Content Policy

AI health tools need clinicians to prevent serious risks, Oxford study warns

The University of Oxford has warned that AI in healthcare, primarily through chatbots, should not operate without human oversight.

Researchers found that relying solely on AI for medical self-assessment could worsen patient outcomes instead of improving access to care. The study highlights how these tools, while fast and data-driven, fall short in delivering the judgement and empathy that only trained professionals can offer.

The findings raise alarm about the growing dependence on AI to fill gaps caused by doctor shortages and rising costs. Chatbots are often seen as scalable solutions, but without rigorous human-in-the-loop validation, they risk providing misleading or inconsistent information, particularly to vulnerable groups.

Rather than helping, they might increase health disparities by delaying diagnosis or giving patients false reassurance.

Experts are calling for safer, hybrid approaches that embed clinicians into the design and ongoing use of AI tools. The Oxford researchers stress that continuous testing, ethical safeguards and clear protocols must be in place.

Instead of replacing clinical judgement, AI should support it. The future of digital healthcare hinges not just on innovation but on responsibility and partnership between technology and human care.

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India urges preference for state telecom providers

The Department of Telecommunications (DoT) in India has introduced a policy urging all state governments and Union Territories to prioritise state-run telecom operators Bharat Sanchar Nigam Ltd (BSNL) and Mahanagar Telephone Nigam Ltd (MTNL) for their communication needs. Although not legally binding, that policy directive emphasises data security as a key reason for favouring these public sector providers.

DoT Secretary underscored the increasing competitiveness of BSNL and MTNL, noting that BSNL now manages MTNL’s operations and will set up a dedicated nodal point to cater to state governments efficiently. The move marks a significant strategic shift toward promoting state-owned telecom companies in government communications.

The policy has raised concerns among private telecom companies, who fear losing valuable government contracts to BSNL and MTNL. Private providers currently hold over 92% of the market’s revenue, and government contracts are especially important for smaller ISPs with tight margins. Diverting these contracts could significantly hurt their financial stability.

BSNL and MTNL were initially created to operate independently and compete fairly with private firms. This new policy, favouring them, risks undermining that independence and disrupting the telecom sector’s competitive balance in India.

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NSA and allies set AI data security standards

The National Security Agency (NSA), in partnership with cybersecurity agencies from the UK, Australia, New Zealand, and others, has released new guidance aimed at protecting the integrity of data used in AI systems.

The Cybersecurity Information Sheet (CSI), titled AI Data Security: Best Practices for Securing Data Used to Train & Operate AI Systems, outlines emerging threats and sets out 10 recommendations for mitigating them.

The CSI builds on earlier joint guidance from 2024 and signals growing global urgency around safeguarding AI data instead of allowing systems to operate without scrutiny.

The report identifies three core risks across the AI lifecycle: tampered datasets in the supply chain, deliberately poisoned data intended to manipulate models, and data drift—where changes in data over time reduce performance or create new vulnerabilities.

These threats may erode accuracy and trust in AI systems, particularly in sensitive areas like defence, cybersecurity, and critical infrastructure, where even small failures could have far-reaching consequences.

To reduce these risks, the CSI recommends a layered approach—starting with sourcing data from reliable origins and tracking provenance using digital credentials. It advises encrypting data at every stage, verifying integrity with cryptographic tools, and storing data securely in certified systems.

Additional measures include deploying zero trust architecture, using digital signatures for dataset updates, and applying access controls based on data classification instead of relying on broad administrative trust.

The CSI also urges ongoing risk assessments using frameworks like NIST’s AI RMF, encouraging organisations to anticipate emerging challenges such as quantum threats and advanced data manipulation.

Privacy-preserving techniques, secure deletion protocols, and infrastructure controls round out the recommendations.

Rather than treating AI as a standalone tool, the guidance calls for embedding strong data governance and security throughout its lifecycle to prevent compromised systems from shaping critical outcomes.

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Fake DeepSeek ads deliver ‘BrowserVenom’ malware to curious AI users

Cybercriminals are exploiting the surge in interest around local AI tools by spreading a new malware strain via Google ads.

