Several major US technology companies have backed Anthropic in its lawsuit challenging the US Department of Defence’s decision to label the AI company a national security ‘supply chain risk’.
Google, Amazon, Apple, and Microsoft have filed legal briefs supporting Anthropic’s attempt to overturn the designation issued by Defence Secretary Pete Hegseth. Anthropic argues the decision was retaliation after the company declined to allow its AI systems to be used for mass surveillance or autonomous weapons.
In court filings, the companies warned that the government’s action could have wider consequences for the technology sector. Microsoft said the decision could have ‘broad negative ramifications for the entire technology sector’.
Microsoft, which works closely with the US government and the Department of Defence, said it agreed with Anthropic’s position that AI systems should not be used to conduct domestic mass surveillance or enable autonomous machines to initiate warfare.
A joint amicus brief supporting Anthropic was also submitted by the Chamber of Progress, a technology policy organisation funded by companies including Google, Apple, Amazon and Nvidia. The group said it was concerned about the government penalising a company for its public statements.
The brief described the designation as ‘a potentially ruinous sanction’ for businesses and warned it could create a climate in which companies fear government retaliation for expressing views.
Anthropic’s lawsuit claims the government violated its free speech rights by retaliating against the company for comments made by its leadership. The dispute escalated after Anthropic declined to remove contractual restrictions preventing its AI models from being used for mass surveillance or autonomous weapons.
The company had previously introduced safeguards in government contracts to limit certain uses of its technology. Negotiations over revised contract language continued for several weeks before the disagreement became public.
Former military officials and technology policy advocates have also filed supporting briefs, warning that the decision could discourage companies from participating in national security projects if they fear retaliation for voicing concerns. The case is currently being heard in federal court in San Francisco.
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A deal valued at up to $600 million will see Netflix acquire InterPositive, the AI filmmaking company founded by actor and director Ben Affleck, according to people familiar with the matter.
The transaction, paid in cash, is expected to become one of the largest acquisitions made by the streaming company. The final upfront amount is reportedly lower, with additional payments tied to performance targets. Netflix has not publicly disclosed the financial terms of the deal.
The acquisition is intended to accelerate the use of AI in film production. InterPositive has developed software tools that enable filmmakers to modify existing footage, including removing unwanted elements or adjusting scene backgrounds. Director David Fincher has already used the technology in work on an upcoming film starring Brad Pitt.
The deal reflects a broader trend among entertainment companies exploring AI technologies to streamline production and improve efficiency. Companies including Netflix and Amazon are experimenting with AI tools in film and television production, while Disney has established a partnership with OpenAI.
The growing use of AI in Hollywood has raised concerns among industry workers. Some fear the technology could reduce jobs or allow studios to use creative work to train AI systems without compensation.
Affleck has said the InterPositive technology is designed to support filmmakers rather than replace them. The system requires directors first to shoot original footage before the software can train on the material. The tools can then assist with editing tasks, but do not generate films independently.
Netflix has traditionally avoided large-scale acquisitions, focusing instead on developing its technology internally. Even so, the purchase of InterPositive signals a step toward strengthening the company’s AI capabilities in film production.
‘The filmmaking process, really, since its inception, has been one long technological progression,’ Affleck said in a video released by Netflix. ‘We’ve always been seeking to make it feel more realistic, more honest, and InterPositive, I hope, is another iteration or step in keeping with that long and storied history.’
Affleck founded InterPositive with backing from investment firm RedBird Capital Partners and began seeking investment in 2025 before the company attracted interest from Netflix.
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The European Parliament has adopted a report urging policymakers to establish a long-term framework protecting copyrighted works used in AI training.
These recommendations aim to ensure that creative industries retain transparency and fair treatment as generative AI technologies expand.
Among the central proposals is the creation of a European register managed by the European Union Intellectual Property Office. The database would list copyrighted works used to train AI systems and identify creators who have chosen to exclude their content from such use.
