Artificial intelligence Archives | Page 8 of 692

AI could reorganise 27% of EU jobs, OpenAI says

OpenAI Economic Research has published a report mapping how AI could reshape the European labour market across occupations and countries.

The report extends OpenAI’s AI Jobs Transition Framework to the EU, using Eurostat employment data and the European Skills, Competences, Qualifications and Occupations taxonomy to examine where AI may create growth, increase automation pressure, or change work organisation.

The framework identifies four occupational groups: roles that may grow with AI, occupations with higher near-term automation potential, occupations likely to reorganise and occupations with less immediate change.

Applied to the EU, the framework suggests that about 12% of employment is in occupations that may grow with AI, while about 14% is in roles with relatively higher near-term automation potential. Another 27% is in occupations likely to undergo workflow and skills changes, while 47% is in roles with less immediate change.

OpenAI said country-level differences are significant. Luxembourg, Sweden and the Netherlands have larger shares of occupations that may grow with AI, while Germany, Greece and Italy have larger employment shares in occupations with higher automation potential.

The company said the framework should not be read as a job-loss forecast, but as a planning tool for policymakers, employers, educators and researchers.

OpenAI said stronger labour-market monitoring, national readiness planning and better links between skills systems and AI adoption data could help Europe prepare for occupational transitions before they appear in headline employment statistics.

Why does it matter?

The report frames AI’s labour-market impact as uneven and occupation-specific, rather than a single economy-wide shock. That matters for policymakers because reskilling, education reform and labour-market support need to be targeted where transition pressure is likely to appear. The country differences also show that AI policy in Europe may need to reflect national labour-market structures rather than EU-wide rules.

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NVIDIA and Palantir expand sovereign AI for US government

Palantir has announced a new sovereign AI capability built on NVIDIA’s open-source Nemotron models, enabling US government agencies and critical infrastructure operators to deploy, customise and continuously improve AI models within highly secure environments.

The platform combines NVIDIA Nemotron open models with Palantir’s Sovereign AI Operating System, allowing organisations to retain full control over their data, model weights and deployment infrastructure.

The system is designed for air-gapped and highly regulated environments where sensitive information cannot be connected to external networks.

Agencies will be able to train AI models using their own operational data, retain ownership of the resulting models and continuously improve performance through internal feedback loops.

The deployment is supported by NVIDIA AI Enterprise and Palantir’s Artificial Intelligence Platform (AIP), Foundry, Ontology and Apollo platforms.

NVIDIA said the initiative reflects the growing importance of open AI models for government and enterprise development, arguing that they offer greater transparency, customisation and lower deployment costs than proprietary alternatives.

The company also highlighted the role of open models in strengthening AI adoption across sectors including defence, healthcare, energy, transportation and public administration.

Why does it matter?

The announcement reflects the growing importance of sovereign AI, as governments and operators of critical infrastructure seek to deploy advanced AI systems without relying on externally hosted services or relinquishing control over sensitive data. Open models combined with secure, self-managed infrastructure offer an alternative approach for organisations with strict security and regulatory requirements.

The partnership also highlights the strategic role of open foundation models in the evolving AI ecosystem. As competition intensifies between proprietary and open AI approaches, governments are increasingly viewing customisable, locally deployable models as critical assets for national security, digital sovereignty and public-sector modernisation.

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Chief AI Officers to lead AI adoption across Australian government

Australian public service agencies are formalising the appointment of Chief AI Officers (CAIOs) to guide the safe, strategic and coordinated use of AI across government.

Under the APS AI Plan, all non-corporate Commonwealth entities must appoint a senior leader as Chief AI Officer by 30 June 2026. Corporate Commonwealth entities and Commonwealth companies are strongly encouraged to make similar appointments.

The role is intended to help agencies adopt and use AI, particularly generative AI, as the technology reshapes government operations, public service delivery and internal processes.

