Artificial intelligence Archives | Page 8 of 650

Google outlines AI-driven measures against online scams and fraud

Google has outlined new and existing measures to tackle online scams and fraud ahead of the second EMEA Anti-Scams and Fraud Summit, hosted by the Google Safety Engineering Centre in Zurich.

The company said the summit brings together representatives from governments, technology companies, consumer groups and academia to discuss collective responses to increasingly sophisticated scams. Google said its approach combines AI-driven protections across its products with wider cooperation involving industry and public authorities.

Google highlighted the use of AI-powered systems in services including Gmail, Chrome, Search, Ads and Phone by Google. The company said Gmail blocks more than 99.9% of spam, phishing and malware, while Search filters out hundreds of millions of spam-related pages daily. It also said its systems caught more than 99% of policy-violating ads before they reached users in 2025.

User-facing tools are also part of the company’s anti-scam strategy. Google pointed to Security Checkup, Passkeys, 2-Step Verification, Circle to Search and Google Lens as tools that can help users strengthen account protection and verify suspicious messages or content.

The company also highlighted public awareness and education initiatives, including Be Scam Ready, a game-based programme that uses simulated scam scenarios to help users recognise common tactics. Google said a previous Google.org commitment of $5 million is supporting anti-scam initiatives in Europe and the Middle East, including work by the Internet Society and Oxford Information Labs.

Google also referred to cooperation through the Global Signal Exchange, a threat-intelligence sharing platform for scams and fraud. As a founding partner, Google said it both contributes to and draws from the platform, which now stores more than 1.2 billion signals used to identify and disrupt criminal activity.

The company said it also works with law enforcement agencies, including the UK’s National Crime Agency, and participates in the Industry Accord Against Online Scams and Fraud. Google also pointed to legal actions against scam operations and botnets, including cases involving Lighthouse and BadBox.

Why does it matter?

Online scams are increasingly industrialised, cross-platform and supported by AI-enabled tactics, making them difficult to address through product-level security alone. Google’s approach shows how major technology companies are combining automated detection, user education, threat-intelligence sharing and law enforcement cooperation to respond to fraud. The wider policy issue is how much responsibility large platforms should bear for detecting and disrupting scams before they reach users.

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Kazakhstan warns AI could displace up to 400,000 jobs

Kazakhstan’s Ministry of Labour and Social Protection has warned that widespread AI adoption could affect between 300,000 and 400,000 jobs over the next decade, highlighting concerns over structural shifts in the labour market.

First Vice-Minister Yerbol Tuyakbayev said the Workforce Development Centre is studying the potential impact of AI on the labour market. He said possible reductions could affect auxiliary and administrative roles, including accounting and some legal positions where tasks do not require direct human involvement.

At the same time, labour officials said demand remains strong for skilled technical and manual professions. The ministry pointed to current vacancies on the Enbek.kz platform and noted continued shortages in occupations requiring specialised practical expertise.

In response, the government has expanded retraining initiatives to help workers move into new roles. Tuyakbayev said around 186,000 people have already completed retraining programmes this year, including through regional initiatives and local centres such as JOLTAP in Astana.

Officials stressed that future employability and wages will depend heavily on qualification levels, as AI continues to reshape job structures and skills requirements across the economy.

Why does it matter?

Kazakhstan’s warning shows how governments are starting to treat AI as a labour-market transition issue, not only a productivity tool. The estimate points to potential pressure on routine administrative and professional roles, while also highlighting the need for retraining systems that can move workers into higher-demand technical and skilled occupations.

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Microsoft MDASH agentic AI security system tops vulnerability discovery benchmarks

Microsoft has described a multi-model agentic AI security system, codenamed MDASH, designed to support vulnerability discovery and cybersecurity research across complex codebases.

According to Microsoft, the system helped researchers identify 16 vulnerabilities across Windows networking and authentication components, including issues in the Windows TCP/IP stack, IKEv2 services, DNS handling and Netlogon processes. Several of the vulnerabilities were reachable over networks without authentication, the company said.

MDASH was developed by Microsoft’s Autonomous Code Security team and combines more than 100 specialised AI agents with an ensemble of frontier and distilled AI models. The system is structured as a multi-stage pipeline covering code preparation, scanning, validation, deduplication and proof generation.

The publication says the system identified remote code execution flaws, denial-of-service issues, information disclosure vulnerabilities and security feature bypasses. Microsoft also described the use of specialised auditor, debater and prover agents designed to analyse vulnerabilities across multiple files and code paths.