Lawmakers in the EU are also calling for greater transparency from AI developers, including disclosure of the websites from which training data has been collected. According to the report, failing to meet transparency requirements could raise questions about compliance with existing copyright rules.
The recommendations have received mixed reactions from industry stakeholders.
Organisations representing creators argue that stronger safeguards are necessary to ensure fair remuneration and legal clarity, while technology sector groups caution that additional requirements could create complexity for companies developing AI systems.
The report is not legally binding but signals the political direction of ongoing European discussions on copyright and AI governance.
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Thousands of writers have joined a symbolic protest against AI companies by publishing a book that contains no traditional content.
The work, titled “Don’t Steal This Book,” lists only the names of roughly 10,000 contributors who oppose the use of their writing to train AI systems without their permission.
An initiative that was organised by composer and campaigner Ed Newton-Rex and distributed during the London Book Fair. Contributors include prominent authors such as Kazuo Ishiguro, Philippa Gregory and Richard Osman, along with thousands of other writers and creative professionals.
Campaigners argue that generative AI systems are trained on vast collections of copyrighted material gathered from the internet without authorisation or compensation.
According to organisers, such practices allow AI tools to compete with the creators whose works were used to develop them.
The protest arrives as the UK Government prepares an economic assessment of potential copyright reforms related to AI. Proposals under discussion include allowing AI developers to use copyrighted material unless rights holders explicitly opt out.
Many writers and artists oppose that approach and demand stronger copyright protections. In parallel, the publishing sector is preparing a licensing initiative through Publishers’ Licensing Services to provide AI developers with legal access to books while ensuring authors receive compensation.
The dispute reflects a growing global debate over how copyright law should apply to generative AI systems that rely on massive datasets to develop chatbots and other digital tools.
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YouTube is expanding its likeness-detection technology designed to identify AI-generated deepfakes, extending access to a pilot group of government officials, political candidates, and journalists.
The tool allows participants to detect unauthorised AI-generated videos that simulate their faces and request removal if the content violates YouTube policies. The system builds on technology launched last year for around four million creators in the YouTube Partner Program.
Similar to YouTube’s Content ID system, which detects copyrighted material in uploaded videos, the likeness detection feature scans for AI-generated faces created with deepfake tools. Such technologies are increasingly used to spread misinformation or manipulate public perception by making prominent figures appear to say or do things they never did.
According to YouTube, the pilot programme aims to balance free expression with safeguards against AI impersonation, particularly in sensitive civic contexts.
‘This expansion is really about the integrity of the public conversation,’ said Leslie Miller, YouTube’s vice president of Government Affairs and Public Policy. ‘We know that the risks of AI impersonation are particularly high for those in the civic space. But while we are providing this new shield, we’re also being careful about how we use it.’
Removal requests will be assessed individually under YouTube’s privacy policy rules to determine whether the content constitutes parody or political critique, which remain protected forms of expression. Participants must verify their identity by uploading a selfie and a government-issued ID before accessing the tool. Once verified, they can review detected matches and submit removal requests for content they believe violates policy.
YouTube also said it supports the proposed NO FAKES Act in the United States, which aims to regulate the unauthorised use of an individual’s voice or visual likeness in AI-generated media. AI-generated videos on the platform are already labelled, though label placement varies depending on the topic’s sensitivity.
‘There’s a lot of content that’s produced with AI, but that distinction’s actually not material to the content itself,’ said Amjad Hanif, YouTube’s vice president of Creator Products. The company said it plans to expand the technology over time to detect AI-generated voices and other intellectual property.
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Meta Platforms has acquired Moltbook, a social networking platform designed for AI agents. The deal brings co-founders Matt Schlicht and Ben Parr into Meta’s AI research division, the Superintelligence Labs, led by Alexandr Wang.
Financial terms of the acquisition were not disclosed, and the founders are expected to start on 16 March.