Chief AI Officers will complement, rather than replace, AI Accountable Officials. While Accountable Officials focus on governance, compliance and risk management, CAIOs will lead strategic adoption, organisational transformation and AI capability building.

The government said CAIOs should provide strategic leadership rather than focus primarily on technical implementation. Their responsibilities include identifying high-value AI use cases, building staff capability, championing responsible adoption and ensuring AI is deployed safely and effectively.

CAIOs will work across technology, data, policy, cybersecurity, privacy and human resources functions, while collaborating with counterparts across the Australian Public Service and the Department of Finance’s AI Delivery and Enablement team.

Chief AI Officers will also collaborate across the Australian Public Service, including with other CAIOs and the AI Delivery and Enablement function in the Department of Finance.

The government said AI should be viewed as a general-purpose capability rather than a conventional technology upgrade, reflecting its potential to transform multiple areas of public-sector work.

The CAIO role is intended to help agencies move from experimentation to more systematic and responsible adoption. It is also designed to support a whole-of-organisation view of AI risks and opportunities.

The AI Delivery and Enablement team has developed an information pack to support agencies in appointing CAIOs, along with a blog for newly appointed leaders.

A wide range of agencies have already appointed Chief AI Officers. The published list includes major departments, regulators, integrity bodies, health and research agencies, cultural institutions, security agencies and service delivery organisations.

A wide range of organisations have already appointed CAIOs, including major government departments, regulators, law enforcement bodies, research organisations and service delivery agencies such as the Department of Finance, Home Affairs, Treasury, the Australian Federal Police, Services Australia and the Australian Electoral Commission.

The appointments of Chief AI Officers reflect a broader effort to coordinate AI adoption across government while maintaining attention to safety, privacy, cybersecurity, governance and public value.

Why does it matter?

Australia’s initiative reflects a broader shift from experimental AI projects to coordinated, organisation-wide adoption across the public sector. By establishing dedicated AI leadership roles, the government is seeking to embed strategic oversight while ensuring that innovation is balanced with governance, privacy, cybersecurity and public accountability.

The creation of Chief AI Officers also highlights the growing recognition that AI adoption is an organisational transformation challenge rather than solely a technical one. As governments integrate AI into public services, dedicated leadership is becoming increasingly important to coordinate implementation, build capability and ensure AI delivers public value responsibly.

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EU calls for stronger action against cyber violence targeting girls

The Council of the European Union has adopted conclusions calling for stronger action to protect girls and young women from cyber violence, urging member states and the European Commission to reinforce prevention, enforcement, and victim support.

Findings from the European Institute for Gender Equality (EIGE) show that girls and young women are disproportionately affected by cyber violence, including online harassment, cyberstalking, non-consensual sharing of intimate images and sexist hate speech. Interviews with teenagers across the EU also suggest many believe existing prevention efforts are inadequate.

The Council called for improved access to mental health services, legal assistance and educational programmes covering digital consent, online safety and gender-responsive digital literacy. It also recommended providing parents and educators with practical guidance and training to help identify and respond to online abuse.

The Council also stressed the need for stronger enforcement of existing legislation, including the Digital Services Act and AI Act, while urging online platforms to take greater responsibility for user safety. It further called for increased investment in law enforcement resources, cross-border cooperation and research into the causes and impact of cyber violence.

Why does it matter?

The Council’s conclusions recognise cyber violence as both an online safety challenge and a barrier to gender equality and digital inclusion. By combining prevention, victim support, stronger enforcement and platform accountability, the EU is signalling that tackling online abuse requires coordinated action across governments, technology companies and civil society.

The recommendations also reinforce the EU’s broader digital governance agenda. Linking cyber violence to legislation such as the Digital Services Act and AI Act demonstrates how existing regulatory frameworks are increasingly being used to address online harms alongside technological innovation.

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Spain’s AI sandbox offers early test for biometric AI compliance

Spain’s AI regulatory sandbox is becoming an early test of how high-risk AI systems may prepare for compliance with the EU AI Act, with facial recognition among the technologies examined.

