The United Nations is urging AI companies to disclose the full environmental cost of their technologies, arguing that the industry’s impact extends far beyond electricity consumption and carbon emissions.

Why The UN Is Concerned

The warning follows the publication of a new report by the United Nations University Institute for Water, Environment and Health (UNU-INWEH), which argues that AI’s environmental footprint is being measured too narrowly.

While public debate has largely focused on carbon emissions and electricity consumption, the report says AI also has substantial water and land footprints that are often overlooked. Cooling data centres, generating electricity and building the infrastructure needed to support AI all consume natural resources on a scale that is growing rapidly.

The report concludes that greater transparency is urgently needed so governments, investors and the public can properly assess AI’s true environmental impact.

What The Numbers Show

According to the report, global data centres could consume around 945 terawatt-hours of electricity every year by 2030. That is almost three times the combined annual electricity consumption of Pakistan, Bangladesh and Nigeria, countries with a combined population of more than 650 million people.

Electricity, however, is only part of the story. The researchers estimate that AI-related electricity generation and cooling could require around 9.3 trillion litres of water each year by the end of the decade, equivalent to the basic annual domestic water needs of approximately 1.3 billion people in Sub-Saharan Africa.

The associated land footprint could exceed 14,500 square kilometres, roughly twice the size of the Jakarta metropolitan area.

Professor Kaveh Madani, Director of UNU-INWEH and one of the report’s authors, said: “This report is not a case against artificial intelligence… It is a call for using it responsibly and addressing its unintended impacts proactively to make it sustainable and equitable.”

Looking Beyond Carbon

One of the report’s central arguments is that measuring AI sustainability through carbon emissions alone can be misleading.

Researchers found that different energy sources can have very different environmental consequences. For example, an energy source that produces fewer greenhouse gas emissions may require considerably more water or land.

Lead author of the report, Dr Miriam Aczel, said: “If we keep judging AI sustainability by carbon alone, we might think that renewables make AI infrastructure clean, but that is solving one problem while creating other problems, often in places that didn’t ask for it.”

The report therefore calls for AI companies to publish standardised information covering carbon, water and land use together, allowing meaningful comparisons between different technologies and data centres.

Daily AI Use Is Driving Demand

The report also challenges another widely held assumption. Many people associate AI’s environmental impact with training large language models. However, the researchers estimate that running AI systems after they have been deployed, known as inference, now accounts for around 80 to 90 per cent of total AI energy consumption.

As millions of people generate text, images and videos every day, those routine interactions collectively consume far more electricity than the original training process.

The report also highlights how energy requirements vary dramatically depending on the task being performed. Generating an AI image can require around 1,450 times more energy than a simple text classification task, while AI video generation demands considerably more still.

A Wider Sustainability Challenge

The United Nations also highlights broader environmental issues extending beyond electricity use. For example, by 2030, AI infrastructure could generate up to 2.5 million tonnes of electronic waste every year, while demand for critical minerals used in processors, batteries and other hardware continues to increase.

The report argues that the environmental burdens associated with AI are often concentrated in communities hosting data centres, mining operations and electronic waste processing, while many of the economic benefits flow elsewhere.

UN Under-Secretary-General and United Nations University Rector Professor Tshilidzi Marwala said: “AI can certainly advance prosperity and human well-being. Whether it does so equitably is now a governance question, not a technical one.”

Towards More Responsible AI

Rather than arguing against AI, the report proposes what it describes as a “responsible AI ecosystem” built around six principles: transparency, efficiency by design, equity, lifecycle responsibility, global cooperation and sustainable use.

Governments are encouraged to incorporate AI infrastructure into energy, water and land-use planning, while AI developers are urged to improve efficiency and publish consistent environmental reporting.

The report also suggests organisations deploying AI should consider selecting the least resource-intensive model capable of completing a particular task rather than automatically using the largest available systems.

What Does This Mean For Your Organisation?

For organisations adopting AI, the UN’s report highlights how sustainability is becoming an increasingly important part of AI governance rather than simply a data centre issue.

