Writers challenge troubling AI assumptions about language and style

A growing unease among writers is emerging as AI tools reshape how language is produced and perceived. Long-established habits, including the use of em dashes and semicolons, are increasingly being viewed with suspicion as machine-generated text becomes more common.

The concern is not opposition to AI itself, but the blurring of boundaries between human expression and automated output. Writers whose work was used to train large language models without consent say stylistic traits developed over decades are now being misread as algorithmic authorship.

Academic and editorial norms are also shifting under this pressure. Teaching practices that once valued rhythm, voice, and individual cadence are increasingly challenged by stricter stylistic rules, sometimes framed as safeguards against sloppy or machine-like writing rather than as matters of taste or craft.

At the same time, productivity tools embedded into mainstream software continue to intervene in the writing process, offering substitutions and revisions that prioritise clarity and efficiency over nuance. Such interventions risk flattening language and discouraging the idiosyncrasies that define human authorship.

As AI becomes embedded in publishing, education, and professional writing, the debate is shifting from detection to preservation. Many writers warn that protecting human voice and stylistic diversity is essential, arguing that affectless, uniform prose would erode creativity and trust.

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Hollywood figures back anti-AI campaign

More than 800 creatives in the US have signed an anti-AI campaign accusing big technology companies of exploiting human work. High-profile figures from film and television in the country have backed the initiative, which argues that training AI on creative content without consent amounts to theft.

The campaign was launched by the Human Artistry Campaign, a coalition representing creators, unions and industry groups in the country. Supporters say AI systems should not be allowed to use artistic work without permission and fair compensation.

Actors and filmmakers in the US warned that unchecked AI adoption threatens livelihoods across film, television and music. Campaign organisers said innovation should not come at the expense of creators’ rights or ownership of their work.

The statement adds to growing pressure on lawmakers and technology firms in the US. Creative workers are calling for clearer rules on how AI can be developed and deployed across the entertainment industry.

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Analysis reveals Grok generated 3 million sexualised images

A new analysis found Grok generated an estimated three million sexualised images in 11 days, including around 23,000 appearing to depict children. The findings raise serious concerns over safeguards, content moderation, and platform responsibility.

The surge followed the launch of Grok’s one-click image editing feature in late December, which quickly gained traction among users. Restrictions were later introduced, including paid access limits and technical measures to prevent image undressing.

Researchers based their estimates on a random sample of 20,000 images, extrapolating from these results to more than 4.6 million images generated during the study period. Automated tools and manual review identified sexualised content and confirmed cases involving individuals appearing under 18.

Campaigners have warned that the findings expose significant gaps in AI safety controls, particularly in protecting children. Calls are growing for stricter oversight, stronger accountability, and more robust safeguards before large-scale AI image deployment.

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Japan arrests suspect over AI deepfake pornography

Police in Japan have arrested a man accused of creating and selling non-consensual deepfake pornography using AI tools. The Tokyo Metropolitan Police Department said thousands of manipulated images of female celebrities were distributed through paid websites.

Investigators in Japan allege the suspect generated hundreds of thousands of images over two years using freely available generative AI software. Authorities say the content was promoted on social media before being sold via subscription platforms.

The arrest follows earlier cases in Japan and reflects growing concern among police worldwide. In South Korea, law enforcement has reported hundreds of arrests linked to deepfake sexual crimes, while cases have also emerged in the UK.

European agencies, including Europol, have also coordinated arrests tied to AI-generated abuse material. Law enforcement bodies say the spread of accessible AI tools is forcing rapid changes in forensic investigation and in the handling of digital evidence.

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Google adds Personal Intelligence to AI Search

Google has expanded AI Search with Personal Intelligence, enabling more personalised responses using Gmail and Google Photos data. The feature aims to combine global information with individual context to deliver search results tailored to each user.

Eligible Google AI Pro and AI Ultra subscribers can opt in to securely connect their Gmail and Photos accounts, allowing Search to draw on personal preferences, travel plans, purchases, and memories.

The system uses contextual insights to generate recommendations that reflect users’ habits, interests, and upcoming activities.

Personal Intelligence enhances shopping, travel planning, and lifestyle discovery by anticipating needs and offering customised suggestions. Privacy controls remain central, with users able to manage data connections and turn off personal context at any time.

The feature is launching as an experimental Labs release for English-language users in the United States, with broader availability expected following testing. Google said ongoing feedback will guide refinements as the system continues to evolve.

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Education for Countries programme signals OpenAI push into public education policy

OpenAI has launched the Education for Countries programme, a new global initiative designed to support governments in modernising education systems and preparing workforces for an AI-driven economy.

The programme responds to a widening gap between rapid advances in AI capabilities and people’s ability to use them effectively in everyday learning and work.

