Artificial intelligence Archives | Page 25 of 658

Apple may be preparing a major Siri AI shake-up in iOS 27

Apple is reportedly preparing a major expansion of Apple Intelligence that could allow users to choose which AI model powers Siri and other system features. According to recent reports, iOS 27, iPadOS 27, and macOS 27 may introduce a new ‘Extensions’ framework designed to integrate third-party AI systems directly into Apple’s software ecosystem.

The reported feature would allow applications such as Gemini and Claude to connect with Siri through their App Store apps. Users may be able to select different AI providers for different tasks, while Apple is also said to be testing separate Siri voices for responses generated by external models rather than Apple’s own systems.

The move would expand Apple’s broader AI partnership strategy rather than replace existing integrations. ChatGPT already supports selected Apple Intelligence functions, and earlier reporting suggested Google Gemini could eventually power parts of Siri itself. The new framework appears aimed at turning Apple devices into a wider AI platform that supports multiple large language models rather than a single assistant stack.

Apple is expected to present further details during its Worldwide Developers Conference on 8 June 2026. If the reported changes materialise, they could significantly reshape how users interact with AI assistants by giving them more control over which models handle tasks such as search, writing, and image generation.

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OpenAI found non-compliant in Canadian ChatGPT privacy probe

Canada’s federal and provincial privacy regulators have found that aspects of OpenAI’s collection, use, and disclosure of personal information through ChatGPT did not comply with applicable private-sector privacy laws, particularly in relation to model training on publicly accessible online data and user interactions.

The joint investigation was conducted by the Office of the Privacy Commissioner of Canada, the Commission d’accès à l’information du Québec, and the privacy commissioners of British Columbia and Alberta.

It examined OpenAI’s GPT-3.5 and GPT-4 models as used in ChatGPT, focusing on whether the company’s handling of personal information from public internet sources, licensed third-party datasets, and user interactions met legal requirements on appropriate purposes, consent, transparency, accuracy, access, retention, and accountability.

The regulators accepted that OpenAI’s overall purposes for developing and deploying ChatGPT were legitimate and appropriate. However, they found that the company’s initial collection of personal information from publicly accessible websites and licensed third-party sources for model training was overbroad and therefore inappropriate, given the scale, sensitivity, and potential inaccuracy of the data involved, as well as the limits of the mitigation measures in place at the time.

The Offices also found that OpenAI failed to obtain valid consent to collect and use personal information from public internet sources to train its models. They concluded that implied consent was not sufficient because the data could include sensitive personal information and because individuals would not reasonably have expected information about them posted online to be scraped and used for AI model training in this way.

On user interactions with ChatGPT, the regulators accepted that using some chat data for model improvement could serve OpenAI’s legitimate purposes. Still, they found that express consent should have been obtained.

They said OpenAI’s safeguards at the time were not strong enough to ensure that sensitive personal information would not be included in training data, and that many users would not reasonably have understood that their conversations could be used to train models or reviewed by human trainers.

The report also found that OpenAI should have obtained express consent for certain disclosures of personal information through ChatGPT outputs, especially where the information was sensitive or fell outside individuals’ reasonable expectations.

While OpenAI had introduced measures to reduce the risk of sensitive disclosures, the regulators said those measures covered a narrower set of information than the broader categories of personal information protected under the relevant privacy laws.

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Siri AI delays lead to $250 million Apple settlement

Apple has agreed to pay $250 million to settle a class action lawsuit alleging that it misled consumers about the readiness and availability of AI-powered Siri features promoted ahead of the iPhone 16 launch. Under the proposed agreement, eligible US customers who bought supported iPhone models between 10 June 2024 and 29 March 2025 may receive between $25 and $95 per device, depending on the number of claims. Apple denied wrongdoing and settled the case without admitting liability.

The complaint argued that consumers who purchased supported iPhone 15 and iPhone 16 models expected advanced Apple Intelligence features and a significantly upgraded Siri experience that were not available at the time of sale. Plaintiffs said Apple’s marketing created the impression that the new capabilities would arrive sooner and with broader functionality than users ultimately received.

The settlement comes shortly before Apple’s annual Worldwide Developers Conference, where the company is widely expected to present further updates to Siri and its wider AI strategy.

Why does it matter?

The case shows how AI product marketing is becoming a legal and regulatory risk, not just a branding issue. As technology companies use generative AI features to drive device sales and platform adoption, courts and consumers are paying closer attention to whether those capabilities are actually available when products reach the market. The Apple settlement suggests that overstating AI readiness can create liability even before regulators step in, making transparency around launch claims increasingly important across the sector.

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Generative AI guidance issued by Australia’s New South Wales tribunal

The New South Wales Civil and Administrative Tribunal has issued guidance on the acceptable use of generative AI in tribunal proceedings as part of Privacy Awareness Week NSW 2026, which this year focuses on personal information risks in the age of AI.