Many businesses are already assessing suppliers on environmental, social and governance criteria. As AI becomes embedded across more business applications, organisations may increasingly expect technology providers to disclose not only carbon emissions but also water use, land impacts and other environmental costs associated with their AI services.

It now looks as though transparency is likely to become just as important as technical performance. As businesses invest more heavily in AI, questions about how those systems are powered, where they operate and what resources they consume are likely to become an increasingly important part of procurement, sustainability reporting and corporate responsibility. The United Nations is making it clear that measuring AI’s environmental impact should no longer stop at carbon emissions alone.

ChatGPT’s new Images 2.0 tool makes it faster and easier to create, edit, and refine high-quality visuals, giving you more control, improved accuracy, and far more realistic results.

[Note – To Watch This Video without glitches/interruptions, It may be best to download it first]

If a Windows update, driver, application or settings change leaves your PC unstable or unable to start properly, Windows 11 now includes a built-in Point-in-Time Restore feature that can roll your computer back to an earlier working state in just a few minutes.

Unlike the older System Restore feature, Point-in-Time Restore automatically creates full restore points every 24 hours by default. These include Windows, installed applications, settings and local files, making it much easier to recover from software problems without rebuilding your PC.

To Check Whether The Feature Is Enabled

– Open “Settings”.

– Select “System > Recovery > Point-in-Time Restore”.

– Confirm that the feature is turned on. On many Windows 11 Home and Pro PCs with drives of 200GB or larger, it is enabled automatically.

If Your PC Develops A Serious Problem

– Restart your PC into the “Windows Recovery Environment”.

– Select “Troubleshoot > Point-in-Time Restore”.

– Enter your “BitLocker recovery key” if prompted.

– Choose a restore point created before the problem occurred.

– Confirm the restore and allow Windows to roll your PC back to that earlier state.

Before using Point-in-Time Restore, remember that any applications, settings or local files created after the selected restore point will be removed. Files stored in OneDrive or another cloud service remain safe, although they may need to synchronise again afterwards.

Point-in-Time Restore provides an excellent safety net when updates or software changes go wrong, but it’s still important to keep your important files backed up to the cloud or another secure location.

Children under the age of 16 will be banned from using major social media platforms in the UK from Spring 2027 under government plans that represent one of the most significant attempts yet to reshape how young people interact with the online world.

What Has Been Announced?

Before his resignation, Sir Keir Starmer had confirmed that the government intends to introduce legislation before Christmas that will prevent under-16s from accessing a range of major social media services.

The ban is expected to come into force in Spring 2027 and will apply to platforms including TikTok, Instagram, Facebook, Snapchat, YouTube and X. Messaging services such as WhatsApp and Signal will not be included.

Announcing the plans, Starmer said: “That’s why we’re going further than any country in the world by banning social media for under-16s and putting wider protections in place to give kids their childhood back.”

The government has described the move as a “line in the sand” that will create “a new normal for future generations”.

The UK Is Going Further Than A Simple Ban

The proposal extends beyond simply preventing children from creating social media accounts.

The government has also announced restrictions on high-risk online features, including livestreaming and communication with strangers. These restrictions will apply not only to social media platforms but also to a wider range of online services, including gaming sites.

Importantly, some protections will remain switched on by default for 16 and 17-year-olds. Ministers say this is intended to avoid what they describe as a “cliff-edge at 16”, where protections would otherwise disappear overnight.

The government is also examining possible restrictions on infinite scrolling and overnight social media use for under-18s, with further details expected later this year.

Meanwhile, so-called AI “romantic companion” chatbots designed to simulate intimate or sexual relationships will be restricted to adults, while similar intimate AI functions will be limited for under-18s.

Why Is The Government Doing This?

The announcement follows a major public consultation that attracted more than 116,000 responses from parents, children and experts.

According to the government’s findings, nine in ten parents supported a social media ban for under-16s, while two-thirds of young people agreed that children under 16 should not be allowed to use at least some social media platforms.