Education systems are positioned at the centre of closing that gap, as research suggests a significant share of core workplace skills will change by the end of the decade.

By integrating AI tools, training and research into schools and universities, national education frameworks can evolve alongside technological change and better equip students for future labour markets.

The programme combines access to tools such as ChatGPT Edu and advanced language models with large-scale research on learning outcomes, tailored national training schemes and internationally recognised certifications.

A global network of governments, universities and education leaders will also share best practices and shape responsible approaches to AI use in classrooms.

Initial partners include Estonia, Greece, Italy, Jordan, Kazakhstan, Slovakia, Trinidad and Tobago and the United Arab Emirates. Early national rollouts, particularly in Estonia, already involve tens of thousands of students and educators, with further countries expected to join later in 2026.

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OpenAI ads in ChatGPT signal a shift in conversational advertising

The AI firm, OpenAI, plans to introduce advertising within ChatGPT for logged-in adult users, marking a structural shift in how brands engage audiences through conversational interfaces.

Ads would be clearly labelled and positioned alongside responses, aiming to replace interruption-driven formats with context-aware brand suggestions delivered during moments of active user intent.

Industry executives describe conversational AI advertising as a shift from exposure to earned presence, in which brands must provide clarity or utility to justify inclusion.

Experts warn that trust remains fragile, as AI recommendations carry the weight of personal consultation, and undisclosed commercial influence could prompt rapid user disengagement instead of passive ad avoidance.

Regulators and marketers alike highlight risks linked to dark patterns, algorithmic framing and subtle manipulation within AI-mediated conversations.

As conversational systems begin to shape discovery and decision-making, media planning is expected to shift toward intent-led engagement, authority-building, and transparency, reshaping digital advertising economics beyond search rankings and impression-based buying.

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The House of Lords backs social media ban for under-16s

The upper house of the Parliament of the United Kingdom,, the House of Lords has voted in favour of banning under-16s from social media platforms, backing an amendment to the government’s schools bill by 261 votes to 150. The proposal would require ministers to define restricted platforms and enforce robust age verification within a year.

Political momentum for tighter youth protections has grown after Australia’s similar move, with cross-party support emerging at Westminster. More than 60 Labour MPs have joined Conservatives in urging a UK ban, increasing pressure ahead of a Commons vote.

Supporters argue that excessive social media use contributes to declining mental health, online radicalisation, and classroom disruption. Critics warn that a blanket ban could push teenagers toward less regulated platforms and limit positive benefits, urging more vigorous enforcement of existing safety rules.

The government has rejected the amendment and launched a three-month consultation on age checks, curfews, and curbing compulsive online behaviour. Ministers maintain that further evidence is needed before introducing new legal restrictions.

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Ransomware attack on Under Armour leads to massive customer data exposure

Under Armour is facing growing scrutiny following the publication of customer data linked to a ransomware attack disclosed in late 2025.

According to breach verification platform Have I Been Pwned, a dataset associated with the incident appeared on a hacking forum in January, exposing information tied to tens of millions of customers.

The leaked material reportedly includes 72 million email addresses alongside names, dates of birth, location details and purchase histories. Security analysts warn that such datasets pose risks that extend far beyond immediate exposure, particularly when personal identifiers and behavioural data are combined.

Experts note that verified customer information linked to a recognised brand can enable compelling phishing and fraud campaigns powered by AI tools.

Messages referencing real transactions or purchase behaviour can blur the boundary between legitimate communication and malicious activity, increasing the likelihood of delayed victimisation.

The incident has also led to legal action against Under Armour, with plaintiffs alleging failures in safeguarding sensitive customer information. The case highlights how modern data breaches increasingly generate long-term consequences rather than immediate technical disruption.

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New AI method boosts reasoning without extra training

Researchers at the University of California, Riverside, have introduced a technique that improves AI reasoning without requiring additional training data. Called Test-Time Matching, the approach enhances AI performance by enabling dynamic model adaptation.

The method addresses a persistent weakness in multimodal AI systems, which often struggle to interpret unfamiliar combinations of images and text. Traditional evaluation metrics rely on isolated comparisons that can obscure deeper reasoning capabilities.

By replacing these with a group-based matching approach, the researchers uncovered hidden model potential and achieved markedly stronger results.

Test-Time Matching lets AI systems refine predictions through repeated self-correction. Tests on SigLIP-B16 showed substantial gains, with performance surpassing larger models, including GPT-4.1, on key reasoning benchmarks.

The findings suggest that smarter evaluation and adaptation strategies may unlock powerful reasoning abilities even in smaller models. Researchers say the approach could speed AI deployment across robotics, healthcare, and autonomous systems.

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