According to NCAT, generative AI tools may be used to assist with administrative and organisational tasks such as summarising material, organising information, or preparing chronologies. At the same time, the tribunal warns that such tools can create privacy risks if users enter personal, sensitive, or confidential information.

The guidance is set out in NCAT Procedural Direction 7 on the use of generative AI, together with an accompanying fact sheet. NCAT says the aim is to clarify when generative AI may be used in tribunal-related work while reinforcing obligations to protect personal and confidential information.

The tribunal also draws a clear line around evidentiary material. Generative AI must not be used to generate or alter evidence in tribunal proceedings, including statements, affidavits, statutory declarations, character references, or other evidentiary documents.

NCAT further states that generative AI must not be used to generate content for an expert report unless the tribunal has given permission. It is encouraging parties and their representatives to review the guidance before using such tools in proceedings.

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Online Safety Act brings progress, but UK children still face harm online

A new report from Internet Matters suggests the UK’s Online Safety Act has introduced more visible safety measures for children, but has not yet delivered the step change needed to make their online lives meaningfully safer. Drawing on surveys and focus groups with children and parents, the report presents an early view of how the law is affecting families in practice.

The findings point to some clear signs of progress. Parents and children report seeing more safety features, including improved reporting tools, content filters, restrictions on certain functions, and stronger parental controls. Many children also say the content they encounter online is becoming more age-appropriate.

At the same time, the report argues that important weaknesses remain. Children continue to encounter harmful content at high rates, while age verification is widely seen as easy to bypass. Internet Matters also says that some of the issues families care most about, including excessive screen time and the risks linked to AI-generated content, are still not adequately addressed under the current framework.

The report concludes that parents are still carrying too much of the burden of keeping children safe online. It calls for stronger enforcement, more effective age assurance, tighter limits on harmful features, and a broader safety-by-design approach to digital services used by children in the UK.

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AI turns disaster news into structured global risk maps

A new AI-powered dataset developed by the European Commission’s Joint Research Centre, in cooperation with the Italian technology company Engineering Ingegneria Informatica and the Institute of Health and Society at the University of Louvain, is turning fragmented disaster reporting into structured knowledge to help researchers and policymakers better understand how crises unfold and interact.

The dataset covers more than 3,000 disaster events across 175 countries and 26 hazard types, drawing on global reporting to reduce geographical and thematic gaps in existing databases.

Climate and geological disasters, including floods, hurricanes, earthquakes, and wildfires, are processed into structured ‘storylines’ that trace causes, impacts, and responses.

A key feature of the system is its ability to identify cascading effects, in which one event triggers a chain of secondary impacts, such as infrastructure disruption, agricultural losses, or disease outbreaks.

Unlike traditional datasets that record impacts in isolation, the AI-generated knowledge graphs reveal interconnected risk dynamics that are often hidden in standard reporting.

The pipeline uses large language models and retrieval-augmented techniques to extract relevant articles and turn them into structured summaries and visual networks.

Why does it matter?

The development shifts disaster analysis away from fragmented reporting and towards more structured, interconnected intelligence. By showing how hazards cascade into broader social, economic, and environmental impacts, it can help policymakers and emergency services anticipate secondary risks more effectively, rather than reacting to isolated events.

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China closes consultation on digital virtual human services

The Cyberspace Administration of China has closed its public consultation on the draft Administrative Measures for Digital Virtual Human Information Services, which set out proposed rules for digital virtual human services provided to the public in China.

The notice states that the consultation opened in April 2026 and that comments were accepted until 6 May 2026. According to the draft, the measures would apply to internet information services delivered to the public within China through digital virtual humans.

The draft says providers and users must process data for lawful purposes and within a lawful scope, use data from legal sources, and fulfil their data security responsibilities. It also requires technical and other necessary measures to protect data storage and transmission and to prevent leaks or improper use.

The text further requires digital virtual human service providers and users to establish security risk monitoring, warning, emergency response, anti-addiction mechanisms, and stronger content-direction management, while also retaining logs. Providers whose services have public opinion attributes or social mobilisation capacity would also be required to complete algorithm filing procedures and security assessments in line with existing national rules.

Beyond cybersecurity and data protection, the draft includes provisions on personal information, personality rights, intellectual property, content controls, labelling requirements, and protections for minors. It defines digital virtual humans as virtual figures in the non-physical world that simulate human appearance and may have voice, behaviour, interaction abilities, or personality traits, using graphics, digital image processing, or AI technologies.

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Major publishers book again Meta’s Llama over AI training

Meta and Mark Zuckerberg are facing a new copyright lawsuit from five major publishers, Hachette, Macmillan, McGraw-Hill, Elsevier, and Cengage, along with author Scott Turow. The plaintiffs accuse the company of using millions of copyrighted books, journal articles, textbooks, and scholarly works to train its Llama AI models without permission. Filed in the US District Court for the Southern District of New York (Manhattan federal court), the proposed complaint seeks monetary compensation, an injunction, and the destruction of allegedly infringing copies held by Meta.

