WordPress has released new guidelines to shape how AI is used across plugins, themes, documentation and media assets. The framework focuses on transparency, accountability and maintaining the project’s open source foundations.
Contributors remain fully responsible for AI-assisted work and are expected to disclose meaningful AI use during submissions. Reviewers are encouraged to assess such contributions with awareness of how automated tools influenced the output.
Strong emphasis is placed on licensing, with all AI-generated material required to remain compatible with GPLv2 or later. Tools that restrict redistribution or reproduce incompatible code are explicitly ruled out.
The guidance also targets so-called AI slop, including untested code, fabricated references and unnecessarily complex solutions. Maintainers are authorised to reject low-quality submissions that lack apparent human oversight.
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A major international AI safety report warns that AI systems are advancing rapidly, with sharp gains in reasoning, coding and scientific tasks. Researchers say progress remains uneven, leaving systems powerful yet unreliable.
The report highlights rising concerns over deepfakes, cyber misuse and emotional reliance on AI companions in the UK and the US. Experts note growing difficulty in distinguishing AI generated content from human work.
Safeguards against biological, chemical and cyber risks have improved, though oversight challenges persist in the UK and the US. Analysts warn advanced models are becoming better at evading evaluation and controls.
The impact of AI on jobs in the UK and the US remains uncertain, with mixed evidence across sectors. Researchers say labour disruption could accelerate if systems gain greater autonomy.
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About 50 residents of Quilicura, an urban community near Chile’s capital, spent a day answering thousands of questions and creating hand-drawn images through a human-powered chatbot called Quili.AI, designed to demonstrate alternatives to instant AI responses and raise awareness of the hidden environmental toll of AI infrastructure.
Participants responded to more than 25,000 global requests, often taking minutes for answers and sketches that would be instantaneous with commercial AI models.
The project, organised by environmental group Corporación NGEN, emphasised that AI systems, especially data centres that host them, consume large amounts of electricity and water, with Quilicura itself becoming a hub for data centres run by major cloud providers.
Organisers said the human chatbot wasn’t an argument against AI’s value but a way to prompt reflection on responsible and sustainable use, especially in regions facing water scarcity and climate stresses like drought and wildfires.
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At the Summit for Clinical Operations Executives (SCOPE) 2026, major players in life sciences showcased artificial intelligence-enabled systems built to accelerate and optimise oncology clinical trials.
Massive Bio’s TrialRelay uses AI routing (“TrialRouter”) to orchestrate the enrolment process, reducing the risk that patients are lost in the referral pipeline after being matched to a study.
ConcertAI’s Accelerated Clinical Trials (ACT) platform, powered by its proprietary agentic AI, integrates real-world and proprietary datasets with advanced workflows to shorten trial timelines by 10–20 months, improve study design and reduce costly amendments, helping sponsors and contract research organisations (CROs) bring therapies to patients faster.
AI adoption in clinical research is rising across recruitment, trial design, data handling and operational forecasting, though integration challenges, regulatory alignment and rapid technological change remain obstacles.
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The EU’s attempt to revise core privacy rules has faced resistance from France, which argues that the Commission’s proposals would weaken rather than strengthen long-standing protections.
Paris objects strongly to proposed changes to the definition of personal data within the General Data Protection Regulation, which remains the foundation of European privacy law. Officials have also raised concerns about several more minor adjustments included in the broader effort to modernise digital legislation.
These proposals form part of the Digital Omnibus package, a set of updates intended to streamline the EU data rules. France argues that altering the GDPR’s definitions could change the balance between data controllers, regulators and citizens, creating uncertainty for national enforcement bodies.
The national government maintains that the existing framework already includes the flexibility needed to interpret sensitive information.
A disagreement that highlights renewed tension inside the Union as institutions examine the future direction of privacy governance.
Several member states want greater clarity in an era shaped by AI and cross-border data flows. In contrast, others fear that opening the GDPR could lead to inconsistent application across Europe.
Talks are expected to continue in the coming months as EU negotiators weigh the political risks of narrowing or widening the scope of personal data.
France’s firm stance suggests that consensus may prove difficult, particularly as governments seek to balance economic goals with unwavering commitments to user protection.
