and teachers have recorded strong employment gains, while more AI-exposed occupations have experienced contraction.

The divergence between highly exposed and less exposed occupations has widened further since the emergence of generative AI tools in late 2022. Analysis indicates a growing divergence in employment trends, with job reallocation increasingly linked to technological exposure and automation potential.

Despite these shifts in employment patterns, wage growth has so far shown little evidence of significant variation based on AI exposure. Economists note that the full impact of AI on earnings and inequality may become more visible as adoption deepens and labour markets adjust over time.

Why does it matter?

The findings suggest that AI’s impact on the labour market may be emerging through occupational reallocation rather than widespread job losses. Instead of reducing total employment, AI appears to be changing demand for specific types of work, with occupations that rely heavily on routine cognitive tasks facing greater pressure than jobs requiring physical, interpersonal or complex problem-solving skills.

The trend has important implications for workforce development and economic policy. If AI continues to reshape demand across occupations, governments, employers and educational institutions may need to adapt training programmes, reskilling initiatives and career pathways to help workers transition into roles that complement rather than compete with increasingly capable AI systems. The longer-term effects on wages, productivity and inequality remain uncertain and will depend on how rapidly AI adoption spreads throughout the economy.

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Oxford researchers develop AI tool to map hidden effects of high blood pressure

Researchers led by the University of Oxford have developed an AI tool called ‘HyperScore’ that could help doctors better understand how high blood pressure affects different organs and individuals in different ways. The approach could support more personalised treatment strategies in the future.

Using the AI tool, researchers identified six distinct patterns of hypertension-related disease by analysing hundreds of measurements, including cardiac imaging, brain MRI scans, blood tests and assessments of the kidneys, liver and vascular system.

The study found that individuals with higher HyperScores faced a greater risk of future cardiovascular events, even when conventional blood pressure measurements did not fully capture that risk. Changes detected through brain MRI imaging emerged as some of the strongest indicators of hypertension-related organ damage.

The researchers analysed data from more than 27,000 participants in the UK Biobank and validated their findings in an additional cohort of more than 5,500 individuals in the US. The researchers cautioned that the approach remains at an early stage and is not yet ready for routine clinical use in the UK.

Why does it matter?

High blood pressure is one of the world’s leading risk factors for heart disease, stroke and other chronic conditions, yet patients with similar blood pressure readings can experience very different health outcomes. The study suggests that AI may help identify hidden patterns of organ damage that are not captured by conventional measurements, potentially enabling more accurate risk assessment and personalised treatment strategies.

The research also highlights the growing role of AI in precision medicine. By combining imaging, laboratory data and clinical information, AI systems may help clinicians move beyond one-size-fits-all approaches to disease management. Although HyperScore remains at an early research stage, the findings demonstrate how AI could support earlier intervention and more targeted care for patients with complex cardiovascular risks.

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Norway restricts generative AI use in primary schools

Norway is introducing new national guidance that significantly restricts the use of generative AI in primary education as part of a broader effort to strengthen foundational learning outcomes. From the upcoming school year, pupils in grades 1–7 will generally not be permitted to use generative AI tools in their schoolwork.

The approach reflects concerns over declining foundational skills, with international assessments indicating a drop in reading and numeracy levels among Norwegian students. Policymakers have linked the decision to evidence suggesting that early and uncritical reliance on generative AI could interfere with the development of essential literacy, numeracy and problem-solving skills.

In secondary education, AI will be introduced gradually, with schools expected to ensure that teachers have the necessary skills and training before students begin using the technology. Full integration is expected at the upper secondary level, where AI is seen as part of preparation for further education and the labour market.

Authorities emphasised that AI may still be used in specific circumstances, particularly to support students with individual learning needs or those requiring tailored educational assistance. The policy will be reviewed and adjusted over time, with a focus on strengthening teacher training and ensuring responsible use of the technology across the education system.

Why does it matter?

The decision reflects a growing international debate over the role of generative AI in education. While AI tools can support learning, creativity and personalised instruction, educators and policymakers are increasingly concerned that early dependence on such technologies could weaken the development of core skills that students need before they can use AI critically and effectively.

Norway’s approach also highlights a broader shift towards phased AI adoption in schools. Rather than focusing solely on access to technology, the policy places teacher competence, pedagogical goals and student development at the centre of implementation. The outcome may influence similar discussions in other countries seeking to balance digital innovation with educational quality and learning outcomes.

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Indonesia plans AI integration across major government programmes

Indonesia plans to integrate AI into major government programmes, including its flagship free meals initiative valued at approximately $15 billion, under a draft presidential regulation awaiting approval from President Prabowo Subianto.

The draft establishes a roadmap for AI adoption across ministries and regional governments between 2026 and 2029. It aims to improve economic growth and strengthen Indonesia’s competitiveness in AI at both regional and global levels.

