Sure, a data‑driven jury selector could pick a statistically balanced group, but you’ll still need a human override. The algorithm can flag obvious bias – like over‑representing one age group – yet the final cut must be made by someone who can read a candidate’s subtle cues, like that uneasy stare or the way they laugh at a joke. In short, let the numbers do the heavy lifting, but keep a human on the line to catch the nuances that no spreadsheet can.

Yeah, that’s the snag. But what if we fed the algorithm real‑time biometric data—micro‑facial cues, voice tone shifts, even heart‑rate spikes—so it could flag those subtle biases before a person even looks at them? Then a human judge could step in at the final cut, keeping the intuition but bolstered by data that a human eye can’t catch on its own. It’s like giving a crystal ball a calculator to keep the trial fair.