Artificial intelligence Archives | Page 13 of 678

Google highlights rising online scam threats

Google has warned that online scams remain a major global challenge, citing estimates that fraud losses could reach nearly $580 billion in 2025.

In its latest fraud and scams advisory, the company said phishing attacks are becoming more sophisticated, with criminals using adversary-in-the-middle techniques and QR code phishing, also known as quishing, to steal credentials and bypass security measures.

The advisory also highlighted risks linked to cryptocurrency investment scams, malicious finance applications and police impersonation schemes. According to Google, scammers are using AI, social engineering and trusted digital services to deceive users, obtain money and collect sensitive information.

Google said its Trust & Safety teams are using AI tools, predictive analytics and policy enforcement to detect and disrupt fraudulent activity across its services. The company also pointed to measures such as stronger protections for session cookies, enforcement against deceptive crypto ads, monitoring of post-installation app behaviour and developer identity verification for apps installed on certified Android devices.

The company urged users to be cautious of unsolicited communications, unrealistic investment promises, unexpected QR codes and requests for personal or financial information.

Why does it matter?

The advisory shows how online fraud is becoming a cross-platform governance problem rather than a narrow cybersecurity issue. Scams now rely on trusted cloud services, mobile apps, messaging platforms, crypto infrastructure and impersonation of public authorities. That creates pressure on major technology companies to strengthen detection, app accountability and policy enforcement, while raising broader questions about consumer protection, platform responsibility and digital trust.

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UK to test AI legal assistants to help reduce court delays

The UK government will develop and test AI legal assistants as part of a broader set of technology initiatives aimed at reducing court delays and improving the efficiency of the justice system. The Ministry of Justice said the tools will support routine casework, including research and case analysis, before any possible use in the Crown Court.

The AI legal assistants will be developed in collaboration with legal professionals and AI developers, with initial testing taking place in controlled environments. The government said the trials will help establish standards for the safe and ethical use of AI in legal settings and ensure any future systems meet the expectations of judges and legal practitioners before wider deployment.

Judges are also preparing to test an AI tool designed to identify trial-ready cases and group similar hearings together. The government said the tool is intended to better use judicial, prosecutorial, and court resources, helping cases move more quickly for victims.

The announcement also covers Justice Transcribe, an AI tool now available to every probation officer in England and Wales. The tool records and transcribes conversations with offenders, reducing the administrative burden associated with transferring handwritten notes into digital systems.

According to the government, Justice Transcribe could free up the equivalent of 18,750 days annually, enabling probation officers to spend more time supervising offenders and supporting efforts to reduce reoffending. A similar transcription tool is being trialled in Immigration and Asylum Tribunals to support judges with case notes and reduce administrative pressure.

The projects form part of the Prime Minister’s AI Exemplars programme, which aims to accelerate the adoption of AI across public services. The government also pointed to AI Growth Labs, secure testing environments intended to help the UK lawtech sector develop and refine AI products before bringing them to market.

Why does it matter?

Justice systems around the world are exploring how AI can help address growing caseloads, administrative burdens and resource constraints. Applications such as legal research assistance, transcription services and case management tools have the potential to improve efficiency while allowing legal professionals to focus on higher-value tasks.

At the same time, the use of AI in judicial and legal contexts raises important questions about accountability, transparency, fairness and human oversight. The UK’s emphasis on controlled testing and ethical safeguards reflects growing recognition that AI deployment in the justice sector requires robust governance alongside technological innovation.

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EDIH Summit 2026 to focus on Europe’s AI implementation challenge

The EDIH Summit 2026 will take place in Brussels on 9 and 10 June, bringing together the European Digital Innovation Hubs (EDIH) network, EU institutions, Member States, AI infrastructures initiatives and innovation stakeholders. The event will focus on how Europe’s AI innovation ecosystem functions in practice.

The summit comes as the European Union increasingly shifts its focus from AI policymaking towards implementation and adoption. With the AI Act in force, the AI Continent Action Plan adopted, and the Apply AI Strategy underway, organisers say attention is turning to whether SMEs and public administrations can access infrastructure, expertise and practical support needed to adopt AI effectively.

Sessions will explore how European Digital Innovation Hubs connect organisations with other components of the EU AI innovation ecosystem, including AI Factories, Testing and Experimentation Facilities (TEFs) and regulatory sandboxes. Discussions will also address common tools, assessment frameworks, and approaches that can be scaled across regions and sectors.

