Rite Aid banned from using face recognition software after false ID shoplifters

we can keep up with well-reasoned arguments, it's just that the words that you're typing are incoherent. i guess we can assume that you think racial profiling is ok and being against it is "shitty"?

The software is in some hardware. The hardware can be seen and removed, and can be known when it's removed.

A chemical can't be seen, and can't be removed.

And even if the hardware is super entwined with the building, making it hard to remove, such as tied in with the HVAC system, there likely will be some toggle switch to turn off facial recognition. There's no toggle switch to remove chemicals.

I don't think this is a very good argument. A UPS driver/truck is temporary, and isn't a part of your business. That's like saying you have to put up a Prop 65 disclaimer for your place of business because someones shoes might have a cancer causing chemical in it.

If your place of business is actively adding cameras, and is actively using facial recognition, those are actions that your business has taken. A temporary action of another party should require you to do a disclaimer. Especially if the same action is something they should be disclaiming.

Is it the landlord's job to prevent a tenant from using facial recognition in the tenant's area of the building? I think the tenant is in charge of putting up the disclaimer if the tenant does that.

As for facial recognition in common areas, the landlord can put a clause in the lease agreement requiring tenants not to do that.

If disclaimers are required for facial recognition and a UPS driver has a facial recognition bodycam, I assume it'll be the UPS driver that needs the disclaimer, not every place the UPS driver visits.

Eliminating either by the customer is very difficult. You can try boycotting or contacting the owner to complain. Even then, removing the chemicals is even more difficult, because even if your boycott gets the attention of the owner, the owner will have a harder time removing the chemicals than removing the facial recognition.

The error reduction from applying a different system applies if the source of the error does not manifest itself in both systems (if errors are uncorrelated, you can get an improvement that looks like that implied by the simple application of statistics, but not if they are correlated).

As an example, you can combine human review with automatic facial detection of identical twins and likely not see much (any?) reduction in error rate at all.

Two independent "85% accurate" humans are not 97.7% accurate for identical twins either.

The question is how correlated are human and machine errors. I would guess fairly strongly, in which case human review would add little additional accuracy.

"So where does this leave us for facial recognition?"

Where it leaves us is that it doesn't work, and it can't work. I see no evidence that there is some big reservoir of facial recognition quality to be extracted from the same basic data set. There is all sorts of reasons to believe that it is simply impossible to create a system that can be given a small percentage of the population as the targets and pick them out from millions of samples correctly.

Of all the disciplines, those trained in computer science should be aware of the concept that problems can be fundamentally hard or unsolvable.

However, I've been careful to phrase what I think may be fundamentally unsolvable as being related to "the same basic data set". Expansion of the data set provides other possibilities, and while I'm not ready to declare that adding that data will certainly solve the problem, I'm not ready to declare it as fundamentally unsolvable either. Add portable device tracking, gait analysis, speech analysis, anything else some clever clog can think of, and probably drop the requirement that de facto minimum wagers be asked to confront nominal criminals (I would assert there is no solution to the mismatched incentives there), and the problem may well be solvable. It would, however, require Rite Aid and anyone else planning to use this sort of thing to radically upgrade their hardware.

I would say that it means whatever procedures we build for taking pictures of "known criminals" and applying recognition to someone in your store, they need to be designed and implemented and carried out by people who are aware at all stages that there is a good possibility that they had the wrong person -- how would you want, say, your grandma to be treated if someone wrongly identified her from a criminal picture but wasn't sure? Treat that person that way.

This is hard, we generally do the opposite. Especially in racialized ways in the USA.

AI systems are often promoted as some kind of a solution to this, that somehow avoids human bias/mistakes. I think your comments even revealed that kind of thinking. I don't think they should be thought of that way.

>Face matching is not a hard problem for computers. Face matching is a hard problem, period.

If that were true, then federal law enforcement agencies wouldn't use social media as a database for facially recognizing people suspected of crimes.

You really couldn't have picked a better example to illustrate why the OPs argument was so ignorant. Pretending that reality doesn't exist doesn't make it stop existing.

No one is disagreeing that 1 per store per day is a small number. We're disagreeing with the OPs statement that there's nothing wrong with one false positive accusation of shoplifting per store per day given the obvious consequences of such an accusation in the context of the US system of policing and global blame shifting to the machine, and that given such a context essentially any false positive rate is too high.

So it's useless to say that A is wrong, but not because of B as claimed -- A is wrong for other reasons?

That sure does limit discussion, and human reason generally. I mean, what do you suggest instead?

You have an alternative for handling law breakers aside from just letting them do it?

And in the US, just being arrested -- even if the arrest was a mistake and no charges are filed -- has serious adverse consequences for the arrested person.