Under the proposals, AI would support the free meals programme by helping design local menus, monitor food safety and kitchen hygiene, forecast demand, detect irregularities and integrate health data for early-warning systems. AI would also support free health screenings and tuberculosis testing.

The draft also proposes the creation of a sovereign AI fund, fiscal incentives for researchers and safeguards to address risks such as biometric misuse, intellectual property violations and deepfakes. Experts cautioned that significant infrastructure gaps, limited digital skills and uneven technological capacity could pose challenges to implementation, which remains at an early stage.

Why does it matter?

The proposal illustrates how governments are increasingly seeking to integrate AI into core public-service delivery rather than limiting its use to pilot projects or administrative functions. Applying AI to areas such as nutrition programmes, healthcare screening and public-sector operations could improve efficiency, resource allocation and service delivery for millions of citizens.

The initiative also highlights the challenges facing emerging economies as they pursue AI-driven development. While Indonesia is seeking to build domestic AI capacity through funding mechanisms and incentives, successful implementation will depend on investments in digital infrastructure, technical expertise and governance frameworks capable of addressing risks such as deepfakes, privacy concerns and misuse of biometric data.

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Cybercriminals exploit World Cup hype with phishing schemes

Cybercriminals are exploiting World Cup interest through fake streaming platforms, phishing campaigns, counterfeit online stores and betting-related scams, according to Kaspersky researchers.

The security company said it had identified more than 336 fake websites designed to imitate official World Cup pages. Many scams target fans looking for cheaper tickets, free match streams or tournament merchandise.

Some fake streaming sites ask users to register and pay for access to matches, sometimes using cryptocurrency. Others collect personal data that can later be used in further phishing attacks.

Kaspersky also identified counterfeit merchandise shops, fraudulent betting schemes and phishing emails promoting fake offers or paid predictions. Some scams rely on urgency, limited-time claims and professional-looking websites to pressure users into sharing payment or personal information.

The company warned that AI-generated websites and more polished scam designs are making fraudulent pages harder to distinguish from legitimate services during high-demand events.

Kaspersky advised fans to use official sources, check website addresses carefully and avoid offers that promise free access, unrealistic discounts or guaranteed betting results.

Why does it matter?

Major sporting events create ideal conditions for online fraud because demand, urgency and emotion are all high. World Cup scams show how criminals combine phishing, fake e-commerce, streaming fraud and social engineering to steal money and personal data. The use of polished or AI-generated websites also reflects a wider challenge for consumer protection: scams are becoming easier to create at scale and harder for users to recognise.

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Malaysia moves to strengthen laws against AI-enabled crimes

Malaysia is moving to strengthen its legal framework to address AI-enabled offences, including deepfakes, identity impersonation and AI-generated child sexual abuse material, according to Digital Minister Gobind Singh Deo.

Speaking in the Dewan Rakyat, Gobind said Malaysia already has legal protections in several areas, particularly those involving children, but that the country’s regulatory framework must evolve to keep pace with emerging AI-related risks, especially those affecting young people.

The minister said the government is pursuing a two-pronged strategy that combines safety-by-design measures during AI development with stronger enforcement mechanisms when AI-generated content violates existing laws.

Gobind added that the government is consulting academics, religious leaders and other stakeholders as part of its review process to ensure future regulations remain effective as AI technologies continue to evolve.

Why does it matter?

The initiative reflects a growing challenge facing governments worldwide: adapting legal systems to address harms created or amplified by AI technologies. Deepfakes, synthetic identities and AI-generated abuse material are creating new enforcement challenges that often do not fit neatly within existing legal frameworks designed for earlier digital technologies.

Malaysia’s approach also highlights an emerging policy trend that combines prevention and enforcement. Rather than relying solely on criminal penalties, governments are increasingly exploring safety-by-design requirements, risk management measures and stakeholder consultation to reduce harm before it occurs. The outcome of Malaysia’s review could influence how other countries in the region approach AI governance, online safety and digital rights.

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EU selects EUROPA consortium to build multilingual frontier AI model

The European Commission has selected the EUROPA consortium, led by Italian company Domyn, as the winner of its Frontier AI Grand Challenge. The project will develop a large-scale open-source AI model capable of operating across all 24 official languages of the EU.

Launched in February 2026, the competition challenged European AI innovators to propose a frontier model exceeding 400 billion parameters, a scale typically associated with some of the world’s most advanced AI systems.

The Commission said the initiative demonstrates Europe’s capacity to develop advanced AI using its domestic talent, infrastructure and industrial capabilities.

The EUROPA model will be openly accessible and designed to support businesses, researchers, public institutions and developers across the EU. By covering every official EU language, the project aims to address Europe’s linguistic diversity while expanding access to advanced AI technologies.

The Commission views the project as a strategic step towards greater technological sovereignty, strengthening Europe’s AI ecosystem while promoting openness, trust and European values in AI development.

Why does it matter?