The programme will also examine how support structures may need to evolve as generative and agentic AI reshape organisational requirements and expectations. The EDIH Summit will also examine the evolving role of EDIHs as AI experience centres, acting not only as access points but as guides within a changing technological and regulatory landscape.

Organisers said the summit is designed to encourage practical exchange, knowledge sharing and actionable outcomes. European Digital Innovation Hubs will be able to compare approaches, identify shared challenges, and contribute to discussions that will shape the network’s priorities for the year ahead.

Why does it matter?

As the European Union moves from developing AI regulations to encouraging widespread adoption, questions increasingly focus on implementation rather than policy design. Many SMEs and public administrations continue to face challenges accessing expertise, testing facilities, funding and trusted guidance for deploying AI solutions.

The EDIH Summit reflects the EU’s broader effort to build a connected AI ecosystem that links businesses and public-sector organisations with technical infrastructure, innovation support services and regulatory guidance. The discussions may help shape how Europe translates its AI ambitions into practical adoption and economic impact.

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Apple unveils next-generation Siri AI and expanded child safety features

Apple has unveiled the next generation of Apple Intelligence at WWDC26, introducing a significantly upgraded Siri designed to provide deeper personal context awareness, broader app integration and more advanced conversational capabilities.

The new assistant can search across messages, emails and photos, answer questions about on-screen content and access web information to provide more up-to-date responses while maintaining Apple’s privacy-focused approach.

Alongside its AI announcements, Apple announced major updates to parental controls and Screen Time features. Parents will be able to approve new contacts, manage app permissions more precisely and benefit from new safety features designed to respond when explicit or violent content is shared.

New screen time recommendations and scheduling tools are also intended to encourage healthier digital habits for children.

Software updates arriving later this year across Apple’s operating systems will also introduce a range of performance improvements.

Apple said app launches on iPhone and iPad are up to 30% faster, newly captured photos load up to 70% faster, and AirDrop transfers can be up to 80% quicker. Search functions across Spotlight, Photos, and Mail have also been redesigned to improve speed and accuracy.

Additional features include enhanced health tracking, expanded AirPods personalisation, improved Apple Watch functionality, cross-platform photo sharing through iCloud Shared Albums, and AI-powered upgrades to Apple Maps and Apple Vision Pro.

Public beta testing begins next month, with the full software release scheduled for autumn. Apple noted that some Apple Intelligence features will vary by device, language, and region, with regulatory requirements affecting availability in certain markets, including China and parts of the European Union.

Why does it matter?

Apple’s latest updates reflect a broader industry shift, especially towards embedding child safety and digital well-being features directly into operating systems, as governments and regulators worldwide increase scrutiny of how technology platforms protect young users online.

Enhanced parental controls, communication safeguards, and screen time management tools could help set new standards for online child protection, influencing future policies and product development across the technology sector.

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Stanford Medicine pilot finds safe use of AI in clinical summaries

A Stanford Medicine pilot study has found that an AI-powered tool can help doctors prepare hospital discharge summaries while easing cognitive burden and reducing reported burnout.

The in-house system, known as MedAgentBrief, was designed to condense complex patient histories into draft discharge summaries for physician review. Discharge summaries are essential for continuity of care, but can be time-consuming because doctors must summarise days or weeks of clinical information for outpatient providers.

The tool was piloted for 10 weeks at a Stanford Health Care unit at Sequoia Hospital. Eleven physicians received secure daily emails containing AI-generated summaries for each of their patients, using a format based on a best-practice discharge summary template.

Doctors were asked to review the summaries and provide feedback on inaccuracies, omissions, hallucinations and potential harm. Feedback on 100 AI-enabled summaries found omissions in 25% and inaccuracies in 20%, while hallucinations were rare at 2%.

Physicians rated most unedited summaries as having no harm potential, while some were judged to have mild harm potential. One summary was initially rated as likely to cause moderate harm, but independent reviewers later determined that it posed no risk. No severe harm was reported.

The pilot did not show large time savings. Physicians felt they saved more than 10 minutes per discharge summary, but electronic medical record logs suggested the actual savings were modest, at around three minutes at best. Researchers said the benefit may have come from reducing the effort required to write summaries from scratch.