Spanish company Herta said it has completed the sandbox process for its facial-recognition video-surveillance system, BioSurveillance. The company presented the pilot as a step towards AI Act-ready deployments in public settings.

Herta describes BioSurveillance as a real-time video-surveillance system capable of detecting multiple faces, enrolling individuals during operation, identifying previously registered people and managing alerts. Its BioSurveillance NEXT product is designed for simultaneous identification in crowded and changing environments.

Spain’s AI agency, AESIA, says practical guides developed through the national AI regulatory sandbox are intended to help companies that develop or deploy high-risk AI systems prepare for their obligations under the EU AI Act. The guides provide recommendations while harmonised EU standards are still being developed.

However, sandbox participation should not be treated as approval for public facial recognition deployments. Remote biometric identification in publicly accessible spaces remains one of the most sensitive areas under the EU AI Act. It is subject to strict limits, depending on the use case, operator and context.

The case highlights how companies developing biometric AI systems are seeking early compliance pathways, while regulators face pressure to balance innovation, public safety, privacy and fundamental rights.

Why does it matter?

Facial recognition is one of the most contested areas of AI regulation because it combines public-space surveillance, biometric data processing and risks to privacy and fundamental rights. Spain’s sandbox offers an early view of how high-risk AI providers may prepare documentation, testing and compliance processes under the EU AI Act. The case also shows why compliance language must be used carefully: participation in a sandbox may support readiness, but it does not remove the legal restrictions surrounding biometric identification in public spaces.

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Malaysia adopts AI-centred digital strategy to 2030

Malaysia has launched the Malaysia Digital Action Plan 2030 (MD2030), a national roadmap that places the Ministry of Digital at the centre of efforts to achieve the country’s ambition of becoming an AI-driven nation by 2030.

Unveiled by Prime Minister Anwar Ibrahim, the strategy aims to transform Malaysia from a consumer of technology into a producer of homegrown digital innovation through a coordinated, whole-of-government approach.

The five-year plan sets national priorities across economic growth, digital public services, infrastructure, talent development, cybersecurity and AI innovation. It is built around seven strategic pillars covering government, the economy, infrastructure, talent, society, trust and security, and innovation.

MD2030 also aligns existing national initiatives, including the Malaysia Digital Economy Blueprint and the National Fourth Industrial Revolution Policy, while supporting the country’s broader economic agenda.

Implementation will be coordinated by the Ministry of Digital in collaboration with agencies including the National AI Office, the Malaysia Digital Economy Corporation, CyberSecurity Malaysia, GovTech Malaysia and MyDIGITAL Corporation.

The government said the strategy will prioritise responsible AI governance, digital trust, AI readiness, smart public services, digital inclusion and the development of domestic AI capabilities across government, business and society.

Why does it matter?

MD2030 positions AI as a core driver of Malaysia’s economic development, public-sector modernisation and long-term competitiveness. By combining AI governance, cybersecurity, digital infrastructure, skills development and innovation within a single national framework, the government is pursuing a coordinated approach to digital transformation rather than isolated technology initiatives.

The strategy also reflects intensifying regional competition to build sovereign AI capabilities. As Southeast Asian countries expand investment in AI infrastructure, talent and governance, Malaysia is seeking to strengthen its domestic innovation ecosystem while promoting trusted and responsible AI adoption across the economy.

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OECD maps AI and citizen participation

The OECD has published a report examining how AI could support citizen participation and democratic innovation while highlighting the safeguards needed for its responsible use.

The report, Artificial Intelligence and the Future of Citizen Participation, was approved and declassified by the OECD Public Governance Committee on 22 June 2026. It was produced as part of the OECD Public Governance Reviews series in collaboration with the Bertelsmann Stiftung.