The government argues that algorithmic feeds, real-time content, cyberbullying, harmful material, addictive platform design and online exploitation are creating risks that existing safeguards have failed to address.

Technology Secretary Liz Kendall said: “Today we take a bold and significant step towards creating a safer, healthier life online for our children and future generations.”

She also argued that technology firms had failed to act voluntarily, stating: “Tech companies have had countless opportunities to keep children safe, yet they have failed to act.”

How Will The Ban Be Enforced?

One of the biggest challenges will be ensuring that under-16s cannot simply bypass the restrictions.

The government says it intends to introduce stronger age assurance requirements and has asked Ofcom to carry out a rapid review into the most effective ways of verifying whether someone is over 16.

Officials have indicated that a range of methods could be used, including facial age estimation technology, identity verification and other forms of age assurance. Many adults may not need additional checks if their accounts are already linked to verified payment methods or age-verified accounts.

The government also says it is learning from Australia’s experience, where social media restrictions have already been introduced but enforcement has proved challenging.

Questions Remain

Not everyone supports the plans. For example, Meta, Snapchat and YouTube have all expressed concerns that blanket bans could push young people towards less regulated services that may be harder to supervise.

YouTube described itself as “a vital resource for young people, educators and parents”, while Meta warned that restrictions could risk isolating teenagers from online communities and information.

Privacy advocates have also raised concerns about age verification technologies, particularly where facial analysis or identity checks may be required to access online services.

Critics also point to evidence from Australia suggesting that many children have continued accessing social media despite restrictions, highlighting the practical difficulties involved in enforcing such bans.

Part Of A Global Trend

The UK’s decision reflects a broader international movement towards tighter controls on children’s access to social media.

Australia became the first country to introduce a nationwide under-16 social media ban, while countries including France, Spain, Greece, Denmark, Canada, Indonesia, Malaysia and others are either introducing similar measures or actively considering them.

Growing concerns about online harms, mental health, addictive platform design, cyberbullying and child exploitation are prompting governments around the world to reconsider the balance between online freedom and child protection.

What Does This Mean For Your Business?

For businesses, the immediate impact may be limited, but the wider significance is substantial.

The proposals signal a growing willingness by governments to intervene directly in how digital platforms operate, particularly where child safety, wellbeing and online harms are concerned. Social media firms, gaming platforms, AI developers and technology providers may all face increasing regulatory scrutiny over the coming years.

The plans also highlight the growing importance of age verification, digital identity, online safety and responsible technology design. Organisations developing online services may find that demonstrating effective safeguards becomes just as important as launching new features.

More broadly, the announcement reflects a wider change in how policymakers view digital platforms. For many years, governments largely relied on technology companies to regulate themselves. The UK’s proposed ban suggests that approach is increasingly being replaced by direct intervention when policymakers believe public safety concerns outweigh the benefits of unrestricted access.

A reported attempt by the UK government to secure continued access to Anthropic’s most advanced AI models has highlighted how dependent many countries have become on frontier AI systems developed and controlled overseas.

What Happened?

The story centres on Claude Fable 5 and Claude Mythos 5, two of Anthropic’s most capable AI models.

Earlier this month, the US Commerce Department reportedly instructed Anthropic to suspend access to both systems following concerns about a technique that could be used to identify software vulnerabilities. The move followed reports that government officials had been alerted to a potential jailbreak affecting the models.

The restrictions quickly became an international issue because Anthropic’s most advanced systems are used by organisations far beyond the United States.

UK Asked For Exemption

Reports indicate that the UK government subsequently sought continued access to the models. However, no exemption was granted and the restrictions remained in place, leaving British users affected alongside other international customers.

Why Were The Models Restricted?

The restrictions stem from a disagreement about the risks posed by advanced AI systems with strong cyber security capabilities.

According to reports, researchers demonstrated a way of prompting Fable 5 to identify software vulnerabilities within computer code. Concerns were raised that such capabilities could potentially be used to support cyber attacks as well as cyber defence.

