The Belfer Center has produced a steady stream of work that treats military AI as a governance problem as much as a technical one. Its analyses, stretching from foundational recommendations on national security and AI to recent policy papers on autonomy, interoperability, and the Replicator effort, converge on familiar prescriptions: design for compliance, improve testing and verification, harden systems against attack, and invest in training and institutional capacity. These are correct, necessary, and insufficient at the same time.
One ethical strength in Belfer’s output is its insistence that law and ethics be baked into development cycles rather than tacked on afterwards. The recommendation to pursue compliance-by-design, and to integrate ethicists, lawyers, and domain experts into development and procurement, pushes developers and commanders toward anticipatory responsibility. That move reframes moral obligation so that it attaches to system architectures, procurement pathways, and governance processes, not merely to the battlefield moment. But the recommendation founders on a practical question: how to codify international law, and the indeterminacies of proportionality and necessity, into statistical models that will face novel and ambiguous contexts. Belfer recognizes the problem of translating legal principles into operational specifications, but the gap between aspirational guidance and an implementable, auditable specification remains large.
Belfer’s attention to adversarial vulnerabilities and the concept of AI security compliance is another welcome corrective. The literature it cites shows that modern machine learning systems can be subverted by subtle inputs, data poisoning, and supply chain manipulation, which in a military context converts brittle models into strategic liabilities. Recommending AI security compliance regimes and mandatory security assessments for government acquisitions is therefore ethically prudent; states that field fragile autonomous capabilities create downstream harms that may be difficult to contain. Yet the policy response risks overconfidence in top-down controls. Compliance programs work when there are measurable baselines, transparent testing protocols, and incentives for truthful reporting. In practice, defense procurement timelines, commercial secrecy, and the classified nature of many systems inhibit the kind of public, repeatable verification that would make compliance credible.
A recurring tension in Belfer’s recent papers concerns explainability. Certain reports prudently argue for prioritizing traceability and accuracy over explainability for complex deep learning models when operational performance and legal accountability are at stake. That is a defensible, pragmatic stance if the alternative is to field unreliable systems with spurious explanations. But ethics should compel us to ask a second question: when is opacity itself an ethical cost we cannot accept? Traceability that shows input to output mappings is useful, but it does not replace deliberative human judgment about value-laden tradeoffs. Belfer’s analysis rightly flags the tradeoff; it stops short of insisting on doctrinal limits on opaque systems in lethal decision loops. The ethical calculus must therefore combine technical thresholds with categorical constraints on where opacity is permissible.
Belfer also emphasizes interoperability, shared lexicons, and joint training as prerequisites for responsible use of AI in the force. Interoperability reduces friction, lowers the risk of misinterpretation between allies, and allows for coordinated verification regimes. Those are important ethical points because disasters of coordination can amplify harm in ways that are not easily reversed on the battlefield. Nonetheless, focusing on interoperability and engineering standards alone risks normalizing an expanded set of permissible uses. In ethical terms, better integration should not be a simple route to more autonomous employment. It should be a precondition for stricter, not laxer, governance.
Where Belfer’s recommendations are most vulnerable is at the political level. Technical and procedural safeguards are necessary but they are only effective within a polity that constrains reckless deployment. The Center rightly calls for new verification and validation frameworks, continuous auditing, and international standards. These, however, presuppose willing cooperation among states, and a political appetite for restraint, both of which are scarce in competitive security environments. Ethical governance therefore requires a second track: deliberate political limits. This means clear red lines about which functions may never be delegated to autonomous systems; strengthened export controls and contractual clauses that prevent the offshoring of lethal autonomy; and international diplomatic efforts to create norms backed by inspection and sanctions. Without political instruments, the best engineering practices will be worked around or gamed.
Finally, Belfer’s work sensibly calls attention to human factors: automation bias, training deficits, and institutional pressures that coax operators to over-rely on algorithmic outputs. Ethics in military AI cannot be reduced to better models or checklists. It must also address organizational incentives, procurement cultures that valorize novelty, and accountability mechanisms that make individuals and institutions answerable for choices that entrain machines into violence. Practical steps include independent third party audits, public reporting requirements for nonclassified aspects of capability, robust whistleblower protections inside firms and services, and legal clarity on responsibility chains. These measures are political and legal, not technical, but they are essential if Belfer’s deservedly high standards are to matter in action.
In sum, Belfer’s recommendations provide a useful scaffolding. They point us toward better design practices, stronger testing regimes, and improved institutional competence. Ethically minded scholars and policymakers should treat those prescriptions as necessary building blocks. They must not mistake them for a finished edifice. The next phase must layer in explicit political constraints, enforceable international norms, and a public architecture of accountability. If we aim to keep human dignity, proportionality, and democratic oversight at the center of how violence is justified, then we must insist that some functions remain irrevocably human and that technological competence is matched by political will. Only then will Belfer’s sensible technical program convert into a genuinely ethical posture toward military AI.