The report says public participation can help governments design better policies and strengthen trust. It cites OECD trust findings showing that people who feel they have a say in government decisions are far more likely to report high trust in government.

The OECD notes that governments have long relied on digital technologies, including online platforms and civic tech tools, to expand public participation. AI represents the next stage of this evolution, with governments increasingly experimenting with tools for consultation, deliberation, communication and policy analysis.

The report is based on desk research and analysis of 50 AI use cases in participation processes from 22 OECD member and partner countries. It proposes a typology to help public officials and practitioners understand where AI tools may be useful and what challenges they may address.

Based on an analysis of 50 AI use cases from 22 OECD member and partner countries, the report proposes a typology covering nine categories of AI applications, including information development, sense-making, translation, transcription, virtual assistance, moderation, facilitation, simulation and participation architecture.

These tools can support both front-office activities, where citizens interact directly with government, and back-office activities, where public administrations design, analyse and manage processes internally.

According to the OECD, AI could make participation processes more accessible and efficient by helping governments analyse large volumes of public input, improve communication, reduce administrative costs and broaden participation.

Sense-making tools can help analyse large amounts of text submitted during consultations. Translation and transcription tools can make processes more accessible across languages and formats, while virtual assistants can help people navigate information about citizen participation opportunities.

AI can also support moderation and facilitation. The report says such tools may help prevent spam, hate speech or manipulation in online discussions, and could support live deliberation by identifying common ground or structuring debate.

However, the OECD cautions against treating AI as a simple fix for democratic challenges. It says technology alone cannot solve problems such as weak links between participation processes and actual policy decisions.

The report also highlights ethical, operational and societal risks, including algorithmic bias, opaque decision-making, hallucinations, cybersecurity threats, digital exclusion and declining public trust if AI systems are poorly designed or deployed.

The OECD also highlights the risks of inaction, noting that governments may miss valuable opportunities if they avoid AI tools even when they could be applied responsibly.

The report says governments should establish guardrails for AI use in citizen participation, including transparency, compliance with democratic values, protection of civic space, attention to data divides and low-tech alternatives for citizens with limited digital access.

It also calls for stronger enablers, including AI literacy, skills development, citizen engagement in the design and governance of AI systems, open standards where appropriate, and support for scaling successful pilots.

The OECD concludes that most public-sector use of AI in citizen participation remains experimental. It argues that lasting benefits will depend on transparent governance, human oversight and continued efforts to strengthen democratic participation beyond technology alone.

Why does it matter?

Governments are increasingly exploring AI as a way to make public participation more accessible, scalable and responsive. The OECD’s report shows that AI can support consultation, deliberation and policy analysis, but only when accompanied by safeguards that protect transparency, inclusion and democratic accountability.

The report also reinforces a broader shift in AI governance from technical capability to institutional design. By emphasising human oversight, civic participation, digital inclusion and democratic values, the OECD argues that AI should enhance, not replace, the processes that underpin public trust and democratic decision-making.

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MIT develops AI system to improve robot understanding

Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a system that helps robots interpret vague human instructions while using significantly less training data.

The approach, called Masked Inverse Reinforcement Learning (Masked IRL), uses two large language models to clarify tasks and identify the details that matter for safe robot movement.

One model expands ambiguous instructions based on user demonstrations. A second model filters out irrelevant information and highlights factors the robot should include in its motion plan.

The system can help robots understand unstated preferences, such as avoiding a laptop while delivering a coffee mug or keeping a safe distance from a person during a task.

MIT said Masked IRL correctly identified users’ unstated preferences up to 15% more often than comparable methods. Researchers also found that it required nearly five times less demonstration data to learn new tasks.

The approach was tested in simulated environments and on a real robotic arm. The robot completed tasks it had not seen during training, including moving a cup towards a person while avoiding a computer and handing over an object while staying away from nearby obstacles.

Researchers plan to make the system more dynamic by adding cameras, enabling robots to identify relevant objects and ignore distractions in their surroundings visually.

