Yale Journal of Law & Technology’s article delves into the ethical and bias challenges in AI‑powered legal tools, dissecting how human inputs—from data selection to prompting—profoundly shape AI outputs. It spotlights the tension between efficiency gains and the risk of automated errors, offering legal professionals a roadmap to evaluate when and how to retain human oversight. This piece matters because it equips lawyers and compliance teams with actionable insights to design fair, defensible AI workflows. Dive into the full analysis to understand the mechanics driving bias and how to implement guardrails that uphold integrity and trust.