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Trump’s AI Accord Puts Big Tech in Charge of Its Own Safety. Is That Enough?

Trump’s AI accord asks major technology companies to strengthen safety measures voluntarily, but critics question whether companies developing powerful AI systems should be allowed to regulate themselves.

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Wooden letter tiles spelling “GUIDE AI” on a table, representing AI governance and safety
The debate over AI safety is increasingly focused on how artificial intelligence should be governed and who should be responsible for regulating it.Image credit:Pexels

The White House has secured a voluntary AI safety pact with six major technology companies. Supporters see it as a way to protect innovation while addressing risks. Critics question whether companies developing increasingly powerful AI should be allowed to police themselves.

US President Donald Trump has brought some of the world’s biggest artificial intelligence companies together around a common promise to make increasingly powerful AI systems safer without putting the brakes on their development.

On September 29, Trump and executives from Google, OpenAI, Anthropic, Meta, Nvidia and xAI signed the White House Accord on Super Intelligence, a voluntary agreement that asks companies to introduce stronger internal controls, external audits and board-level oversight of their AI systems.

But the agreement has also exposed a larger question at the heart of the AI debate: can an industry regulate itself when the companies involved have enormous commercial incentives to keep developing faster?

What does the accord actually promise?

The agreement calls on companies developing frontier AI models to establish robust internal controls to monitor their systems during training and deployment.

Those controls are expected to cover risks including cybersecurity, biosecurity and chemical threats, as well as unintended access by AI systems to technical systems. Companies have also agreed to work with independent external auditors and have their boards review the results of safety evaluations.

The companies will also meet regularly to establish safety standards and best practices.

The catch is that the accord is not legally binding.

Trump described the commitment as “morally binding” and argued that companies have a strong incentive to police themselves because their businesses and reputations are at stake.

The agreement itself leaves open the possibility that some of its measures could eventually be written into law or formal regulations.

Trump’s argument: regulate without slowing innovation

The accord fits with Trump’s broader approach to AI.

His administration has argued that excessive regulation could weaken US technological competitiveness, particularly as Washington sees AI leadership as part of its competition with China.

Trump has therefore favoured industry-led safeguards over a broad new federal regulatory framework. At the White House meeting, he described self-regulation as a way of addressing safety concerns while allowing American AI development to continue at speed.

There is also support for this approach within the technology industry.

Trump,safety,ai

Representational image.Image credit:Pexels

Nvidia CEO Jensen Huang has argued that innovation and safety do not have to be opposing goals. Supporters of the accord say companies developing frontier systems are already investing heavily in testing and safety mechanisms, and that flexible standards can evolve more quickly than government legislation.

Critics see a problem with companies marking their own homework

The strongest criticism is about enforcement.

Because the accord is voluntary, it does not establish a clear penalty if a company fails to follow its commitments. Nor does it establish a government regulator responsible for independently verifying whether the promised safeguards are actually working.

Democratic Senator Mark Warner has called for mandatory testing, evaluation and incident-reporting requirements for the most advanced AI systems. His argument is that the companies building powerful AI should not be left to determine the rules governing their own technology.

AI researchers have raised a similar concern. Toby Walsh of the UNSW AI Institute questioned whether companies that have commercial incentives to move quickly should be trusted to assess their own risks.

The Council on Foreign Relations has also argued that the safeguards in the accord are sensible but ultimately limited because companies are not compelled to adopt them.

The bigger question is who gets to set the rules

The disagreement is therefore not simply about whether AI needs safety measures. There is broad recognition that increasingly capable systems require safeguards.

The dispute is over who should enforce them.

Trump’s model places much of that responsibility with the companies developing frontier AI. Critics want a stronger role for governments, independent regulators and international institutions.

The debate is becoming more urgent as AI systems are used in cybersecurity, scientific research, government services and other sensitive areas. Recent incidents involving AI systems gaining unintended access to computer systems have also intensified concerns about whether existing safeguards can keep pace with technological development.

