the "right number" is strongly dependent on what the consequences of false positives are. If you're comfortable pulling numbers from thin air, 0.5% of these guided patrols lead to prevented crimes, but 10% lead to arrests of simply suspicious looking people (suspicious on grounds of being around where crime is predicted) and then while they're being detained are late for a job and get fired. Is 20 people getting fired worth preventing one crime? Say, a catalytic converter being stolen, since "crime" is very bad, not, say, murder particularly.

Further, who in the general vicinity of a precrime report is “suspicious looking”? Who gets their day, if not their life, turned upside down?

Thankfully, police are notoriously fair-minded and empathetic, and never arbitrary, deceptive, or biased when it comes to probable cause.

This is actually the real problem. Police patrols have to be directed somewhere, somehow. It's either the whim of the commisioner, or gut feeling of the officers, or machine learning software.

When one says that machine learning software is terrible, you have to trust either the officers, or their boss. I have a feeling that the same people who criticize the software trust rank-and-file officers even less..

> How big does it need to be before it is good? 2%? 50%? 100%? If you can't give any answer to that question, then it doesn't matter what the number really is because the number still doesn't mean anything.

Uh, seems a lot like it should be the government answering that question before spending tax money on it and subjecting real people to the uncaring US justice system just because crime is bad so we have to do something, even if that something is ML snake oil?