Earlier quoted context omitted.
Would results of discovery be public record? If so, I could also see: 3) They don't want their "secret sauce" made publicly available. That would both open them up to commercial competition, and make their product less reliable in court, as anti-Shotspotter experts would start figuring out how to effectively argue against the product's methodology. In general I think technology like this should have to be fully trans…
This is a reasonable argument, but I'm not sure you're aware of allegations of this company altering evidence to better fit a police narrative: https://www.vice.com/en/article/qj8xbq/police-are-telling-sh... I sincerely doubt there's any secret sauce to protect when they have "analysts" sitting around regularly "correcting" evidence.
In general though, I think there are legitimate reasons for manual analysis. Any machine learning approach to a problem like this is going to have to balance false positives and false negatives, and there is necessarily going to be a somewhat arbitrary cutoff. Detecting bang-like noises in a large city is likely going to have a pretty conservative cutoff to avoid DDOSing the police with calls. For example say the company sets their cutoff for automatic reporting at 90% confidence, but when the police ask them to review a specific time period, it turns out there was a shot detected with 89% confidence, and manual analysis indicates a false negative. That is probably still useful information, and it would definitely be useful to include this data point with the correct classification in future iterations of the model.