The EUROPA project reflects Europe’s growing determination to develop advanced AI capabilities within its own technological ecosystem. As AI becomes increasingly important for economic competitiveness, public services and scientific research, access to large-scale models is emerging as a strategic capability alongside semiconductors, cloud infrastructure and high-performance computing.

The initiative is also notable for its focus on linguistic diversity and open access. By developing a frontier model capable of operating across all 24 official EU languages and making it openly available, the project aims to broaden participation in AI innovation while reducing dependence on a small number of predominantly US-based providers. Its success could become an important test of Europe’s ability to combine technological sovereignty with open and collaborative AI development.

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Beijing publishing forum calls for AI copyright standards

Publishing leaders and professionals have called for clearer copyright rules and industry standards for the use of AI in publishing, following discussions at the 2026 International Publishing Forum in Beijing.

The forum, held during the Beijing International Book Fair, brought together nearly 300 publishing executives and professionals from 26 countries and regions. It was jointly organised by the Publishers Association of China and the International Publishers Association.

Participants discussed how AI is reshaping publishing workflows, content production and distribution. They said AI should support, rather than replace, human creativity, with human-machine collaboration helping publishers improve efficiency and expand access to high-quality content.

Speakers also warned that the industry must protect intellectual property, preserve the authenticity and credibility of content, and support linguistic diversity as AI-generated material becomes more widely used.

Participants called for international cooperation on standards and copyright frameworks for AI applications in publishing. They said such rules should define rights and responsibilities, support fair compensation and ensure source traceability.

The discussions reflect growing concern in the publishing sector over how AI systems use copyrighted works, how original creators are recognised, and how publishers can maintain trust in content as synthetic media and automated production tools spread.

Why does it matter?

The forum highlights a central concern for creative industries: AI can improve publishing workflows and content distribution, but it also raises unresolved questions about copyright, attribution, compensation and authenticity. For publishers and authors, clear standards on source traceability and rights could become essential as AI-generated or AI-assisted content becomes more common.

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Los Angeles AI arts museum Dataland opens with Google Cloud support

Dataland, a Los Angeles museum dedicated to AI-based art, has opened to the public with Google serving as a technology and creative collaborator.

The museum was co-founded by media artist Refik Anadol and Efsun Erkılıç and is located at The Grand LA in downtown Los Angeles. Google says the 25,000-square-foot space is designed as an interactive environment where data, machine learning and sensory experiences form part of the artwork.

Its inaugural exhibition, ‘Machine Dreams: Rainforest’, uses Anadol’s Large Nature Model, an AI system trained on environmental datasets, to transform natural-world data into large-scale generative visuals.

Google Cloud provides infrastructure for the museum’s real-time image generation, soundscapes, scent augmentation and interactive visitor experiences. Google says the system uses tools including Gemini, diffusion models and generative adversarial networks.

The project builds on a decade of collaboration between Google and Anadol, including work using LA Philharmonic archives, Google Quantum AI data, planetary datasets and the ‘Machine Dreams: Biophilia’ installation at Google’s Mountain View campus.

Google Arts & Culture is also supporting the Dataland AI Artist Residency, a six-month programme for four artists. The residency will provide grants, mentorship from Refik Anadol Studio and access to Google Cloud tools and machine learning models.

Why does it matter?

Dataland shows how AI art is moving from experimental installations into permanent cultural infrastructure. It also highlights the role of cloud providers and large AI platforms in shaping creative production, exhibition design and access to machine-learning tools. For cultural institutions, the project raises broader questions about authorship, data provenance, sustainability, audience interaction and the dependence of new creative formats on private technology infrastructure.

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EPO places AI and quality at the centre of SACEPO discussions

The European Patent Office used the 58th meeting of the Standing Advisory Committee before the EPO to discuss patent quality, AI and the digital transformation of the European patent system.

The annual Main SACEPO meeting brought together users of the patent system to review the EPO’s Quality Action Plan 2026, legal changes, the Unitary Patent system and activities of the EPO Observatory and IP Lab.

A key focus was the use of AI to support the patent-granting process. The EPO said AI tools are intended to help examiners improve efficiency, consistency and completeness, while all patent decisions remain under human responsibility.

Participants also discussed progress on quality measures, stakeholder feedback and continued investment in examiner expertise, quality assurance and user engagement.

The meeting reviewed the EPO’s transition to a paperless patent-granting process, planned for April 2027, as well as updates to MyEPO services and DOCX filing.

Discussions also covered recent legal changes, the operational development of the Unitary Patent system, patent validation agreements, implementation of the WIPO treaty on genetic resources and traditional knowledge, and new activities from the EPO Observatory on Patents and Technology.

Why does it matter?

The meeting shows how AI is becoming part of the everyday infrastructure of patent administration. For patent offices, AI can support searches, classification, workflows and consistency, but legal certainty still depends on human responsibility and procedural safeguards. The EPO’s approach also reflects a wider shift towards fully digital public services in intellectual property, where automation, quality control and user trust need to develop together.

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