Moltbook, launched in January, allows AI-powered bots to exchange code and interact socially in a Reddit-like environment. The platform has sparked debate on AI autonomy and real-world capabilities, highlighting growing competition among tech giants for AI talent and technology.
Industry figures have offered differing views on the platform’s significance. OpenAI CEO Sam Altman called Moltbook a potential fad but acknowledged its underlying technology hints at the future of AI agents.
Meanwhile, Anthropic’s chief product officer, Mike Krieger, noted that most users are not ready to grant AI full autonomy over their systems.
The platform’s growth also highlighted security risks. Cybersecurity firm Wiz reported a vulnerability that exposed private messages, email addresses, and credentials, which was resolved after the owners were notified.
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Japan has identified dozens of advanced technologies as priority investment targets as part of an economic strategy led by Sanae Takaichi.
The plan aims to channel public and private capital into industries expected to drive long-term economic growth.
Government officials selected 61 technologies and products for support across 17 strategic sectors. The list includes emerging fields such as AI, quantum computing, regenerative medicine and marine drones.
Many of these technologies are still in early development, but are considered important for economic security and global competitiveness.
The strategy forms a central pillar of Takaichi’s broader economic agenda to strengthen Japan’s industrial base and encourage investment in high-growth sectors. Authorities plan to release spending estimates and implementation timelines by summer as part of a detailed investment roadmap.
Japan has also set ambitious market goals in several sectors. Officials aim to secure more than 30% of the global AI robotics market by 2040 while increasing annual sales of domestically produced semiconductors to ¥40 trillion.
Several Japanese technology companies could benefit from the policy direction. Firms such as Fanuc, Yaskawa Electric and Mitsubishi Electric are integrating AI into industrial robots, while Sony Group produces sensors used in robotic systems.
Chipmakers, including Rohm, Kioxia and Renesas Electronics, may also benefit from increased investment in semiconductor manufacturing and related supply chains.
Despite strong investor interest, analysts note uncertainty about how the programme will be financed, particularly as Japan faces rising spending pressures from social security, defence and public debt.
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New York lawmakers are considering legislation that would ban AI chatbots from providing legal or medical advice. The bill aims to stop automated systems from impersonating licensed professionals such as doctors and lawyers.
The proposal would also require chatbot operators to clearly inform users that they are interacting with an AI system. Notices must be prominent, written in the same language as the chatbot, and use a readable font.
A key feature of the bill is a private right of action. However, this would allow users to file civil lawsuits against chatbot owners who violate the law, recovering damages and legal fees. Experts say this enforcement tool strengthens the rules and deters abuse.
Supporters of the legislation argue it protects New Yorkers’ safety, particularly minors. Other bills in the same package would regulate online platforms like Roblox and set standards for generative AI, synthetic content, and the handling of biometric data.
The bill’s author, state Senator Kristen Gonzalez, said AI innovation should not come at the expense of public safety. She pointed to recent cases where AI chatbots were linked to harmful outcomes for minors, highlighting the need for transparency and accountability.
If passed, the law would take effect 90 days after the governor signs it. Lawmakers hope it will balance innovation with user protection, ensuring AI tools are used responsibly and safely across the state.
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A draft initiative from the European Commission seeks to introduce a new legal structure designed to simplify how companies operate across the EU.
The proposal, often referred to as the ‘EU Inc’ initiative, explores the creation of a so-called ’28th regime’ that would exist alongside national corporate frameworks used by member states.
A concept that aims to provide startups and technology firms with a single legal structure that applies across the EU.
Instead of navigating different national rules in each country, companies could operate under a unified regulatory model intended to reduce administrative barriers and encourage cross-border innovation.
According to the draft, the initiative may rely on an EU regulation rather than separate national legislation. Such an approach could enable faster implementation, as the EU regulations apply directly across all member states without requiring domestic transposition.