The White House accord therefore represents a significant shift in the conversation, but not necessarily a resolution.

It acknowledges that powerful AI needs stronger safety controls while leaving the companies themselves largely responsible for implementing them.

EP Staff is the editorial team at EdPublica, an independent media organisation focused on science, education, environment and public policy. The team produces evidence-based news, features, explainers and analysis on issues that shape society and everyday life.

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India–Poland to Pursue Joint Research in AI, Semiconductors and Quantum Technology

India and Poland have agreed to pursue collaborative research in AI, semiconductors and quantum technologies, while identifying battery recycling, rare-earth processing and higher education as areas for closer cooperation.

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Indian and Polish national flags flying side by side against a blue sky.
India and Poland are expanding cooperation in AI research, clean energy, semiconductors and higher education. Representational image. Image credit: Aleksandra Aleshchenko/ Pexels

India and Poland have agreed to pursue collaborative research in artificial intelligence (AI), semiconductors and quantum technologies, while identifying battery recycling and rare-earth mineral refining as potential areas of cooperation. India-Poland commitments were outlined during Polish Prime Minister Donald Tusk’s official visit to India from October 21 to 23, 2026.

The joint statement also calls for stronger partnerships between universities, research institutions, startups and businesses in both countries. While the governments have identified these areas for collaboration, the statement does not announce specific research projects, dedicated funding or participating institutions.

AI, Semiconductors and Quantum Technologies

The two governments agreed to undertake collaborative research in AI, semiconductors and quantum technologies, and to encourage closer cooperation between their research institutions and innovation ecosystems. They also agreed to strengthen startup partnerships.

The statement identifies AI and digital technologies as tools for improving productivity, economic growth and public service delivery. However, it does not specify the research questions the countries intend to pursue, the institutions that will lead the work or a timeline for launching joint projects.

Space technology is another area identified for cooperation. Both sides called for stronger institutional and industry-level engagement to identify specific opportunities. No joint space mission or new space research programme was announced in the statement.

Battery Recycling and Rare-earth Processing

India and Poland identified battery recycling and rare-earth mineral refining as potential areas for cooperation in the circular economy. They also highlighted geology, mining and critical minerals, with a memorandum of understanding on the sector still under negotiation. The focus on battery recycling concerns the recovery of materials from used batteries for possible reuse. Rare-earth processing, meanwhile, is relevant to industries that depend on these materials for components used in electronics and other advanced technologies.

The joint statement does not identify the battery chemistries or minerals to be prioritised, nor does it set recycling targets or announce a joint processing facility. The two countries also called for closer cooperation in clean energy, sustainable technologies and climate-resilient development. They linked greater use of domestically produced clean energy to energy security, climate protection and industrial competitiveness.

India welcomed Poland’s announcement that it would join the Coalition for Disaster Resilient Infrastructure. It also invited Poland to join the International Solar Alliance and the Global Biofuels Alliance. These announcements concern different stages of engagement: Poland announced its intention to join the disaster-resilience coalition, while membership of the two energy alliances was an invitation from India.

Higher Education and Academic Exchange

The joint statement calls for deeper partnerships between Indian and Polish higher education institutions, including student and faculty exchanges and collaborative research. It also notes Poland’s longstanding academic interest in Indology and Sanskrit, the Indian Council for Cultural Relations Chair of Indian Studies at Jagiellonian University in Kraków, and the presence of Polish-language teachers at Indian universities.

An agreement on cooperation in culture, science and higher education is expected to be concluded soon. The statement does not provide details of its proposed provisions or identify universities that will participate in new exchange programmes.

The emphasis on academic partnerships accompanies the proposed research collaboration in AI, semiconductors and quantum technologies. Whether these tracks will be linked through joint university projects or researcher exchanges remains unspecified.

India-Poland What Remains Open

The joint statement sets out different levels of commitment. Collaborative research in AI, semiconductors and quantum technologies is an agreed objective. Battery recycling and rare-earth refining are identified as opportunities, while the memorandum covering geology, mining and critical minerals remains under negotiation. The agreement on culture, science and higher education is also yet to be concluded.

