Every publicly known facial recognition wrongful arrest in the US has been of a Black person, yet police departments still lack mandatory policies on algorithmic accountability

Every publicly documented case of a wrongful arrest caused by facial recognition technology in the United States has involved a Black individual -- including Robert Williams (Detroit, 2020, detained 30 hours), Nijeer Parks (New Jersey, 2019, jailed 10 days), Porcha Woodruff (Detroit, 2023, arrested while 8 months pregnant), LaDonna Crutchfield (Detroit, January 2024, misidentified despite being 5 inches shorter and years younger than the actual suspect), and Trevis Williams (New York, August 2025). Why it matters: Black individuals are disproportionately misidentified by facial recognition, so innocent people are handcuffed, booked, and jailed for crimes they did not commit, so they suffer lasting psychological trauma, job loss, and legal costs even after exoneration, so communities of color develop justified distrust of both AI and law enforcement institutions, so the constitutional guarantee of equal protection is systematically undermined by an unregulated technology that most police departments deploy without any public disclosure or accuracy auditing. The structural root cause is that facial recognition training datasets historically overrepresented lighter skin tones, producing higher error rates on darker skin, and no federal law requires accuracy testing across demographics before deployment, bias auditing after deployment, or mandatory human verification before arrest -- the Williams v. City of Detroit settlement in June 2024 created the strongest constraints on any single department but applies only to Detroit.