However, the legal basis of the proposal could raise institutional concerns. Using a regulation as the primary mechanism may constitute an unconventional shortcut in the EU lawmaking, potentially sparking debate among policymakers over the approach’s scope and legitimacy.
The initiative reflects broader efforts within the Union to simplify regulatory frameworks and strengthen the competitiveness of European startups. If adopted, the ‘EU Inc’ model could reshape how young companies expand across the single market.
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On 28 February 2026, Anthropic’s Claude rose to No. 1 in Apple’s US App Store free rankings, overtaking OpenAI’s ChatGPT. The surge came shortly after OpenAI announced a partnership with the US Department of Defense (DoD), making its technology available to the US Army. The development prompted discussion among users and observers about whether concerns over military partnerships were influencing the shift to alternative AI tools.
Mere hours before the USD $200 million OpenAI-DoD deal was finalised, Anthropic was informed that its potential deal with the Pentagon had fallen through, largely because the AI company refused to relinquish total control of its technology for domestic mass surveillance. According to reporting, discussions broke down after Anthropic declined to grant the US government unrestricted control over its models, particularly for potential uses related to large-scale surveillance.
Following the breakdown of negotiations, US officials reportedly designated Anthropic as a ‘supply chain risk to national security’. The decision effectively limited the company’s participation in certain defence-related projects and highlighted growing tensions between AI developers’ safety policies and government expectations regarding national security technologies.
I resigned from OpenAI. I care deeply about the Robotics team and the work we built together. This wasn’t an easy call. AI has an important role in national security. But surveillance of Americans without judicial oversight and lethal autonomy without human authorization are…
The debate over military partnerships sparked internal and industry-wide discussion. Caitlin Kalinowski, the former head of AR glasses hardware at Meta and the hardware leader at OpenAI, resigned soon after the US DoD deal, citing ethical concerns about the company’s involvement in military AI applications.
AI has driven recent technological innovation, with companies like Anduril and Palantir collaborating with the US DoD to deploy AI on and off the battlefield. The debate over AI’s role in military operations, surveillance, and security has intensified, especially as Middle East conflicts highlight its potential uses and risks.
Against this backdrop, the dispute between Anthropic and the Pentagon reflects a wider debate on how AI should be used in security and defence. Governments are increasingly relying on private tech companies to develop the systems that shape modern military capabilities, while those same companies are trying to set limits on how their technologies can be used.
As AI becomes more deeply integrated into security strategies around the world, the challenge may no longer be whether the technology will be used, but how it should be governed. The question is: who should ultimately decide where the limits of military AI lie?
Anthropic’s approach to military AI
Anthropic’s approach is closely tied to its concept of ‘constitutional AI’, a training method that guides how the model behaves by embedding a set of principles directly into its responses. Such principles are intended to reduce harmful outputs and ensure the system avoids unsafe or unethical uses. While such safeguards are intended to improve reliability and trust, they can also limit how the technology can be deployed in more sensitive contexts such as military operations.
Anthropic’s Constitution says its AI assistant should be ‘genuinely helpful’ to people and society, while avoiding unsafe, unethical, or deceptive actions. The document reflects the company’s broader effort to build safeguards into model deployment. In practice, Anthropic has set limits on certain applications of its technology, including uses related to large-scale surveillance or military operations.
Anthropic presents these safeguards as proof of its commitment to responsible AI. Reports indicate that concerns over unrestricted model access led to the breakdown in talks with the US DoD.
At the same time, Anthropic clarifies that its concerns are specific to certain uses of its technology. The company does not generally oppose cooperation with national security institutions. In a statement following the Pentagon’s designation of the company as a ‘supply chain risk to national security’, CEO Dario Amodei said, ‘Anthropic has much more in common with the US DoD than we have differences.’ He added that the company remains committed to ‘advancing US national security and defending the American people.’