Microsoft said MDASH uses plugins and domain-specific knowledge to support validation and proof-of-concept generation, allowing security experts to add context that foundation models may not capture on their own.

The company also reported benchmark results from internal and public tests. It said MDASH identified all 21 deliberately inserted vulnerabilities in a private test driver with zero false positives in that run, achieved 96% recall against five years of confirmed Microsoft Security Response Center cases in clfs.sys and 100% in tcpip.sys, and scored 88.45% on the public CyberGym benchmark.

Microsoft said the system is already being used by its security engineering teams and is being tested with a small group of customers through a limited private preview.

Why does it matter?

MDASH shows how agentic AI is moving into high-value cybersecurity tasks such as vulnerability discovery, validation and proof generation. If systems like this can reliably reduce false positives and help researchers find exploitable flaws earlier, they could improve defensive security at scale. The same development also raises governance questions around access, oversight and dual-use risk, since tools capable of finding and proving vulnerabilities may be valuable to both defenders and attackers.

The company also discussed broader implications for AI-assisted cybersecurity operations, including the use of agentic AI systems for vulnerability discovery, validation, and remediation workflows. Microsoft stated that the system is currently being tested internally and through a limited private preview involving selected customers.

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Practice Note on AI issued by Australia’s Supreme Court of Victoria

Australia’s Supreme Court of Victoria has issued a Practice Note for court users and Judicial Guidelines for judicial officers on the use of AI, setting out how the technology may be used in court processes while preserving accuracy, privacy, accountability and fairness.

The Practice Note recognises that AI may enhance access to justice, but warns court users to understand the risks when using AI to prepare court documents. It states that users remain responsible for the content of documents they file, whether or not AI has been used.

Court users are also warned that filing documents containing inaccuracies could lead to costs orders. The Practice Note outlines privacy issues linked to different types of AI tools and notes possible sanctions for legal practitioners who rely on unverified AI outputs.

The Judicial Guidelines state that generative AI must not be used for judicial decision-making. Court-approved AI tools may, however, assist judicial officers and court staff with supportive tasks such as organising and locating case materials, producing summaries and chronologies, aiding legal research and proofreading.

The guidelines stress that such uses are not a substitute for reading or listening to evidence and submissions, or for fact-finding where required in judicial decision-making. Judicial officers must consider each matter before them and exercise their own judgement in reaching decisions and giving reasons where appropriate.

The Court said the new documents build on earlier AI guidelines developed in 2024 and respond to a review by the Victorian Law Reform Commission. Chief Justice Richard Niall said the Practice Note and Judicial Guidelines would help mitigate actual and perceived risks of AI use.

Niall said AI should be ‘an aid to, not a replacement of, judicial decision-making’, adding that the Court would continue adapting its practice without sacrificing impartiality, privacy, accountability and fairness.

Why does it matter?

The guidance shows how courts are beginning to define practical limits for AI use without banning it entirely. By allowing supportive uses while excluding generative AI from judicial decision-making, Victoria’s Supreme Court is drawing a line between administrative assistance and the exercise of judicial judgement, a distinction likely to become increasingly important as AI tools enter legal practice.

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South Africa and China expand digital education ties

South Africa and China have agreed on measures to deepen cooperation in digital education, technical skills development and student mobility following bilateral talks at the World Digital Education Conference in Hangzhou.

The talks brought together South Africa’s Minister of Higher Education and Training, Buti Manamela, and China’s Vice Minister of Education, Xu Qingsen. According to SAnews, the meeting produced a framework for stronger cooperation in areas including AI, vocational training and industry-linked education pathways.

Planned measures include a structured cooperation framework on AI in education and digital transformation, as well as a Joint Technical Working Group to oversee the rollout of China-South Africa Vocational and Technical Centres across all nine South African provinces.

Both countries also committed to expanding technical and vocational education and training cooperation, aligning programmes with industrial sectors such as AI, robotics, renewable energy and advanced manufacturing. Scholarship programmes are also expected to be more closely linked to South Africa’s industrial priorities, including AI, engineering, green energy and the development of TVET lecturers.

The cooperation will include expanded postgraduate study opportunities and joint research initiatives. Future short-term training programmes are expected to focus on AI governance, digital learning systems, industrial policy and digital public infrastructure, to strengthen institutional capacity across government and the post-school education sector.

