Human errors in criminal investigations have previously led to devastating miscarriages of justice. For example, flaws in forensic identification based on physical or photographic evidence are notoriously unreliable. The criminal justice system has, therefore, started to turn to artificial intelligence (AI) to improve the reliability and fairness of forensic identification. So as not to repeat history, it is critical to evaluate the appropriateness of deploying these new AI forensic tools. We assess the feasibility of measuring basic physical attributes in a photo using a state-of-the-art AI system, and compare performance with human experts and non-experts. Our results raise concerns as to the use of current AI-based forensic identification.

As generative artificial intelligence (AI) continues its ballistic trajectory, everything from text to audio, image, and video generation continues to improve at mimicking human-generated content. Through a series of perceptual studies, we report on the realism of AI-generated voices in terms of identity matching and naturalness. We find human participants cannot consistently identify recordings of AI-generated voices. Specifically, participants perceived the identity of an AI-generated voice to be the same as its real counterpart approximately [Formula: see text] of the time, and correctly identified a voice as AI generated only about [Formula: see text] of the time.