The episode, therefore, highlights a nuanced position. Anthropic appears open to defence partnerships but seeks to maintain clearer limits on the deployment of its AI systems. The disagreement with the Pentagon ultimately reflects not a fundamental difference in goals, but rather different views on how far military institutions should be able to control and use advanced AI technologies.
Anthropic’s position illustrates a broader challenge facing governments and tech companies as AI becomes increasingly integrated into national security systems. While military and security institutions are eager to deploy advanced AI tools to support intelligence analysis, logistics, and operational planning, the companies developing these technologies are also seeking to establish safeguards for their use. Anthropic’s willingness to step back from a major defence partnership and challenge the Pentagon’s response underscores how some AI developers are trying to set limits on military uses of their systems.
Defence partnerships that shape the AI industry
While Anthropic has taken a cautious approach to military deployment of AI, other technology companies have pursued closer partnerships with defence institutions. One notable example is Palantir, the US data analytics firm co-founded by Peter Thiel that has longstanding relationships with numerous government agencies. Documents leaked in 2013 suggested that the company had contracts with at least 12 US government bodies. More recently, Palantir has expanded its defence offering through its Artificial Intelligence Platform (AIP), designed to support intelligence analysis and operational decision-making for military and security institutions.
Another prominent player is Anduril Industries, a US defence technology company focused on developing AI-enabled defence systems. The firm produces autonomous and semi-autonomous technologies, including unmanned aerial systems and surveillance platforms, which it supplies to the US DoD.
Shield AI, meanwhile, is developing autonomous flight software designed to operate in environments where GPS and communications may be unavailable. Its Hivemind AI platform powers drones that can navigate buildings and complex environments without human control. The company has worked with the US military to test these systems in training exercises and operational scenarios, including aircraft autonomy projects aimed at supporting fighter pilots.
The aforementioned partnerships illustrate how the US government has increasingly embraced AI as a key pillar of national defence and future military operations. In many cases, these technologies are already being used in operational contexts. Palantir’s Gotham and AIP, for instance, have supported US military and intelligence operations by processing satellite imagery, drone footage, and intercepted communications to help analysts identify patterns and potential threats.
Other companies are contributing to defence capabilities through autonomous systems development and hardware integration. Anduril supplies the US DoD with AI-enabled surveillance, drone, and counter-air systems designed to detect and respond to potential threats. At the same time, OpenAI’s technology is increasingly being integrated into national security and defence projects through growing collaboration with US defence institutions.
Such developments show that AI is no longer a supporting tool but a fundamental part of military infrastructure, influencing how defence organisations process information and make decisions. As governments deepen their reliance on private-sector AI, the emerging interplay among innovation, operational effectiveness, and oversight will define the central debate on military AI adoption.
The potential benefits of military AI
The debate over Anthropic’s restrictions on military AI use highlights the reasons governments invest in such technologies: defence institutions are drawn to AI because it processes vast amounts of information much faster than human analysts. Military operations generate massive data streams from satellites, drones, sensors, and communication networks, and AI systems can analyse them in near real time.
In 2017, the US DoD launched Project Maven to apply machine learning to drone and satellite imagery, enabling analysts to identify objects, movements, and potential threats on the battlefield faster than with traditional manual methods.
AI is increasingly used in military logistics and operational planning. It helps commanders anticipate equipment failures, enables predictive maintenance, optimises supply chains, and improves field asset readiness.
Recent conflicts have shown that AI-driven tools can enhance military intelligence and planning. In Ukraine, for example, forces reportedly used software to analyse satellite imagery, drone footage, and battlefield data. Key benefits include more efficient target identification, real-time tracking of troop movements, and clearer battlefield awareness through the integration of multiple data sources.
AI-assisted analysis has been used in intelligence and targeting during the Gaza conflict. Israeli defence systems use AI tools to rapidly process large datasets for surveillance and intelligence operations. The tools help analysts identify potential militant infrastructure, track movements, and prioritise key intelligence, thus speeding up information processing for teams during periods of high operational activity.