Participating physicians also reported lower burnout scores. Researchers said the findings suggest AI-generated discharge summaries can support clinical documentation when used under physician supervision, while further evaluation will be needed as health systems consider vendor-based tools.

Why does it matter?

The pilot is useful because it focuses on a practical, high-friction healthcare workflow rather than a speculative AI use case. Discharge summaries affect continuity of care, and poor documentation can create risks for patients after they leave the hospital. Stanford’s findings suggest AI may help reduce doctors’ cognitive load, but also show why human review remains essential: omissions and inaccuracies were common enough that the tool should be treated as clinical support, not automation.

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EY Malta expands AI in audit services

EY Malta has introduced enterprise-scale agentic AI across its Assurance services, integrating the technology into EY Canvas, the firm’s global audit platform.

The rollout forms part of EY’s wider global strategy to embed AI into audit workflows and support audit quality, risk assessment, and client insights.

EY said the AI-enabled framework helps auditors analyse large volumes of data, assess risks, and access updated auditing and accounting guidance in real time. The firm said the technology is designed to support, not replace, auditors, with professional judgement and human oversight remaining central to the audit process.

The system is integrated with Microsoft Azure, Microsoft Foundry, and Microsoft Fabric, reflecting EY’s broader global partnership with Microsoft on the secure and scalable deployment of AI.

EY said the rollout follows global testing and is part of its long-term investment in audit quality, technology, and workforce development. The firm added that further AI enhancements are planned over the coming years as audit teams use the tools across more stages of the audit process.

EY Malta also highlighted related assurance and advisory services linked to AI readiness, governance, and risk management. The firm said the technology would allow teams in Malta to focus more on risk and audit quality while reducing administrative work.

Why does it matter?

The rollout shows how agentic AI is moving into regulated professional services, including audit, where accuracy, accountability, and human judgement remain central. AI could help auditors analyse larger datasets and focus on higher-risk areas. Still, it also raises questions about oversight, explainability, skills, liability, and how regulators assess AI-supported audit work.

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Researchers develop AI governance tools for public health across the Global Majority

A research team led by Professor Jude Kong from the University of Toronto is developing new tools to monitor, assess, and govern the use of AI in public health across the Global Majority, with a particular focus on Africa.

The team, which includes Jake Effoduh, Jim Hinton, Abbas Yazdinejad, and Maral Niaz, has begun mapping how AI is being integrated into healthcare systems and infrastructure. The work focuses on identifying key actors, technologies and use cases, providing a clearer picture of how AI is becoming embedded in public health systems.

The next phase involves developing a dynamic dashboard designed to track AI systems and support evidence-based decision-making. Rather than relying solely on top-down governance frameworks, the team aims to co-develop tools that policymakers, civil society organisations, educators and practitioners can use in their own contexts.

In practice, this means creating tools that are not only technically robust but also socially legitimate and locally relevant. While strengthening AI literacy and governance capacity across the Global Majority, the initiative aims to empower policymakers with evidence-based insights, support civil society in understanding AI systems, and enable more informed and inclusive decision-making processes.

By bringing together expertise in technology, law, public policy and social impact, the project reflects the multidisciplinary nature of AI governance. The team will present its findings at the AI for Good Global Summit in Geneva, during ITU’s Kaleidoscope sessions on Thursday, 9 July 2026, from 15:30 to 16:30.

Why does this matter in AI world?

AI for the Global Majority (AI4GM) is a joint initiative of the Geneva Graduate Institute, Microsoft and the International Telecommunication Union. The initiative supports research on how AI can benefit majority populations in areas including governance, education, health, finance, and digital innovation.

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UK launches £200 million initiative to accelerate AI adoption across the economy

The UK government has unveiled a nationwide initiative to accelerate AI adoption, announcing more than £200 million in funding to help businesses deploy AI technologies while strengthening workforce skills.

The announcement was made at the inaugural AI Adoption Summit, which brought together technology companies, trade unions and industry leaders to discuss the practical deployment of AI across the economy.

The programme includes a £100 million expansion of the Bridge AI scheme to connect businesses with AI solutions and expertise, alongside £53 million for new AI innovation and adoption initiatives. Additional funding will support AI Growth Zones, scholarships, workforce training and sector-specific programmes aimed at helping organisations adopt AI responsibly and effectively.

