In mid-February, under Eastern Standard Time, the U.S. Pentagon was reported to be seriously considering reducing or even terminating some AI collaborations with Anthropic, prompting a new round of scrutiny regarding the militarization of AI. On the surface, this is an issue of whether to continue a government contract, but fundamentally it represents a direct conflict between the military's craving for high-intensity, broadly applicable AI capabilities and a laboratory whose brand core centers on safety and alignment, involving a debate around ethical red lines. The core of the controversy highly focuses on two points: whether large-scale surveillance of the American public should be allowed and whether fully autonomous weapon systems should be permitted. This divergence not only has the potential to reshape the technological trajectory of U.S. military AI but also compels the entire industry to reprice and queue between “military contracts” and “safety bottom lines.”
The military accelerates the rollout of AI war machines
● Advancement pace: Public information indicates that the U.S. military is accelerating the incorporation of large models and various AI capabilities into key processes like intelligence analysis, combat planning, and command assistance, aiming to shorten the time difference from “sensor to shooter” through automated intelligence filtering, real-time battlefield situation integration, and decision-making suggestion generation. In this context, the military increasingly views large models as the infrastructure for future warfare, rather than merely as specific localized tools.
● All-scenario access demand: In the military's technical vision, the ideal state is to have open access to models under “all lawful military uses,” meaning that as long as it doesn't violate explicit laws, the same set of model capabilities can be invoked. This demand stems from a preference for a unified technology stack, reduced approval processes, and enhanced deployment speed, hoping to avoid frequently switching model configurations and authorization boundaries across different theaters and missions.
● Concerns about case-by-case reviews: According to a briefing quoting Pentagon officials, “if case-by-case negotiations or model strategic intercepts are necessary, it becomes practically unacceptable.” This statement reflects the military's core concern: if every invocation involving sensitive application scenarios requires back-and-forth confirmation with vendors, or if models are refused output on the grounds of safety policy at critical moments, it will directly undermine system usability and potentially cause link disruptions in actual combat or exercises.
● Friction with safety-first vendors: From the military's perspective, collaborating with AI companies that emphasize safety and ethics can yield advanced models but also entails accepting a whole set of externally imposed safety policies and usage restrictions. For organizations pursuing high efficiency and emphasizing controlled command chains, these restrictions are not merely “additional procedures,” but seen as potential losses to combat capability and response speed, increasing their structural distrust of such collaborative relationships.
Anthropic sets two non-crossable red lines
● Prohibiting large-scale surveillance of American citizens: According to a single source of information, Anthropic clearly refuses for its models to be used for large-scale surveillance of the American public, listing this as one of the collaboration bottom lines. The logic for this safety concern is that once large models are embedded into scalable surveillance networks, they might technically amplify the government or agencies' abilities to profile, track, and predict individual behaviors, making it difficult to guarantee that subsequent actions will not exceed the gray areas of law and social consensus, resulting in an irreversible “surveillance infrastructure lock-in effect.”
● Refusing fully autonomous weapon systems: The second red line pertains to the autonomy of weapon systems—Anthropic refuses to support fully autonomous lethal systems that operate completely outside of human decision-making, insisting on the so-called “human-in-the-loop” control principle. Their stance is concerned that if target identification, threat assessment, and lethal decision-making are entirely relegated to models, any errors in training data, environmental perception, or reasoning chains could be fatal and unaccountable, violating the current international humanitarian law and armed conflict law practices on defining subjects of responsibility and the principle of proportionality.
● Background of safety branding and restriction frameworks: From its inception, Anthropic has positioned “alignment” and “safety principles” as core selling points, and has previously established a comprehensive framework of usage restrictions and reviews to constrain the application categories its models can participate in. Unlike some laboratories that center on performance or scale as key promotional points, they prefer to embed “preset brakes” at the product design level and retain the right to refuse collaboration or downgrade services when engaging with high-risk industries, making them naturally more sensitive in government and military projects.
● How red lines turn into stumbling blocks: In low-risk enterprise solutions, these safety red lines are often seen as brand-enhancing, but when the partner is the military, aiming for large-scale deployment and pursuing extreme efficiency, the same red lines become real operational constraints. The military's desired “access for all lawful uses” is structurally incompatible with Anthropic’s “use whitelist + dynamic blocking” logic, causing many originally envisioned high-intensity application scenarios to be obstructed before they could be realized due to these bottom lines.
Turning point from sweet collaboration to reconsideration of withdrawal
● Initial collaboration scope: At the outset, the Pentagon's collaboration with Anthropic was more focused on areas like intelligence-assisted analysis, document processing, and internal process optimization. The military originally hoped to gradually expand from this foundation, transferring the same set of model capabilities to more sensitive applications closer to the front line, such as command support and threat identification, thus forming a unified and reusable AI infrastructure in terms of technology and processes.
● Cracks in application boundary negotiations: As specific application scenarios progressed, both parties were compelled to discuss directly whether the model could be used for cross-domain data correlation, automated filtering of battlefield targets, and links closer to real-time monitoring and weapon control. It was precisely in these boundary negotiations that Anthropic’s two red lines were continuously touched, gradually revealing a fundamental divergence between them on the core issue of “what AI can do”: the military sees “as long as lawful” as the bottom line, while Anthropic premises on “lawful but high-risk must be limited.”