Why does it matter?

Masked IRL could make robots easier to deploy in homes, offices, factories and care environments by reducing the amount of human training needed. The system also addresses a core safety challenge in robotics: people often give vague instructions and leave important preferences unstated. Better interpretation of human intent could help robots work more safely around people, objects and changing environments.

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South Korea unveils national AI infrastructure strategy

South Korea’s Ministry of Science and ICT has announced a comprehensive whole-of-government strategy to expand the country’s AI computing infrastructure and strengthen national AI capabilities.

The strategy is built around three pillars: expanding AI computing infrastructure, developing next-generation AI models, and accelerating AI adoption across public services. To strengthen computing capacity, the government aims to secure 18,000 high-performance GPUs by the first half of 2026, with 10,000 acquired through a public-private National AI Computing Centre and another 8,000 deployed as part of a sixth national supercomputer.

To advance domestic AI development, the government plans to launch a flagship initiative provisionally named the ‘World’s Best LLM’ project. Selected AI teams will receive dedicated access to computing resources, datasets and research funding. A Global AI Challenge will also be launched to attract leading domestic and international researchers, with winners offered startup support or positions within flagship AI projects.

Talent development is another key pillar. South Korea plans to expand its AI Frontier Labs beyond New York into Europe and other regions, establish AI Transformation graduate schools through industry-university partnerships and offer competitive salaries, research funding and relocation support to attract leading international AI experts.

The third pillar focuses on deploying domestically developed AI models across public services, including healthcare, education, the legal system, public administration, disaster management and content creation.

Why does it matter?

South Korea’s strategy reflects a growing global shift towards treating AI as strategic national infrastructure rather than simply a commercial technology. By combining investments in computing capacity, foundation models, talent development and public-sector deployment, the government is pursuing a comprehensive approach to strengthening technological competitiveness and digital sovereignty.

The plan also illustrates how competition in AI increasingly extends beyond model development alone. Access to high-performance computing, skilled researchers and coordinated industrial policy is becoming just as important as algorithmic innovation, with governments playing a more active role in shaping national AI ecosystems.

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Australian audit highlights governance gaps in public-sector AI

The Australian National Audit Office has found that IP Australia’s use of AI in the patent rights process is largely effective, while calling for stronger cybersecurity governance, monitoring and strategic oversight.

Auditor-General Report No. 43 of 2025–26 examined whether IP Australia has effective arrangements to support AI adoption in the patent rights process. IP Australia administers intellectual property rights, including patents, trade marks, design rights and plant breeders’ rights.

The agency deployed its first AI tool for patent examination in 2018 and now uses four AI tools in the process. The tools are designed to provide examiners with information to support better decisions, rather than to decide patent applications themselves.

The ANAO said IP Australia has been an early adopter of AI and has progressively improved its governance arrangements. The agency has introduced an AI governance policy, risk-scaled assessment mechanisms and clearer enterprise accountability roles.

However, the audit found that strategic oversight of AI implementation and related benefits is not yet fully established. It said IP Australia’s AI inventory, committee roles and use-case ownership remain works in progress.

Monitoring and reporting were assessed as only partly effective. The ANAO said benefits have been inconsistently defined and measured, making it harder to demonstrate the ongoing effectiveness of AI tools and manage emerging risks.

The ANAO made two recommendations, urging IP Australia to review cybersecurity governance controls for AI and establish clearer risk-based monitoring and reporting arrangements. IP Australia agreed to both recommendations.

The audit said public-sector agencies should regularly reassess AI governance frameworks as they move from experimentation to wider use.

Why does it matter?

The audit shows how AI is moving from experimentation into routine public-sector decision support. IP Australia’s experience points to the benefits of AI in improving efficiency and quality, but also shows that governance must evolve as tools become embedded in official processes. Cybersecurity, accountability, monitoring and measurable benefits are becoming central to responsible AI use in government.

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