Anthropic strongly disagrees with that assessment. The company says the technique exposed only a limited number of previously known vulnerabilities and argues that similar capabilities already exist in other leading AI systems. Anthropic has also warned that applying this standard across the industry could severely restrict the deployment of future frontier AI models.

The dispute reflects a broader challenge facing policymakers. The same AI systems that can help defenders find and fix vulnerabilities can also potentially be used by attackers to identify weaknesses more quickly.

Why The UK Became Involved

The incident has drawn attention to the UK’s reliance on foreign AI providers.

Many British organisations increasingly use frontier AI models for software development, cyber security, research, data analysis, and operational tasks. Access to those capabilities is largely controlled by a small number of US companies.

Reports suggest that organisations in sectors including finance, healthcare, research, and government were affected when Anthropic’s models became unavailable.

The situation has also raised wider national security questions.

UK AI minister Kanishka Narayan reportedly highlighted the growing importance of advanced AI systems in areas such as cyber security, drones, and defence technologies, arguing that access to frontier AI is increasingly becoming a strategic issue rather than simply a commercial one.

Cyber Security Industry Pushback

The restrictions have generated significant opposition from within the cyber security community, where many experts argue that advanced AI models are becoming increasingly important defensive tools. For example, more than 80 cyber security leaders and researchers have reportedly signed an open letter calling for the measures to be reversed, including senior figures from major cyber security firms and technology companies.

Their concern is that security teams are already using frontier AI systems to identify software vulnerabilities, analyse malware, generate detection rules, and accelerate security research. From their perspective, restricting access to powerful AI models may reduce the ability of defenders to find and fix weaknesses before attackers can exploit them.

Critics also argue that determined attackers are unlikely to be deterred by the restrictions, given the growing availability of alternative frontier models, open-source systems, and overseas providers. The debate therefore centres on whether limiting access to advanced AI genuinely improves security or simply changes who is able to use the technology and for what purpose.

The Growing Case For Sovereign AI

One of the most important consequences of the dispute may be renewed interest in sovereign AI.

The term refers to a country’s ability to develop, host, control, or guarantee access to strategically important AI capabilities without relying entirely on foreign providers.

The UK has already launched a £500 million Sovereign AI Fund and other initiatives designed to strengthen domestic AI capabilities. The Anthropic restrictions are likely to be viewed by supporters of those programmes as evidence that greater technological independence may be necessary.

Similar conversations are now taking place across Europe, Canada, India, and other regions concerned about becoming dependent on a small number of foreign AI suppliers.

Why This Matters

The significance of the story extends well beyond Anthropic. For decades, most organisations assumed that software purchased from commercial suppliers would remain available unless a provider discontinued a product or suffered an outage. Advanced AI may not follow the same pattern.

The Anthropic episode demonstrates that frontier AI systems can become entangled in national security concerns, export controls, geopolitical tensions, and government interventions. Access can potentially be affected by decisions taken far beyond the control of the organisations using them.

The incident also illustrates how rapidly AI is moving from being a productivity tool to becoming a strategic technology with implications for economic competitiveness, cyber security, and national resilience.

What Does This Mean For Your Business?

For businesses, the immediate issue is not whether they use Anthropic specifically, but whether they understand their dependence on external AI providers.

Many organisations are integrating AI into software development, customer service, cyber security, research, and business operations. The Anthropic restrictions highlight that access to those capabilities may not always be guaranteed.

The wider lesson is that AI resilience may become as important as AI adoption. Organisations may increasingly need to consider where their AI services come from, what alternatives exist, and how dependent critical processes have become on specific providers.

The dispute also highlights a broader reality. As AI systems become more capable and strategically important, decisions about access may increasingly be influenced by government policy, national security considerations, and international politics as much as by technological innovation itself.

A brain-computer interface developed by researchers at the University of California, Davis, has enabled a man with advanced ALS to communicate with remarkable accuracy, return to full-time employment, and use a computer independently for nearly two years, marking one of the most significant real-world demonstrations of the technology to date.

How The System Works

The breakthrough centres on Casey Harrell, a man living with amyotrophic lateral sclerosis (ALS), a progressive neurological condition that destroys motor neurons and can eventually leave people unable to speak or move.