According to antivirus firm Kaspersky, attackers use fake ads for DeepSeek’s R1 AI model to deliver ‘BrowserVenom,’ malware designed to intercept and manipulate a user’s internet traffic instead of merely infecting the device.

The attackers purchased ads appearing in Google search results for ‘deep seek r1.’ Users who clicked were redirected to a fake website—deepseek-platform[.]com—which mimicked the official DeepSeek site and offered a file named AI_Launcher_1.21.exe.

Kaspersky’s analysis of the site’s source code uncovered developer notes in Russian, suggesting the campaign is operated by Russian-speaking actors.

Once launched, the fake installer displayed a decoy installation screen for the R1 model, but silently deployed malware that altered browser configurations.

BrowserVenom rerouted web traffic through a proxy server controlled by the hackers, allowing them to decrypt browsing sessions and capture sensitive data, while evading most antivirus tools.

Kaspersky reports confirmed infections across multiple countries, including Brazil, Cuba, India, and South Africa.

The malicious domain has since been taken down. However, the incident highlights the dangers of downloading AI tools from unofficial sources. Open-source models like DeepSeek R1 require technical setup, typically involving multiple configuration steps, instead of a simple Windows installer.

As interest in running local AI grows, users should verify official domains and avoid shortcuts that could lead to malware.

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Meta sues AI firm over fake nude images created without consent

Meta has filed a lawsuit against Joy Timeline HK Ltd in Hong Kong, accusing the firm of using its platforms to promote a generative AI app called CrushAI.

The app allows users to digitally strip clothes from images of people, often without consent. Meta said the company repeatedly attempted to bypass ad review systems to push harmful content, advertising phrases like ‘see anyone naked’ on Facebook and Instagram.

The lawsuit follows Meta’s broader investigation into ‘nudity’ apps, which are increasingly being used to create sexualised deepfakes. Despite bans on nonconsensual explicit content, the company said such apps evade detection by disguising ads or rotating domain names after bans.

According to research by Cornell Tech, over 8,000 ads linked to CrushAI appeared on Meta platforms in recent months. Meta responded by updating its detection systems with a broader range of flagged terms and emojis.

While many of the manipulated images target celebrities, concerns are growing about the use of such technology to exploit minors. In one case in Florida, two teenagers used similar AI tools to create sexualised images of classmates.

The issue has sparked legal action in the US, where the Take It Down Act, signed into law earlier this year, criminalises the publication of nonconsensual deepfake imagery and simplifies removal processes for victims.

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Turing Institute urges stronger AI research security

The Alan Turing Institute has warned that urgent action is needed to protect the UK’s AI research from espionage, intellectual property theft and risky international collaborations.

Its Centre for Emerging Technology and Security (CETaS) has published a report calling for a culture shift across academia to better recognise and mitigate these risks.

The report highlights inconsistencies in how security risks are understood within universities and a lack of incentives for researchers to follow government guidelines. Sensitive data, the dual-use potential of AI, and the risk of reverse engineering make the field particularly vulnerable to foreign interference.

Lead author Megan Hughes stressed the need for a coordinated response, urging government and academia to find the right balance between academic freedom and security.

The report outlines 13 recommendations, including expanding support for academic due diligence and issuing clearer guidance on high-risk international partnerships.

Further proposals call for compulsory research security training, better threat communication from national agencies, and standardised risk assessments before publishing AI research.

The aim is to build a more resilient research ecosystem as global interest in UK-led AI innovation continues to grow.

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Meta and TikTok contest the EU’s compliance charges

Meta and TikTok have taken their fight against an the EU supervisory fee to Europe’s second-highest court, arguing that the charges are disproportionate and based on flawed calculations.

The fee, introduced under the Digital Services Act (DSA), requires major online platforms to pay 0.05% of their annual global net income to cover the European Commission’s oversight costs.

Meta questioned the Commission’s methodology, claiming the levy was based on the entire group’s revenue instead of the specific EU-based subsidiary.

The company’s lawyer told judges it still lacked clarity on how the fee was calculated, describing the process as opaque and inconsistent with the spirit of the law.