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Toronto’s notoriously congested traffic, among the worst in North America, with drivers spending an average of about 100 hours in traffic annually, continues to frustrate commuters.
Experts and city officials are now considering artificial intelligence-driven traffic signal optimisation as a key tool to improve traffic flows by dynamically adjusting signal timing across the city’s roughly 2,500 intersections.
AI systems could analyse real-time traffic patterns faster and more efficiently than manual control, helping reduce idle time, clear bottlenecks and support transit modes like the Finch West LRT by prioritising movement where needed.
While details of Toronto’s broader congestion management plan are still being finalised, this high-tech approach is being positioned as one of the most promising ways to address chronic gridlock and improve overall mobility.
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Scientists are increasingly applying generative AI models to address complex problems in materials science, such as predicting structures, simulating properties, and guiding the discovery of advanced materials with novel functions.
Traditional computational methods, such as density functional theory, can be slow and resource-intensive, whereas AI-based tools can learn from existing data and propose candidate materials more efficiently.
Early applications of these generative approaches include designing materials for energy storage, catalysis, and electronic applications, speeding up workflows that previously involved large amounts of trial and error.
Researchers emphasise that while AI does not yet replace physics-based modelling, it can complement it by narrowing the search space and suggesting promising leads for experimental validation.
The work reflects a broader trend of AI-augmented science, where machine learning and generative models act as accelerators for discovery across disciplines such as chemistry, physics and bioengineering.
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India has unveiled a plan to offer foreign cloud providers zero taxes on revenues from services sold abroad if workloads are run from Indian data centres until 2047. The move aims to attract AI investment despite power and water shortages.
Major US tech companies, including Google, Microsoft and Amazon, have pledged billions of dollars to expand AI-focused data centres in India. Domestic operators are also increasing capacity, with large projects announced in Andhra Pradesh and other states.
The government has boosted incentives for electronics and semiconductor manufacturing, critical minerals, and cross-border e-commerce. These measures aim to integrate India more deeply into global technology supply chains.
Analysts warn that execution risks remain, including energy shortages, land access and regulatory hurdles. Observers say the tax holiday and incentives reflect a strategic bet on establishing India as a global hub for AI and cloud computing.
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Social media platforms are increasingly filled with AI-generated slop created to maximise engagement. The rapid spread has been fuelled by easy access to generative tools and algorithm-driven promotion.
Users across major platforms are pushing back, frequently calling out fake or misleading posts in comment sections. In many cases, criticism of AI slop draws more attention than the original content.
Technology companies acknowledge concerns about low-quality AI media but remain reluctant to impose strict limits. Platform leaders argue that new formats are often criticised before gaining wider acceptance.
Researchers warn that repeated exposure to AI slop may contribute to what they describe as ‘brain rot’, reducing attention and discouraging content verification. The risk becomes more serious when fabricated visuals shape public opinion or circulate as news.
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A leading British think tank has urged the government to introduce ‘nutrition labels’ for AI-generated news, arguing that clearer rules are needed as AI becomes a dominant source of information.
The Institute for Public Policy Research said AI firms are increasingly acting as new gatekeepers of the internet and must pay publishers for the journalism that shapes their output.
The group recommended standardised labels showing which sources underpin AI-generated answers, instead of leaving users unsure about the origin or reliability of the material they read.
It also called for a formal licensing system in the UK that would allow publishers to negotiate directly with technology companies over the use of their content. The move comes as a growing share of the public turns to AI for news, while Google’s AI summaries reach billions each month.
IPPR’s study found that some AI platforms rely heavily on content from outlets with licensing agreements, such as the Guardian and the Financial Times, while others, like the BBC, appear far less often due to restrictions on scraping.
The think tank warned that such patterns could weaken media plurality by sidelining local and smaller publishers instead of supporting a balanced ecosystem. It added that Google’s search summaries have already reduced traffic to news websites by providing answers before users click through.
The report said public funding should help sustain investigative and local journalism as AI tools expand. OpenAI responded that its products highlight sources and provide links to publishers, arguing that careful design can strengthen trust in the information people see online.
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