In 2023, surgeons implanted four microelectrode arrays into the speech motor region of Harrell’s brain. The arrays record neural activity associated with attempted speech, which is then analysed by machine-learning software developed by the UC Davis team.

The system translates those neural signals into phonemes, the basic sounds that make up words, before converting them into complete sentences. The decoded text can then be displayed on screen or spoken aloud using a synthesised version of Harrell’s voice from before ALS affected his speech.

According to the research paper published in Nature Medicine, the system achieved more than 99 per cent word accuracy during formal testing using a vocabulary of 125,000 words. Over nearly two years of real-world use, Harrell communicated more than 183,000 sentences, totalling almost two million words.

Moving Beyond The Laboratory

What makes the achievement particularly significant is that the technology was used independently at home rather than under constant supervision from researchers.

Many previous brain-computer interface studies have demonstrated impressive results in controlled laboratory settings. However, practical day-to-day use has remained a major challenge.

The UC Davis team reported that Harrell used the system for more than 3,800 hours over a 19-month period and operated it without researchers being present. After initial setup by trained care partners, he was able to communicate, browse the internet, send messages, participate in video calls, and control a computer cursor using only neural signals.

The researchers described this as one of the key barriers to real-world adoption that the project has now overcome.

In the paper, they wrote that the results demonstrate “that intracortical BCIs have the potential to support independent use in the home, marking a critical step toward practical assistive technology for people with severe motor impairment.”

Helping Someone Return To Work

The technology’s impact extends beyond technical performance metrics.

Despite being paralysed and unable to speak naturally, Harrell has returned to full-time employment as an environmental advocate while using the system. Researchers reported that he used the brain-computer interface as his primary method of communication, preferring it to previous assistive technologies.

The study states that the system enabled him to maintain “full-time employment” while independently managing professional and personal communications.

Harrell also highlighted the personal benefits of the technology. Speaking through the brain-computer interface, he said: “It is a life that is more full of dynamic action and with friends and family, with colleagues, and it is something that allows me to communicate more in my natural way of communicating than any other technology that I have experienced.”

Why AI Is Central To The Breakthrough

Although brain implants often attract the headlines, the most important innovation may actually be the software.

The hardware used in the project is based on existing microelectrode technology. The major advance comes from the AI-powered decoding system developed by the UC Davis team.

Their software platform, known as BRAND, uses machine-learning algorithms to interpret complex neural signals in real time and convert them into meaningful language. Researchers continually refined the algorithms during the study to improve accuracy, stability, and ease of use.

The research paper notes that the latest transformer-based decoder achieved a state-of-the-art word accuracy rate of 99.2 per cent while requiring little or no daily recalibration.

Important Limitations Remain

Despite the encouraging results, it should be noted here that the technology remains in the experimental stage.

The study involved only a single participant, and researchers acknowledge that it is not yet known how widely the results will apply to other patients with ALS or different neurological conditions.

The system also still relies on external computers, wired connections, and trained carers to connect the equipment each day. Widespread clinical use would require further miniaturisation, regulatory approval, and substantial reductions in cost.

The researchers themselves note that “future work will be needed to evaluate wireless or fully implantable systems, minimise setup time and expand access to users with different clinical profiles.”

What Does This Mean For Your Business?

For most organisations, brain-computer interfaces may seem far removed from everyday business concerns. However, the study provides another example of how AI is increasingly moving beyond software applications and becoming integrated with healthcare, assistive technologies, and human-machine interaction.

The achievement also highlights the growing role of AI in solving complex real-world problems that extend well beyond productivity tools and chatbots. In this case, machine learning is helping restore communication, digital access, and employment opportunities for someone who would otherwise face severe limitations.

The technology remains years away from routine commercial deployment, but the results suggest that brain-computer interfaces are beginning to transition from research projects into practical assistive tools. If future studies can replicate these results at scale, they could significantly improve quality of life for people living with ALS, paralysis, and other severe neurological conditions.