Officials also highlighted the goal of linking education more directly with employment. Existing cooperation includes a partnership with Beijing Polytechnic College, where South African TVET students completed specialised training in new energy vehicles and hybrid technologies, with Chinese automaker BYD committing to provide internships and employment opportunities.

Why does it matter?

The cooperation links digital education with industrial policy, skills development and employment pathways, rather than treating AI education as a standalone technology issue. By focusing on vocational centres, scholarships, AI governance and digital public infrastructure, South Africa and China are positioning education cooperation as part of broader workforce and institutional capacity-building for the digital economy.

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OpenAI sued over alleged ChatGPT role in Florida State University shooting

The family of a victim killed in the April 2025 Florida State University shooting has filed a federal lawsuit in Florida against OpenAI, alleging that ChatGPT enabled the attack. The lawsuit was filed on Sunday by Vandana Joshi, the widow of Tiru Chabba, who was killed alongside university dining director Robert Morales.

The complaint states that the accused shooter, Phoenix Ikner, engaged in extensive conversations with ChatGPT months before leading up to the incident. According to the suit, those exchanges included images and discussions about firearms he had acquired, ideological material, ideological far-right beliefs, and possible outcomes of violent attacks.

The chatbot is further accused of providing contextual information about campus activity and commenting on factors that could increase public attention in violent incidents. This is indicated by the fact that at one point, ChatGPT said, ‘if children are involved, even 2-3 victims can draw more attention’. The filing also claims Ikner asked about legal consequences and planning considerations shortly before the attack.

The lawsuit contends that OpenAI failed to identify escalating risk indicators within the conversations and did not adequately prevent harmful guidance. It argues the system ‘failed to connect the dots’ despite Ikner’s repeated questions about suicide, terrorism and mass shootings.

OpenAI has rejected responsibility for the attack, claiming its platform is not to blame. Company spokesperson Drew Pusateri said ChatGPT generated factual responses that could be found broadly across publicly available information and did not encourage or promote illegal activity. He also stated that OpenAI continues to strengthen safeguards to identify harmful intent, reduce misuse and respond appropriately when safety risks arise.

Joshi’s complaint argues that the system reinforced the shooter’s beliefs and failed to interrupt conversations involving violent ideation. The filing alleges the ChatGPT inflamed, validated and endorsed delusional thinking and contributed to planning discussions while ‘convincing him that violent acts can be required to bring about change’.

The lawsuit forms part of a broader wave of litigation involving AI systems and alleged harm. OpenAI is already facing separate lawsuits linked to incidents involving violence and suicide, raising wider questions about safeguards and user protection

Florida’s Attorney General James Uthmeier announced a criminal investigation into OpenAI and ChatGPT following a review of chat logs connected to the case. Uthmeier said in a statement that ‘If ChatGPT is a person it would be facing charges for murder’.

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Wikimedia Foundation joins Digital Public Goods Alliance

The Wikimedia Foundation has joined the Digital Public Goods Alliance, a UN-endorsed multi-stakeholder initiative that promotes open-source software, datasets, AI models, and content as digital public goods.

The foundation, which operates Wikipedia and other Wikimedia projects, said the membership reflects its commitment to open knowledge as a public good that remains accessible, rights-based, and governed in the public interest.

Jan Gerlach, Public Policy Director at the Wikimedia Foundation, said: ‘ ‘Wikipedia, Wikidata, and other Wikimedia projects show how hundreds of thousands of people working together across borders can create and maintain free and open knowledge infrastructure built in the public interest. As the host of these projects, we look forward to sharing our learnings and collaborating more closely with fellow DPGA members who share our vision of an internet that protects and promotes community-led spaces.’

The foundation joins DPGA members, including UNESCO, UNICEF, GitHub, the Inter-American Development Bank, and several governments. As part of its membership, it will report activities linked to digital public goods and the sustainable development goals through the annual State of the DPG Ecosystem Report and the DPGA Roadmap.

Planned activities include strengthening Wikimedia Cloud Services, which supports volunteer-developed tools used across Wikimedia projects. The foundation said around 30% of all edits to Wikimedia projects rely on tools hosted on the service, and that future work will focus on scalability, security, usability, contributor access, and innovation.

The Wikimedia Foundation also plans to continue advocating for open knowledge infrastructure in digital policy, including open-source-first approaches, responsible use of open data for public interest AI, information integrity, and protection of digital public goods.

The move follows the DPGA’s 2025 recognition of Wikipedia and Wikidata as digital public goods. It also builds on the foundation’s 2024 Global Digital Compact advocacy, which called for protecting online public-interest projects and for AI to support people rather than replace them.

