Artificial intelligence

Workplace deepfake abuse: What employers must know

Deepfake technology—AI-generated videos, images, and audio—has entered the workplace in alarming ways.

Once difficult to produce, deepfakes are now widely accessible and are being used to harass, impersonate, or intimidate employees. These synthetic media attacks can cause deep psychological harm, damage reputations, and expose employers to serious legal risks.

While US federal law hasn’t yet caught up, new legislation like the Take It Down Act and Florida’s Brooke’s Law require platforms to remove non-consensual deepfake content within 48 hours.

Meanwhile, employers could face claims under existing workplace laws if they fail to act on deepfake harassment. Inaction may lead to lawsuits for creating a hostile environment or for negligent oversight.

Most workplace policies still don’t mention synthetic media and something like this creates blind spots, especially during investigations, where fake images or audio could wrongly influence decisions.

Employers need to shift how they assess evidence and protect both accused and accuser fairly. It’s time to update handbooks, train staff, and build clear response plans that include digital impersonation and deepfake abuse.

By treating deepfakes as a modern form of harassment instead of just a tech issue, organisations can respond faster, protect staff, and maintain trust. Proactive training, updated policies, and legal awareness will be crucial to workplace safety in the age of AI.

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ChatGPT and generative AI have polluted the internet — and may have broken themselves

The explosion of generative AI tools like ChatGPT has flooded the internet with low-quality, AI-generated content, making it harder for future models to learn from authentic human knowledge.

As AI continues to train on increasingly polluted data, a loop forms in which AI imitates already machine-made content, leading to a steady drop in originality and usefulness. The worrying trend is referred to as ‘model collapse’.

To illustrate the risk, researchers compare clean pre-AI data to ‘low-background steel’ — a rare kind of steel made before nuclear testing in 1945, which remains vital for specific medical and scientific uses.

Just as modern steel became contaminated by radiation, modern data is being tainted by artificial content. Cambridge researcher Maurice Chiodo notes that pre-2022 data is now seen as ‘safe, fine, clean’, while everything after is considered ‘dirty’.

A key concern is that techniques like retrieval-augmented generation, which allow AI to pull real-time data from the internet, risk spreading even more flawed content. Some research already shows that it leads to more ‘unsafe’ outputs.

If developers rely on such polluted data, scaling models by adding more information becomes far less effective, potentially hitting a wall in progress.

Chiodo argues that future AI development could be severely limited without a clean data reserve. He and his colleagues urge the introduction of clear labelling and tighter controls on AI content.

However, industry resistance to regulation might make meaningful reform difficult, raising doubts about whether the pollution can be reversed.

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Scientists convert brain signals into words using AI

Australian scientists have developed an AI model that converts brainwaves into spoken words and sentences using a wearable EEG cap.

The system, created at the University of Technology Sydney, marks a significant step in communication technology and cognitive care.

The deep learning model, designed by Daniel Leong, Charles Zhou, and Chin-Teng Lin, currently works with a limited vocabulary but has achieved around 75% accuracy. Researchers aim to improve this to 90% by expanding training data and refining brainwave analysis.

Bioelectronics expert Mohit Shivdasani noted that AI now detects neural patterns previously hidden from human interpretation. Future uses include real-time thought-to-text interfaces or direct communication between people via brain signals.

However, breakthrough opens new possibilities for patients with speech or movement impairments, pointing to future human-machine interaction that bypasses traditional input methods.

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Nvidia’s sovereign AI vision gains EU support

Nvidia CEO Jensen Huang’s call for ‘sovereign AI’ is gaining traction among European leaders who want more control over their data and digital future. He argues that nations must develop AI rooted in their own language, culture and infrastructure.

During a recent European tour, Huang unveiled major partnerships and investments European cities, citing the region’s over-reliance on US tech firms. European officials echoed his concerns, with French President Emmanuel Macron and German Chancellor Friedrich Merz supporting national AI initiatives.

The EU plans to build four AI gigafactories, aiming to reduce dependence on US cloud giants and strengthen regional innovation. Nvidia has committed to providing chips for these projects, while startups like Mistral are working to become local leaders in AI development.

Despite enthusiasm, high energy costs and limited resources may hinder Europe’s progress. Industry voices warn that without sustained investment, the region could struggle to match the spending power of US hyperscalers.

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Smart machines, dark intentions: UN urges global action on AI threats

The United Nations has warned that terrorists could seize control of AI-powered vehicles to launch devastating attacks in public spaces. A new report outlines how extremists might exploit autonomous cars and drones to bypass traditional defences.

AI is also feared to be a tool for facial recognition targeting and mass ‘swarm’ assaults using aerial devices. Experts suggest that key parts of modern infrastructure could be turned against the public if hacked.

Britain’s updated counter-terrorism strategy now reflects these growing concerns, including the risk of AI-generated propaganda and detailed attack planning. The UN has called for immediate global cooperation to limit how such technologies can be misused.

