Australia’s social media ban for under-16s is worrying social media companies. According to the country’s eSafety Commissioner, these companies fear a global trend of banning such apps. In Australia, regulators say major platforms reluctantly resisted the policy, fearing that similar rules could spread internationally.
In Australia, the ban has already led to the closure of 4.7 million child-linked accounts across platforms, including Instagram, TikTok and Snapchat. Authorities argue the measures are necessary to protect children from harmful algorithms and addictive design.
Social media companies operating in Australia, including Meta, say stronger safeguards are needed but oppose a blanket ban. Critics have warned about privacy risks, while regulators insist early data shows limited migration to alternative platforms.
Australia is now working with partners such as the UK to push tougher global standards on online child safety. In Australia, fines of up to A$49.5m may be imposed on companies failing to enforce the rules effectively.
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US companies are increasingly adopting Chinese AI models as part of their core technology stacks, raising questions about global leadership in AI. In the US, Pinterest has confirmed it is using Chinese-developed models to improve recommendations and shopping features.
In the US, executives point to open-source Chinese models such as DeepSeek and tools from Alibaba as faster, cheaper and easier to customise. US firms say these models can outperform proprietary alternatives at a fraction of the cost.
Adoption extends beyond Pinterest in the US, with Airbnb also relying on Chinese AI to power customer service tools. Data from Hugging Face shows Chinese models frequently rank among the most downloaded worldwide, including across US developers.
Researchers at Stanford University have found Chinese AI capabilities now match or exceed global peers. In the US, firms such as OpenAI and Meta remain focused on proprietary systems, leaving China to dominate open-source AI development.
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AI has dominated discussions at the World Economic Forum in Davos, where IMF managing director Kristalina Georgieva warned that labour markets are already undergoing rapid structural disruption.
According to Georgieva, demand for skills is shifting unevenly, with productivity gains benefiting some workers while younger people and first-time job seekers face shrinking opportunities.
Entry-level roles are particularly exposed as AI systems absorb routine and clerical tasks traditionally used to gain workplace experience.
Georgieva described the effect on young workers as comparable to a labour-market tsunami, arguing that reduced access to foundational roles risks long-term scarring for an entire generation entering employment.
IMF research suggests AI could affect roughly 60 percent of jobs in advanced economies and 40 percent globally, with only about half of exposed workers likely to benefit.
For others, automation may lead to lower wages, slower hiring and intensified pressure on middle-income roles lacking AI-driven productivity gains.
At Davos 2026, Georgieva warned that the rapid, unregulated deployment of AI in advanced economies risks outpacing public policy responses.
Without clear guardrails and inclusive labour strategies, she argued that technological acceleration could deepen inequality rather than supporting broad-based economic resilience.
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Apple has accused the European Commission of preventing it from implementing App Store changes designed to comply with the Digital Markets Act, following a €500 million fine for breaching the regulation.
The company claims it submitted a formal compliance plan in October and has yet to receive a response from EU officials.
In a statement, Apple argued that the Commission requested delays while gathering market feedback, a process the company says lasted several months and lacked a clear legal basis.
The US tech giant described the enforcement approach as politically motivated and excessively burdensome, accusing the EU of unfairly targeting an American firm.
The Commission has rejected those claims, saying discussions with Apple remain ongoing and emphasising that any compliance measures must support genuinely viable alternative app stores.
Officials pointed to the emergence of multiple competing marketplaces after the DMA entered into force as evidence of market demand.
Scrutiny has increased following the decision by SetApp mobile to shut down its iOS app store in February, with the developer citing complex and evolving business terms.
Questions remain over whether Apple’s proposed shift towards commission-based fees and expanded developer communication rights will satisfy EU regulators.
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OpenAI’s latest GPT-5.2 model has sparked concern after repeatedly citing Grokipedia, an AI-generated encyclopaedia launched by Elon Musk’s xAI, raising fresh fears of misinformation amplification.
Testing by The Guardian showed the model referencing Grokipedia multiple times when answering questions on geopolitics and historical figures.
Launched in October 2025, the AI-generated platform rivals Wikipedia but relies solely on automated content without human editing. Critics warn that limited human oversight raises risks of factual errors and ideological bias, as Grokipedia faces criticism for promoting controversial narratives.
OpenAI said its systems use safety filters and diverse public sources, while xAI dismissed the concerns as media distortion. The episode deepens scrutiny of AI-generated knowledge platforms amid growing regulatory and public pressure for transparency and accountability.
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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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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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A multi-faceted phishing campaign is abusing LinkedIn private messages to deliver weaponised malware using DLL sideloading, security researchers have warned. The activity relies on PDFs and archive files that appear trustworthy to bypass conventional security controls.
Attackers contact targets on LinkedIn and send self-extracting archives disguised as legitimate documents. When opened, a malicious DLL is sideloaded into a trusted PDF reader, triggering memory-resident malware that establishes encrypted command-and-control channels.
Using LinkedIn messages increases engagement by exploiting professional trust and bypassing email-focused defences. DLL sideloading allows malicious code to run inside legitimate applications, complicating detection.
The campaign enables credential theft, data exfiltration and lateral movement through in-memory backdoors. Encrypted command-and-control traffic makes containment more difficult.
Organisations using common PDF software or Python tooling face elevated risk. Defenders are advised to strengthen social media phishing awareness, monitor DLL loading behaviour and rotate credentials where compromise is suspected.
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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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Stanford University, ETH Zurich, and EPFL have launched a transatlantic partnership to develop open-source AI models prioritising societal values over commercial interests.
The partnership was formalised through a memorandum of understanding signed during the World Economic Forum meeting in Davos.
The agreement establishes long-term cooperation in AI research, education, and innovation, with a focus on large-scale multimodal models. The initiative aims to strengthen academia’s influence over global AI by promoting transparency, accountability, and inclusive access.
Joint projects will develop open datasets, evaluation benchmarks, and responsible deployment frameworks, alongside researcher exchanges and workshops. The effort aims to embed human-centred principles into technical progress while supporting interdisciplinary discovery.
Academic leaders said the alliance reinforces open science and cultural diversity amid growing corporate influence over foundation models. The collaboration positions universities as central drivers of ethical, trustworthy, and socially grounded AI development.
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