More broadly, AI is transforming the way militaries coordinate across land, air, sea, and cyber domains. AI integrates data from diverse sources, equipping commanders to interpret complex operational situations and enabling faster, informed decision-making. The advances reinforce why many governments see AI as essential for future defence planning.
Ethical concerns and Anthropic’s limits on military AI
Despite the operational advantages of military AI, its growing role in national defence systems has raised ethical concerns. Critics warn that overreliance on AI for intelligence analysis, targeting, or operational planning could introduce risks if the systems produce inaccurate outputs or are deployed without sufficient human oversight. Even highly capable models can generate misleading or incomplete information, which in high-stakes military contexts could have serious consequences.
Concerns about the reliability of AI systems are also linked to the quality of the data they learn from. Many models still struggle to distinguish authentic information from synthetic or manipulated content online. As generative AI becomes more widespread, the risk that systems may absorb inaccurate or fabricated data increases, potentially affecting how these tools interpret intelligence or analyse complex operational environments.
Questions about autonomy have also become a major issue in discussions around military AI. As AI systems become increasingly capable of analysing battlefield data and identifying potential targets, debates have emerged over how much decision-making authority they should be given. Many experts argue that decisions involving the use of lethal force should remain under meaningful human control to prevent unintended consequences or misidentification of targets.
Another area of concern relates to the potential expansion of surveillance capabilities. AI systems can analyse satellite imagery, communications data, and online activity at a scale beyond the capacity of human analysts alone. While such tools may help intelligence agencies detect threats more efficiently, critics warn that they could also enable large-scale monitoring if deployed without clear legal and institutional safeguards.
It is within this ethical landscape that Anthropic has attempted to position itself as a more cautious actor in the AI industry. Through initiatives such as Claude’s Constitution and its broader emphasis on AI safety, the company argues that powerful AI systems should include safeguards that limit harmful or unethical uses. Anthropic’s reported refusal to grant the Pentagon unrestricted control over its models during negotiations reflects this approach.
The disagreement between Anthropic and the US DoD therefore highlights a broader tension in the development of military AI. Governments increasingly view AI as a strategic technology capable of strengthening defence and intelligence capabilities, while some developers seek to impose limits on how their systems are deployed. As AI becomes more deeply embedded in national security strategies, the question may no longer be whether these technologies will be used, but who should define the boundaries of their use.
Military AI and the limits of corporate control
Anthropic’s dispute with the Pentagon shows that the debate over military AI is no longer only about technological capability. Questions of speed, efficiency, and battlefield advantage now collide with concerns over surveillance, autonomy, human oversight, and corporate responsibility. Governments increasingly see AI as a strategic asset, while companies such as Anthropic are trying to draw boundaries around how far their systems can go once they enter defence environments.
Contrasting approaches across the industry make the tension even clearer. Palantir, Anduril, Shield AI, and OpenAI have moved closer to defence partnerships, reflecting a broader push to integrate advanced AI into military infrastructure. Anthropic, by comparison, has tried to keep one foot in national security cooperation while resisting uses it views as unsafe or unethical. A divide of that kind suggests that the future of military AI may be shaped as much by company policies as by government strategy.
The growing reliance on private firms to build national security technologies has made governance harder to define. Military institutions want flexibility, scale, and operational control, while AI developers increasingly face pressure to decide whether they are simply suppliers or active gatekeepers of how their models are deployed. Anthropic’s position does not outright defence cooperation, but it does expose how fragile the relationship becomes when state priorities and corporate safeguards no longer align.
Military AI will continue to expand, whether through intelligence analysis, logistics, surveillance, or autonomous systems. Governance, however, remains the unresolved issue at the centre of that expansion. As AI becomes more deeply embedded in defence policy and military planning, should governments alone decide how far these systems can go, or should companies like Anthropic retain the power to set limits on their use?
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