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UN invites leaders for AI governance dialogue

The co-chairs of the first Global Dialogue on AI Governance have invited member states and stakeholders to express interest in co-chairing thematic discussions during the meeting, which will take place in Geneva on 6–7 July 2026 alongside the ITU AI for Good Global Summit under UN General Assembly resolution 79/325.

The discussions will be organised around four themes: the social, economic, ethical, cultural, linguistic, and technical implications of AI; bridging AI divides through capacity-building and digital access; safe, secure, and trustworthy AI, including interoperability between governance approaches; and human rights issues such as transparency, accountability, and human oversight.

Each thematic session will be jointly chaired by one member state and one stakeholder representative, with the aim of fostering multistakeholder exchanges on experiences, best practices, and policy cooperation. Governments are asked to nominate high-level representatives, while stakeholders are encouraged to nominate senior experts relevant to the selected theme.

Selected co-chairs will support dialogue design, facilitate exchanges, and contribute to inclusive and balanced participation.

According to the UN, the initiative aims to bring together diverse perspectives from governments, industry, academia and civil society. The process is intended to strengthen collaboration and inform future AI governance approaches.

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AI working group revived by New Environment Canterbury of New Zealand

Environment Canterbury, the regional council for Canterbury in New Zealand, has approved the re-establishment of its Artificial Intelligenc e Working Group to examine how AI is being used to analyse data, support decision-making, and serve local communities.

Canterbury Regional Councillors approved the group at a Regional Delivery Committee meeting. The working group will provide an informal forum for councillors to explore AI applications, analyse trends, share knowledge, promote digital democracy, and develop informed views on the technology.

The Artificial Intelligence Working Group will be chaired by Councillor Joe Davies and is expected to meet up to four times a year. Workshops will generally be open to the public and will give local developers and AI start-ups opportunities to present their work.

Davies said the decision reflects a proactive approach to governance as AI becomes part of everyday public sector work. He stated: ‘AI is already part of everyday public sector work, and by leaning into these conversations now, we’re making sure we understand what’s happening, what’s coming, and what good governance looks like in this space.’

The group builds on work undertaken during the previous triennium, including discussions with external experts on AI use, regulation, and risk.

Insights from the working group will be reported back to the Regional Delivery Committee to inform future council discussions. Davies said the initiative would help Canterbury engage with technological change openly and responsibly rather than simply reacting to it.

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G7 working group advances cybersecurity approach for AI systems

The German Federal Office for Information Security published guidance developed by the G7 Cybersecurity Working Group outlining elements for a Software Bill of Materials for AI. The document aims to support both public and private sector stakeholders in improving transparency in AI systems.

The guidance builds on a shared G7 vision introduced in 2025 and focuses on strengthening cybersecurity throughout the AI supply chain. It sets out baseline components that should be included in an AI SBOM to better track and understand system dependencies.

The document outlines seven baseline building blocks that should form part of an AI Software Bill of Materials (SBOM for AI), designed to improve visibility into how AI systems are built and how their components interact across the supply chain.

At the foundation is a Metadata cluster, which records information about the SBOM itself, including who created it, which tools and formats were used, when it was generated, and how software dependencies relate to one another.

The framework then moves to System Level Properties, covering the AI system as a whole. This includes the system’s components, producers, data flows, intended application areas, and the processing of information between internal and external services.

A dedicated Models cluster focuses on the AI models embedded within the system, documenting details such as model identifiers, versions, architectures, training methods, limitations, licenses, and dependencies. The goal is to make the origins and characteristics of models easier to trace and assess.

The document also introduces a Dataset Properties cluster to improve transparency into the data used throughout the AI lifecycle. It captures dataset provenance, content, statistical properties, sensitivity levels, licensing, and the tools used to create or modify datasets.

Beyond software and data, the framework includes an Infrastructure cluster that maps the software and hardware dependencies required to run AI systems, including links to hardware bills of materials where relevant.

Cybersecurity considerations are grouped under Security Properties, which document implemented safeguards such as encryption, access controls, adversarial robustness measures, compliance frameworks, and vulnerability references.

Finally, the framework proposes a Key Performance Indicators cluster that includes metrics related to both security and operational performance, including robustness, uptime, latency, and incident response indicators.

According to the paper, the objective is to provide practical direction that organisations can adopt to enhance visibility and manage risks linked to AI technologies. The framework is intended to support more secure development and deployment practices.

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