These distinctions matter when assessing what the visit has delivered for science and technology. The governments have identified areas for cooperation, but the statement does not establish project budgets, implementation schedules or measurable research targets.

The immediate outcome is a stated framework for closer engagement across advanced technology, energy and higher education. Further official agreements and project announcements will be needed to establish the scale and practical direction of that cooperation.

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AI Models Could Soon Spread Across Smart Devices, Raising Cybersecurity Fears

Anthropic’s experiments highlight how AI self-replication could create new cybersecurity risks, allowing malicious systems to spread across internet-connected devices.

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Smartphone displaying a VPN connection, illustrating digital security concerns surrounding AI-powered cyberattacks and connected devices.
A VPN can encrypt internet traffic, but protecting connected devices against emerging AI-driven cyber threats also requires secure software and regular updates. Representational image. Image credit: Dan Nelson/ Pexels

Artificial intelligence (AI) models could soon spread from one internet-connected device to another, potentially creating networks of compromised devices that carry out cyberattacks with limited human involvement. The warning from AI company Anthropic highlights a possible new challenge for cybersecurity as AI systems become capable of performing increasingly complex tasks.

In experiments, Anthropic found that AI models with 30 billion parameters or fewer could already perform many of the individual tasks needed to copy and spread themselves. However, the models struggled to complete the entire process reliably. The findings point to a potential threat, although they do not establish that fully self-replicating AI networks are already operating in the real world.

How AI could spread through smart devices

Many everyday devices, including smart televisions, security cameras and household appliances, connect to the internet. Internet of Things (IoT) devices present a particular concern because many connect directly to networks while receiving limited security attention from users. Weak passwords, outdated software and unpatched vulnerabilities can leave devices exposed to remote exploitation.

Laptop, smartphones, tablet and other internet-connected electronic devices arranged on a desk, illustrating the growing network of devices potentially exposed to AI-driven cybersecurity threats.
As more devices connect to the internet, security vulnerabilities in everyday technology could provide entry points for AI-assisted cyberattacks and the spread of malicious software. Representational iamge. Image credit: Pixabay

Once compromised, a device can become part of a botnet — a network of devices secretly controlled by attackers. Such networks have long been used to spread harmful software, send spam messages and overwhelm websites with large volumes of unwanted traffic.

AI could make these attacks easier to carry out. A malicious AI system might help identify vulnerable devices, exploit security weaknesses and use compromised devices to reach others. Anthropic’s experiments examined whether an AI agent could combine the computing power of inexpensive, internet-connected devices to run other AI models. If such a process becomes reliable, attackers could potentially use large numbers of ordinary devices to support their operations.

Cybersecurity: Why these networks are difficult to stop

A major concern is that a botnet can operate across thousands of devices in different locations. Shutting down one infected device may not stop the others from continuing to operate.

For example, if a security camera is compromised, its owner may not immediately notice anything unusual. The camera could continue recording while its computing resources are used for activities the owner never authorised. If similar weaknesses exist in other devices, attackers could build a much larger network.

AI-assisted attacks could become harder to manage if systems learn to carry out several steps automatically, reducing the need for attackers to control every action themselves. However, Anthropic’s findings do not show that AI can yet carry out this entire process consistently without assistance.

Securing AI and connected devices

The warning raises questions about how AI developers can prevent their models from being used to exploit computer systems. It also draws attention to the security of the devices people bring into their homes.

Manufacturers can reduce risks by fixing software vulnerabilities, providing regular security updates and strengthening password and access protections. Users can help by changing default passwords, installing updates and replacing devices that no longer receive security support.

AI developers, meanwhile, need to test whether their systems can be misused to automate cyberattacks. The immediate concern is not that every smart device will become a threat. It is that weaknesses already present in internet-connected devices could become easier to exploit as AI gains the ability to perform complex tasks with less human direction.

