Increasing Trust and Reducing Bias: Legal-Grounded AI for Intelligence and Targeting

In this context, bias is not just a technical flaw; it is a strategic, legal, and moral risk. A mislabeled suspect, a skewed risk score, or a flawed targeting recommendation can damage international relations, fuel instability, and erode public confidence. Our priority should not only be “smarter AI,” but AI explicitly grounded in laws and regulations that already constrain human decision-makers.

One way to reduce risk is to ground AI systems in the legal and regulatory frameworks that are supposed to govern behavior in the first place. Rather than relying solely on past operational data - which often encodes historic bias and opaque practices - legal-focused LLMs can be explicitly grounded in constitutions, statutes, case law, rules of engagement, commanders’ operations plans and associated targeting directives, as well as applicable human rights obligations. The center of gravity is then shifted. The system is pulled toward what is permitted, prohibited, and proportionate, not simply what was done before.

This legal anchoring also supports transparency. When an AI-assisted analyst flags a target, highlights a pattern of concern, or recommends a course of action, those outputs can be tied back to specific legal provisions, regulations, and/or policy rules rather than obscure correlations in the data. Legal anchoring creates an audit trail for oversight, red-teaming, and challenge, which are crucial for maintaining legitimacy in commercial security, national security and defense operations.

Legal corpora can reflect power dynamics and prejudices of the society in which they are created. But using code, statute, and regulation as primary reference points helps move AI from copying institutional habits to engaging with explicit standards that can be cited, debated, and audited by commanders, lawyers, and oversight bodies. Combined with diverse human review and continuous testing, legal-grounded LLMs can narrow the gap between what is technologically possible and what is ethically acceptable. 

In the age of AI-enabled intelligence and targeting, trust will belong to those intelligence professionals who can demonstrate not only that their systems work, but that they work within the law and can explain why. Legal-aware, constituency reflected, AI is not a luxury; it is fast becoming a societal reflection glass for morality and justice and a precondition for responsible power.