1. United States
2. Texas
3. Letter

I appreciate the promise that artificial intelligence offers for streamlining the implementation of complex laws, but its adoption must be paired with a deliberate period of human-guided testing. Before an algorithm begins interpreting statutes, allocating funds, or determining eligibility for benefits, it should undergo a transparent pilot phase—long enough to surface hidden biases, edge-case failures, and unintended policy consequences that only real-world use can reveal. During this probationary window, every AI-generated decision should be auditable by qualified reviewers who can trace the model’s reasoning and verify its compliance with both the letter and the spirit of the law. Wherever the system’s logic diverges from legislative intent, humans must be empowered to override the output, refine the training data, and amend the guidance documents. Only after this iterative review demonstrates consistent accuracy and fairness should the tool move from provisional to fully operational status. This safeguard protects citizens from premature automation, protects agencies from costly rollbacks, and, most importantly, preserves democratic accountability. Human judgment remains indispensable—not as an obstacle to innovation but as its ethical compass.