Or, more properly, they use the 117 matches as a starting point in an investigation to eliminate most of them, i.e., they weren't in the area at the time, and identify the others who were in the area at the time. Probably not worth it for a petty crime, but for something more serious...

Or, they just store the info, and when the same petty criminal pops up again with a similar crime, as is often the case, also track the particulars of this one to see if they get a match and add that to the prosecution list.

Kind of like cell phone tracking. There's hundreds of phones in the vicinity of any one bank robbery, but when you get one that is in the vicinity of all three, probably a good idea to investigate the owner of that one...

> Or, more properly, they use the 117 matches as a starting point in an investigation to eliminate most of them, i.e., they weren't in the area at the time, and identify the others who were in the area at the time.

Which is how you get false convictions, because you're starting with a list of essentially random people, with no guarantee that the true perpetrator is even on it.

Then you ping cell phone records, and the actual perpetrator left their phone at home because they knew they'd be committing a crime, but one person out of a hundred on your list of random people happened to be in the area at that time, and that combined with what looks like their face on video is enough to convince a jury. Or convince the accused that a jury would be convinced so they'll plead guilty to a crime they didn't commit.

> Or, they just store the info, and when the same petty criminal pops up again with a similar crime, as is often the case, also track the particulars of this one to see if they get a match and add that to the prosecution list.

So you get another video with the same face matching the same hundred odd people, which increases the chances that one of the other random people on the list was in the vicinity of at least one of the crimes while the actual perpetrator always leaves their phone at home, and now the innocent party gets convicted of multiple counts.

> Kind of like cell phone tracking. There's hundreds of phones in the vicinity of any one bank robbery, but when you get one that is in the vicinity of all three, probably a good idea to investigate the owner of that one...

Then it turns out to be the alarm tech or insurance adjuster or regional bank manager responding to the robbery, or some company that always makes deposits on Friday around 3PM which is also when the robbery crew always robs the banks. Which makes it a lot easier to choose any of those parties as a scapegoat if you can't find who really did it.

Computers are really good at finding random coincidences in large data sets. Humans are really bad at not interpreting that kind of noise as signal.

How likely is it actually that out of the set of 116 people who look like you from your your state (which I see as basically a random sample of 116 people, unless you have a tendency to gravitate people who look like yourself toward yourself...), one of them was in the same area as you, at the same time that a crime was committed against you there?

The real question is how many of those random people could conclusively clear themselves with an alibi. If 20% of those people don't remember or can't conclusively prove where they were... You now have a ton of suspects that each are just as likely the criminal and obviously at most one of them could have committed the crime.

Yes if you can narrow it down to 100 people and then further confirm their identity with DNA or other real evidence that is potentially useful (and only potentially... It may waste your time). But for any sort of petty crime it seems like it will almost always do more harm than good.

> The real question is how many of those random people could conclusively clear themselves with an alibi

No, that's not the real question. The real question is how frequently such people would even exist in the first place, which is what I was asking. We're not trying to find solutions to non-problems here.

Now likely, well based on the number of false convictions we seem to get in the US legal system, I can tell you that the probability is non-zero.

Especially since there may be a genetic component of people looking the same. Chasing down all the Smiths in your neighborhood can increase the rates of false detection.

> How likely is it actually that out of the set of 116 people who look like you from your your state (which I see as basically a random sample of 116 people, unless you have a tendency to gravitate people who look like yourself toward yourself...), one of them was in the same area as you, at the same time that a crime was committed against you there?

That's going to depend a lot on how stringently you define "in the area" and "the time of the crime" as well as things like population density and demographics. For example, if the perpetrator is a particular race and so consequently are all the facial recognition matches, and the state's population has particular races concentrated in particular areas, expect that to affect the probability in a way that leads to more false positives all around, because it's then effectively the case that people with similar faces tend to live near each other.

But the really perfidious thing about all this is that it's not just facial recognition and cell phone matches. Suppose the chance of a random person out of a hundred with a similar face being in the same area is "only" 5%. That would be the case if there were around 500 people in the vicinity (not unusual in an urban area) in a state with a million people, and then around 5% of your convicted criminals would be innocent.

But we're not just checking faces and cell phones, we also check all kinds of things like internet history, family and work connections, financial and purchasing history, etc.

Then we come to find out that one of the facial recognition matches did a web search for Halloween masks in October of last year and the co-conspirators whose faces we don't have were wearing masks, and the same person has a low paying job, a fair amount of debt and a second cousin with a twenty year old conviction for marijuana possession, and the cousin's cell phone was in the vicinity of the crime.

It's a pile of circumstantial nonsense. It's all selection bias and dependent variables. Everybody searches for Halloween masks around Halloween. Each of your hundred odd facial recognition matches has a hundred odd family members, there were a few hundred people in the vicinity, you start multiplying numbers like that and you get coincidence matches. The random cousin who hangs out in the same areas as crimes are committed is not unlikely to have a checkered past.

But all the jury sees is a huge pile of evidence. Which gets bigger the more mass surveillance there is, independent of guilt or innocence, because more surveillance can uncover more coincidences. (And then they pick up your cousin and find drugs on him again, and suddenly he's testifying against you for a lesser sentence even though you haven't even seen him in five years.)

>Or, more properly, they use the 117 matches as a starting point in an investigation to eliminate most of them, i

Maybe if you're a local politician, a cop or rich enough for them to know who you are you'll get that kind of service. For everyone else they'll just do nothing or nearly nothing and go back to playing with that APC they don't need.

If they find your car as part of some other crime they'll add another page to the book they're throwing but you don't need a database to do that.

Exactly! For most minor crimes like car break in, unless it's part of a string, they'll be unlikely to assign resources to the investigation (unless the victim is a VIP), but for a more serious crime, there's some good clues for the investigation.