A key element of the initiative is the creation of the AI Economics Institute, chaired by Nobel Prize-winning economist Simon Johnson. The institute will examine how AI affects employment, productivity and economic growth.

More than 30 companies have also committed to sharing data and experiences related to workplace AI adoption to help inform future policy development.

The UK government said the strategy seeks to increase AI adoption across businesses while ensuring workers gain the skills needed to benefit from technological change. Alongside public investment, several technology companies announced additional commitments focused on training, workforce development, research and business support.

Why does it matter?

Governments are increasingly shifting their focus from supporting AI research alone to encouraging widespread adoption across businesses and public services. Many policymakers see AI deployment as a key driver of productivity, competitiveness and economic growth, provided organisations and workers have the skills needed to use the technology effectively.

The UK’s initiative reflects this broader trend by combining investment in AI adoption with workforce development and evidence-based policymaking. The creation of the AI Economics Institute also signals growing interest in understanding how AI will affect jobs, productivity and economic performance as adoption accelerates.

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Belgium outperforms EU average in business AI use

Belgium ranks among Europe’s top five countries for business use of AI, with more than a third of companies now using at least one AI technology.

In 2025, 34.54% of Belgian companies reported using AI, up from 24.71% in 2024. The figure is well above the European average of 19.95%, according to the latest Belgian Digital Economy Overview.

Adoption varies strongly by company size. More than 76% of large enterprises already use AI technologies, compared with just over 28% of small businesses.

The most common business applications include text analysis, content production (written or spoken), machine learning, and workflow automation. Companies mainly use AI for administrative and management processes, accounting and finance, and marketing and sales.

AI use is also rising among individuals. In 2025, 33.53% of Belgians used generative AI tools for personal use, compared with the European average of 25.09%.

Digitalisation Minister Vanessa Matz said Belgium should build on the momentum with a coherent strategy that strengthens expertise, supports talent, improves access to European technological capabilities, and builds trust.

She also stressed that AI development should take place within a clear, protective, and inclusive framework that respects privacy, prevents bias, and avoids widening inequalities.

Why does it matter?

Belgium’s AI uptake shows that business adoption is no longer limited to experimentation, especially among large companies. The gap between large enterprises and small businesses also matters, because uneven adoption could widen productivity differences inside the economy. The policy challenge is to support broader AI use while building safeguards around privacy, bias, skills, and inclusion.

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UK to launch national centre for AI in policing

The UK government is preparing to formally launch PoliceAI, a national centre dedicated to AI in policing, later this month. The centre began mobilising in April 2026 and will support police forces in England and Wales with the responsible adoption of AI and automation.

The government says the use of AI in policing must be lawful, ethical and transparent, supported by robust algorithmic assessments before deployment. It also emphasises that accountability for AI performance and the use of AI-generated outputs must be clearly defined through operational procedures and governance frameworks.

PoliceAI will be hosted by the College of Policing and funded through a Home Office grant under Section 57 of the Police Act 1996. The centre is expected to coordinate AI-related activity across police forces, helping to reduce duplication, improve consistency and strengthen public confidence.

PoliceAI will include an AI Lab responsible for developing, testing and evaluating AI tools, products and services for policing applications. It will assess commercial products and open-source models, benchmark their performance in a UK policing context, run sandbox testing, and support more informed procurement and deployment decisions by Chief Officers.

PoliceAI will also support forces with adoption, guidance, procurement, training, and business change. A dedicated strategy and oversight function will also maintain a public registry of AI models used in operational policing, including details of testing, governance checks and deployment safeguards.

Initial priorities include case file assistants, disclosure assistants, crime data integrity tools, rapid analysis of CCTV and digital media, image identification and classification, governance for Copilot use, transcription and translation tools, and possible AI applications for retail crime and tool theft. A Policing AI Threat Hub will support efforts to address criminal misuse of AI, including the detection of deepfakes and AI-generated false evidence.

Why does it matter?

Police forces are increasingly exploring AI tools to support investigations, administrative tasks, evidence analysis and operational decision-making. However, the use of AI in law enforcement raises important questions about transparency, accountability, bias, public trust and oversight.

PoliceAI represents an effort to create a more coordinated approach to AI adoption across policing in England and Wales. By providing testing, governance, training and public transparency mechanisms, the centre aims to help police forces deploy AI technologies more consistently while addressing concerns about their responsible use.

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