Summary
- Detroit woman wrongly arrested for carjacking and robbery due to facial recognition technology error.
- Porsche Woodruff, 8 months pregnant, mistakenly identified as culprit based on outdated 2015 mug shot.
- Surveillance footage did not match the identification, victim wrongly identified Woodruff from lineup based on the 2015 outdated photo.
- Woodruff arrested, detained for 11 hours, charges later dismissed; she files lawsuit against Detroit.
- Facial recognition technology’s flaws in identifying women and people with dark skin highlighted.
- Several US cities banned facial recognition; debate continues due to lobbying and crime concerns.
- Law enforcement prioritized technology’s output over visual evidence, raising questions about its integration.
- ACLU Michigan involved; outcome of lawsuit uncertain, impact on law enforcement’s tech use in question.
I think the appropriate procedure depends on the ratio of true/false positives/negatives. This is basically the same discussion that occurred with covid tests, because the mathematics behind are identical. Looking at the Positive/Negative Predictive Value should give you an idea how much you should trust each assessment.
Based on the articles we’ve seen recently, it seems that the false positives are the main problem here, so perhaps the PPV isn’t high enough. Ideally, you would combine two types of methods so that at the end of the day you’ll get to a very high PPV and NPV. However, I’m pretty sure humans have a very low NPV. Hopefully, the PPV is a lot higher, but racism clearly isn’t helping here. Augmenting that appalling mess with a flawed system is still a step forward IMO. Well, at least it would be if the system wasn’t used to oppress and discriminate people.