● Accumulation of frustration and distrust: For the military, being “strategically refused” output by models in critical tasks or being told certain uses must be negotiated case by case poses a challenge to the continuity of the operational chain. The briefing’s statement “if case-by-case negotiations or model strategic intercepts are needed, it becomes practically unacceptable” reflects a deeper sense of frustration: commanders are reluctant to entrust critical aspects to a black-box system that could take a morally contrary stance.
● Shift to evaluation initiation: After multiple rounds of negotiation and communication, the Pentagon began to no longer view its collaboration with Anthropic as a “done deal on a long-term technological route,” but instead actively evaluate the feasibility of scaling back collaboration, migrating sensitive applications to other models, or even completely terminating parts of the collaboration. This shift reflects not only a wavering trust in a single supplier but also indicates that the military might redesign its collaborative structure with multiple AI laboratories to reduce the extent constrained by a single security stance.
The four laboratories' competition: Who opens the gates for military AI
● Overall strategy of broad access: According to “to be verified” information in the briefing, the Pentagon is exploring a strategy to obtain broader access from multiple leading AI laboratories, hoping to invoke and orchestrate multiple models under the same framework to reduce dependency on any single supplier. This “multi-model pool” concept allows for dynamic balancing of performance, cost, and safety policies, establishing a more resilient technical backup for military AI.
● Unverified claim of “four open labs”: There are claims that the military wishes for four laboratories, including Anthropic, to provide access for “all lawful uses,” but the briefing specifically notes that this remains unverified information, lacking supporting public documents. What can be confirmed is that the military indeed leans towards trying to weaken usage restrictions in negotiations, but whether this forms a unified, equitable written request for all four labs remains inconclusive.
● Simulation of looser spaces among other laboratories: If it is assumed that other laboratories have more lenient criteria concerning surveillance and weapon applications, the military will gain significantly greater maneuvering room in technical choices: they can prioritize capabilities related to domestic surveillance and weapon aid modules with higher autonomy levels to these more “cooperative” models while reserving relatively “clean” backend analysis and office automation needs for suppliers with stricter limitations, thereby modularizing ethical risks.
● Pressure of choice between safety red lines and commercial opportunities: In the face of a substantial military order, each laboratory inevitably has to make difficult trade-offs between safety red lines and commercial opportunities. Loosening restrictions may immediately enhance procurement opportunities and revenue scale but could incur costs in public opinion, regulatory scrutiny, and even future international rule-making; steadfastly holding to red lines could mean losing short-term orders but gains long-term leverage in safety discourse. Anthropic’s choice, indirectly, also creates reference points and pressure tests for its peers.
A tug-of-war between AI ethical red lines and safety dividends
● Military position: From the military's perspective, national security and military advantages hold the highest priority, and any usage restrictions imposed by model suppliers are easily understood as weakening combat capabilities. Given that potential adversaries are also actively integrating AI for intelligence and command systems, they fear “being tied up first” under moral self-restriction rather than gaining an advantage in a technical race, thus they prefer to regard models as tools that can fully fit into existing military rules and confidentiality systems instead of participants with autonomous ethical judgment.
● Anthropic's position: Anthropic, however, views long-term system safety as paramount, asserting that once models are allowed to participate in large-scale surveillance of the American public or provide critical decision support for completely autonomous weapons, it amounts to laying a technical foundation for some high-risk states. In the short term, it might appear controllable, but once political environments, regulatory intensity, or other variables shift, these capabilities will likely be irretrievable and further erode social trust, triggering a chain reaction where technology could be diverted to more extreme uses.
● Structural contradictions from a global perspective: This dispute around the two red lines reflects a structural contradiction between the arms race in AI and ethical guardrails worldwide: great powers, driven by security anxieties, tend to expand technological advantages within gray areas as much as possible, while society and academia continuously call for strong constraints on usage boundaries. The stronger the technology, the harder it is to delineate boundaries, and any retreat by one side can be interpreted by the opponent as “weakness” or “backwardness,” creating a security dilemma that is difficult to escape.
● Demonstrative effects on industry terms and government orders: The high-profile divergence between the Pentagon and Anthropic will undoubtedly serve as a significant reference for other AI companies in drafting usage terms and addressing government and military orders. Particularly for companies supplying both civilian markets and public sectors, it’s essential to anticipate whether incorporating restrictions on surveillance and weapon applications into terms might render them “unreliable suppliers”; conversely, if they remain completely open, how they would explain this strategic choice to employees, investors, and the public.
Will the military yield or turn to other models?
In the coming months, the Pentagon's game with Anthropic may take several paths: the military could, under pressure, make tactical concessions on certain application red lines, accepting finer granularity on usage restrictions; it may quietly shift the most sensitive projects to laboratories more willing to cooperate, retaining only relatively “safe” collaborations; or it may maintain the current state of multi-party negotiations and technical pilots, dynamically switching between different models to buy time. For Anthropic, adhering to the two red lines on large-scale surveillance and automatic lethality may mean sacrificing some potential revenue and government backing in the short term, but from a long-term perspective, it creates an opportunity to earn greater discourse power and trust dividends in future regulatory legislation and international rule-making.
As discussions intensify globally regarding the military boundaries of AI, whether laws, treaties, or industry standards will outline clearer hard boundaries on surveillance and weapon applications will directly impact the feasibility and pricing of such collaborations. Regardless of whether the Pentagon ultimately reduces its cooperation with Anthropic, the dispute itself has already transcended contractual boundaries, pointing to a more fundamental question: in the AI era, how do we make value choices between national security and overall human safety, and what behaviors do we allow to become permanently written into the underlying logic of warfare and social governance through technology?
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