TikTok also criticised the charge, alleging inaccurate and discriminatory data inflated its payment.

Its legal team argued that user numbers were double-counted when people switched between devices. The Commission had wrongly calculated fees based on group profits rather than platform-specific earnings.

The Commission defended its approach, saying group resources should bear the cost when consolidated accounts are used. A ruling is expected from the General Court sometime next year.

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AI startup faces lawsuit from Disney and Universal

Two of Hollywood’s most powerful studios, Disney and Universal, have launched a copyright infringement lawsuit against the AI firm Midjourney, accusing it of illegally replicating iconic characters.

The studios claim the San Francisco-based company copied their creative works without permission, describing it as a ‘bottomless pit of plagiarism’.

Characters such as Darth Vader, Elsa, and the Minions were cited in the 143-page complaint, which alleges Midjourney used these images to train its AI system and generate similar content.

Disney and Universal argue that the AI firm failed to invest in the creative process, yet profited heavily from the output — reportedly earning $US300 million in paid subscriptions last year.

Despite early attempts by the studios to raise concerns and propose safeguards already adopted by other AI developers,

Midjourney allegedly ignored them and pressed ahead with further product releases. The company, which calls itself a small, self-funded team of 11, has declined to comment on the lawsuit directly but insists it has a long future ahead.

Disney’s legal chief, Horacio Gutierrez, stressed the importance of protecting creative works that result from decades of investment. While supporting AI as a tool for innovation, he maintained that ‘piracy is piracy’, regardless of whether humans or machines carry it out.

The studios are seeking damages and a court order to stop the AI firm from continuing its alleged copyright violations.

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Wikipedia halts AI summaries test after backlash

Wikipedia has paused a controversial trial of AI-generated article summaries following intense backlash from its community of volunteer editors.

The Wikimedia Foundation had planned a two-week opt-in test for mobile users using summaries produced by Aya, an open-weight AI model developed by Cohere.

However, the reaction from editors was swift and overwhelmingly negative. The discussion page became flooded with objections, with contributors arguing that such summaries risked undermining the site’s reputation for neutrality and accuracy.

Some expressed concerns that inserting AI content would override Wikipedia’s long-standing collaborative approach by effectively installing a single, unverifiable voice atop articles.

Editors warned that AI-generated summaries lacked proper sourcing and could compromise the site’s credibility. Recent AI blunders by other tech giants, including Google’s glue-on-pizza mishap and Apple’s false death alert, were cited as cautionary examples of reputational risk.

For many, the possibility of similar errors appearing on Wikipedia was unacceptable.

Marshall Miller of the Wikimedia Foundation acknowledged the misstep in communication and confirmed the project’s suspension.

While the Foundation remains interested in exploring AI to improve accessibility, it has committed to ensuring any future implementation involves direct participation from the Wikipedia community.

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Sam Altman predicts AI will discover new ideas

In a new blog post titled The Gentle Singularity, OpenAI CEO Sam Altman predicted that AI systems capable of producing ‘novel insights’ may arrive as early as 2026.

While Altman’s essay blends optimism with caution, it subtly signals the company’s next central ambition — creating AI that goes beyond repeating existing knowledge and begins generating original ideas instead of mimicking human reasoning.

Altman’s comments echo a broader industry trend. Researchers are already using OpenAI’s recent o3 and o4-mini models to generate new hypotheses. Competitors like Google, Anthropic and FutureHouse are also shifting their focus towards scientific discovery.

Google’s AlphaEvolve has reportedly devised novel solutions to complex maths problems, while FutureHouse claims to have built AI capable of genuine scientific breakthroughs.

Despite the optimism, experts remain sceptical. Critics argue that AI still struggles to ask meaningful questions, a key ingredient for genuine insight.

Former OpenAI researcher Kenneth Stanley, now leading Lila Sciences, says generating creative hypotheses is a more formidable challenge than agentic behaviour. Whether OpenAI achieves the leap remains uncertain, but Altman’s essay may hint at the company’s next bold step.

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