Security officials maintain that AI also offers valuable tools in the fight against extremism, enabling quicker intelligence processing and real-time threat identification. Nonetheless, authorities have been urged to prepare for worst-case scenarios involving AI-directed violence.

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Armenia plans major AI hub with NVIDIA and Firebird

Armenia has unveiled plans to develop a $500mn AI supercomputing hub in partnership with US tech leader NVIDIA, AI cloud firm Firebird, and local telecoms group Team.

Announced at the Viva Technology conference in Paris, the initiative marks the largest tech investment ever seen in the South Caucasus.

Due to open in 2026, the facility will house thousands of NVIDIA’s Blackwell GPUs and offer more than 100 megawatts of scalable computing power. Designed to advance AI research, training and entrepreneurship, the hub aims to position Armenia as a leading player in global AI development.

Prime Minister Nikol Pashinyan described the project as the ‘Stargate of Armenia’, underscoring its potential to transform the national tech sector.

Firebird CEO Razmig Hovaghimian said the hub would help develop local talent and attract international attention, while the Afeyan Foundation, led by Noubar Afeyan, is set to come on board as a founding investor.

Instead of limiting its role to funding, the Armenian government will also provide land, tax breaks and simplified regulation to support the project, strengthening its push toward a competitive digital economy.

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Amazon launches AU$ 20 bn investment in Australian solar-powered data centres

Amazon will invest AU$ 20 billion to expand its data centre infrastructure in Australia, using solar and wind power instead of traditional energy sources.

The plan includes power purchase agreements with three utility-scale solar plants developed by European Energy, one of which—Mokoan Solar Park in Victoria—is already operational. The other two projects, Winton North and Bullyard Solar Parks, are expected to lift total solar capacity to 333MW.

The investment supports Australia’s aim to enhance its cloud and AI capabilities. Amazon’s commitment includes purchasing over 170MW of power from these projects, contributing to both data centre growth and the country’s renewable energy transition.

According to the International Energy Agency, electricity demand from data centres is expected to more than double by 2030, driven by AI.

Amazon Web Services CEO Matt Garman said the move positions Australia to benefit from AI’s economic potential. The company, already active in solar projects across New South Wales, Queensland and Victoria, continues to prioritise renewables to decarbonise operations and meet surging energy needs.

Instead of pursuing growth through conventional means, Amazon’s focus on clean energy could set a precedent for other tech giants expanding in the region.

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OpenAI turns to Google Cloud in shift from solo AI race

OpenAI has entered into an unexpected partnership with Google, using Google Cloud to support its growing AI infrastructure needs.

Despite being fierce competitors in AI, the two tech giants recognise that long-term success may require collaboration instead of isolation.

As the demand for high-performance hardware soars, traditional rivals join forces to keep pace. OpenAI, previously backed heavily by Microsoft, now draws from Google’s vast cloud resources, hinting at a changing attitude in the AI race.

Rather than going it alone, firms may benefit more by leveraging each other’s strengths to accelerate development.

Google CEO Sundar Pichai, speaking on a podcast, suggested there is room for multiple winners in the AI sector. He even noted that a major competitor had ‘invited me to a dance’, underscoring a new phase of pragmatic cooperation.

While Google still faces threats to its search dominance from tools like ChatGPT, business incentives may override rivalry.

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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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Taiwan tightens rules on chip shipments to China

Taiwan has officially banned the export of chips and chiplets to China’s Huawei and SMIC, joining the US in tightening restrictions on advanced semiconductor transfers.

The decision follows reports that TSMC, the world’s largest contract chipmaker, was unknowingly misled into supplying chiplets used in Huawei’s Ascend 910B AI accelerator. The US Commerce Department had reportedly considered a fine of over $1 billion against TSMC for that incident.

Taiwan’s new rules aim to prevent further breaches by requiring export permits for any transactions with Huawei or SMIC.

The distinction between chips and chiplets is key to the case. Traditional chips are built as single-die monoliths using the same process node, while chiplets are modular and can combine various specialised components, such as CPU or AI cores.

Huawei allegedly used shell companies to acquire chiplets from TSMC, bypassing existing US restrictions. If TSMC had known the true customer, it likely would have withheld the order. Taiwan’s new export controls are designed to ensure stricter oversight of future transactions and prevent repeat deceptions.

The broader geopolitical stakes are clear. Taiwan views the transfer of advanced chips to China as a national security threat, given Beijing’s ambitions to reunify with Taiwan and the potential militarisation of high-end semiconductors.

With Huawei claiming its processors are nearly on par with Western chips—though analysts argue they lag two to three generations behind—the export ban could further isolate China’s chipmakers.

Speculation persists that Taiwan’s move was partly influenced by negotiations with the US to avoid the proposed fine on TSMC, bringing both countries into closer alignment on chip sanctions.

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