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Thorium-229 Nuclear Clock Opens New Way to Probe Dark Matter

Scientists have demonstrated a working thorium-229 nuclear clock, opening new possibilities for precision timekeeping and research into dark matter.

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Scientific illustration of a thorium atom showing its nucleus at the centre and electrons arranged in concentric shells.
An illustration of a thorium atom. Researchers are studying the thorium-229 isotope to develop nuclear clocks that could advance precision timekeeping and tests of fundamental physics.Image credit:Pixabay

Scientists have demonstrated a working nuclear clock based on thorium-229, an advance that could open new possibilities for precision timekeeping and the search for dark matter. Unlike conventional atomic clocks, which measure transitions involving electrons, the device uses an energy transition inside an atomic nucleus. The clock operates with thorium-229 nuclei embedded in a small crystal at room temperature, offering a potential route towards compact and highly sensitive timekeeping technology.

The findings, published in Nature demonstrate how a laser can be continuously stabilised using the nuclear transition itself. The researchers also used the device to investigate whether dark matter might produce detectable changes in fundamental physical quantities.

From atomic transitions to the atomic nucleus

Modern atomic clocks measure the frequency of radiation associated with transitions between energy levels in atoms or ions. Because these frequencies are highly stable, they provide precise standards for measuring time and testing physical theories.

The proposed nuclear clock uses thorium-229, an isotope with an unusually low-energy nuclear transition that can be excited using ultraviolet light. Researchers have explored this possibility for decades because nuclear transitions are expected to be less sensitive to some external disturbances than electronic transitions.

In the new experiment, the researchers embedded thorium-229 nuclei in a millimetre-sized calcium fluoride crystal. The device operated at approximately room temperature, around 294.7 kelvin. A laser emitting radiation at a wavelength of 148 nanometres was used to probe the nuclear transition.

A central feature of the experiment was its feedback system. The researchers measured how much laser light the nuclei absorbed and used the resulting signal to correct the laser frequency. This allowed the nuclear transition to serve as the reference for stabilising the laser, rather than relying entirely on an external reference.

Ytterbium Optical Lattice Clock purple and green light

A ytterbium optical lattice clock at NMIJ, National Metrology Institute of Japan used to measure International Atomic Time (TAI).Image credi:Wikimedia commons

The team also compared the nuclear clock with an established ytterbium-ion optical clock. This comparison helped researchers assess the new device’s frequency stability and look for possible changes in the thorium transition.

A new tool in the search for dark matter

Beyond timekeeping, the clock offers a way to investigate possible changes in fundamental constants of nature. Some theoretical models propose that ultralight dark matter could cause these constants to vary over time, producing small changes in the frequencies measured by precision clocks.

The researchers compared the thorium clock’s frequency with that of the ytterbium reference over approximately 23 hours. They searched for periodic fluctuations and gradual drifts that could indicate such changes.

The experiment found no statistically significant periodic signal within the range examined. Instead, the measurements placed new limits on certain interactions between ultralight dark matter and ordinary matter. The resulting constraints were competitive with leading atomic-clock measurements for some photon-related interactions and improved previous constraints involving the strong nuclear force.

These results do not establish the existence of dark matter, nor do they rule out all possible models. They demonstrate how a nuclear clock can be used to test predictions that might otherwise be difficult to investigate experimentally.

Challenges remain

The device is still a developing technology. Its performance is limited by factors including laser power, measurement noise and variations in the crystal’s nuclear transition frequency at different locations. The researchers also identified reproducibility between measurements taken on different days as an important limitation.

They suggest that stronger ultraviolet laser sources and improvements to the crystal material could substantially improve the clock’s stability and sensitivity. Their projections indicate that future versions could approach the performance of leading optical atomic clocks while retaining the practical advantages of a solid-state system.

The demonstration marks a significant step towards nuclear clocks that can operate as standalone devices. Further improvements will determine how effectively the technology can support precision timekeeping and searches for new physics.

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