Eyewitness Identification: A Signal Detection Theory Lab

Every eyewitness lineup decision is, underneath, a single number crossing a threshold: a felt strength of recognition compared against a personal decision criterion. This simulator renders that model in 3D as two Gaussian "mountains" of memory strength — one for an innocent lure, one for the true culprit — separated by a distance d′ that represents how good the witness's memory actually is. Drag the criterion to see the classic speed–accuracy trade-off of eyewitness testimony: a lenient witness racks up hits but also false identifications of innocent people, while a cautious one protects the innocent at the cost of missed guilty suspects. Run batches of simulated witnesses to watch the hit rate, false-alarm rate, and an empirically recovered d′ converge toward the values the sliders predict, and compare simultaneous against sequential lineup presentation — the reform actually adopted by many police departments after decades of forensic-psychology research on exactly this trade-off.