The complaint argues that Meta’s AI strategy relied on protected works from trade, education, and academic publishing, including content allegedly taken from pirate libraries such as LibGen and Anna’s Archive, as well as broad web scrapes containing subscription-only material. The publishers also claim Zuckerberg personally directed or authorised the conduct, a charge Meta is expected to contest vigorously.

At the centre of the lawsuit is a policy question now shaping AI governance worldwide: whether large-scale copying for model training can be justified as fair use or requires permission, transparency, and compensation? Meta and other AI developers argue that training enables transformative innovation, while rights holders say commercial models are being built from creative and scholarly labour without licensing. A previous Meta win in an author’s case showed that courts may accept fair-use arguments, but only where plaintiffs fail to prove clear market harm.

Either way, the publishers are trying to make that market-harm argument harder to dismiss. Their filing describes Llama as an ‘infinite substitution machine’, capable of generating long-form books, educational materials, and scholarly-style outputs that may compete with human-authored works. The case also points to the alleged erosion of licensing markets, arguing that harm occurs not only when AI outputs imitate books, but also when copyrighted works are copied into commercial training pipelines without consent.

The US Copyright Office’s 2025 report said that fair use in generative AI training requires case-by-case analysis, with market effects and the source of the training material playing central roles. In the EU, the AI Act has shifted the debate toward transparency by requiring general-purpose AI providers to publish summaries of their training data and to comply with the EU copyright rules, including rights reservations for text and data mining.

Why does it matter?

The Meta case is the manifestation of a global shift in digital governance: AI copyright disputes are no longer isolated lawsuits, but part of a broader effort to define lawful data supply chains. Anthropic’s $1.5 billion settlement over pirated books, the EU’s training-data transparency regulation, and continuing legal disputes in the US all point in the same direction: courts and regulators are asking whether AI innovation can remain competitive while respecting the rights, labour, and markets that make high-quality knowledge possible.

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European Commission publishes first Digital Markets Act review

The European Commission has published its first formal review of the Digital Markets Act, assessing how the regulation is affecting the behaviour of large online platforms in the EU digital economy. According to the review, the law has produced visible changes in some areas, while also exposing continuing problems in implementation and enforcement.

The review points to changes in user choice since the DMA entered into force in March 2024. These include support for third-party app stores and prompts on devices to select browsers or search engines, alongside reported increases in usage and downloads of alternative services.

Enforcement action is also a central part of the assessment. In April 2025, Apple was fined €500 million for blocking developers from directing users to cheaper purchasing options, while Meta was fined €200 million over its ‘consent or pay’ model. Both companies are appealing the decisions.

At the same time, the review identifies clear implementation challenges. It says investigations are taking around twice as long as the 12-month target, while legal procedures are being used to slow compliance. It also raises broader questions about whether fast-growing areas such as AI tools and cloud platforms should eventually be brought within the scope of the regulation.

The Digital Markets Act is therefore presented less as a completed intervention than as an ongoing regulatory process. The review suggests that its long-term impact will depend not only on the rules already in force, but also on how consistently they are enforced and how the EU responds to changes in digital markets.

Why does it matter?

The review matters because it shows that the real test of the Digital Markets Act is no longer whether the EU can write rules for large platforms, but whether it can enforce them quickly and adapt them to new market realities. Early changes in user choice suggest the law is starting to affect platform behaviour. However, delays in investigations and questions around AI and cloud services show that the regulatory contest is still evolving.

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New Meta age assurance system aims to prevent underage access

Meta has expanded its use of AI to strengthen age assurance and improve enforcement of underage account policies across its platforms. The systems are designed to detect users under 13 for removal and to place suspected teens into protected Teen Account settings on Instagram and Facebook in regions including the EU, Brazil, and the US.

The technology analyses a range of signals, including profile information, user activity, and other contextual indicators, to estimate age more accurately. Automated systems are also being used to support faster and more consistent review of reports related to underage use.

Visual analysis has also become part of Meta’s broader detection approach, with the company saying its systems look for general age-related indicators rather than attempting to identify specific individuals. Reporting tools have been simplified, and AI-assisted moderation is being used to improve the speed and reliability of enforcement decisions.

Alongside these enforcement measures, Meta is increasing parental engagement through notifications and guidance to encourage more accurate age reporting and safer online behaviour. The wider effort reflects growing pressure on platforms to move beyond self-declared age checks and to build stronger systems to protect younger users.

Why does it matter?

The significance of the move lies in the fact that age assurance is becoming a core platform governance issue rather than a secondary moderation tool. Meta is trying to show that large social platforms can use AI not only to recommend or personalise content, but also to enforce minimum age rules at scale. That matters because regulators are increasingly questioning whether self-declared age data is enough to protect minors online. It also points to a broader shift in which platforms are expected to combine safety obligations, automated detection, and parental tools into a more active system of child protection.

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