It sounds preferable to calculate risk scores deterministically rather than rely on Law Enforcement's discretion.
Risk scores are computed for every traffic stop, wouldn't you want to take that process away from the office and give it to a computer?
Risk scores are computed for every traffic stop, wouldn't you want to take that process away from the office and give it to a computer?
Humans are accountable, changeable, cross-examinable. Computer systems are not. Please do not give enforcement systems over to computer systems, and have the bias calcified forever.
Computer systems are accountable, changeable, and cross-examinable. Arguably more so than humans.
I do stipulate that computer systems can be racist or otherwise biased and can be "just wrong".
The human mind tends to be set in its ways.
The history of junk forensic science has pretty clearly demonstrated that nobody in law enforcement cares about testing their biases, or improving the processes.
If it gets them results, they'll use it.
With algorithms, I think it can be done... but given how subtle the negative effects can be, the process must be stringent and err on the side of caution. In other words, any algorithm should be assumed to be biased until proven otherwise, and with a relatively high bar at that. There should be clear technical standards for what constitutes a valid proof. The testing process should be reproducible by third parties. And there should be a straightforward way to challenge either the process itself, or its results in any particular case.
In practice, given how low our bar for law enforcement accountability is today in other cases - including those where people die or are badly hurt - I'd say that we need to fix those issues first before talking about face recognition and its regulation in this context. And until then, it should be off-limits, because the potential for abuse is so high.
I agree. But the reason that we don't have that right now isn't related to whether or not computers are involved, and introducing algorithms won't solve that situation.
The reason that police accountability is weak is political.
Absolutely. One major positive outcome of the OJ Simpson trial was how Simpson's attorneys completely trashed the police handling of forensic evidence on a national stage, forcing law enforcement across the country to raise their game.
Please never enter politics.
What I want is this process to be cross-examinable. You can't cross-examine an algorithm in any meaningful way at a jury trial. You can't cross-examine a neural network at all.
You know all the bullshit about how police dogs are used to conduct illegal searches, and how you can't cross-examine a dog? It'll be like that, but much, much worse.
https://en.m.wikipedia.org/wiki/Bayesian_inference#Applicati...
What we have today is institutional racism based on people’s gut reactions. An NN can be tested and shown that given all other factors it risks race, or any other protected class higher than it should.
Institutional racism is not based on people's gut reactions. Institutional racism is based on flawed algorithms. Not computer algorithms in this case, but bureaucratic ones.
I don't see how a flawed computer algorithm would be any easier to correct than a flawed bureaucratic algorithm.
To address things like institutional racism, you have to change the institution. That's a human problem for which there is no technological solution (although technology can certainly be one of the tools used to create a larger change).
Since we've not made much traction on blackbox testing bureaucracies, I'm going to go ahead and say that blackbox testing algorithms will be even worse. (For some dumb reason, people are inclined to trust algorithms.)
I'm just intervening to point out that what you're saying is not what the paper you linked implies. Its title is "Semantics derived automatically from language corpora contain human-like biases", and the general conclusion you could derive from it is that AI programs reflect the stereotypes ... of the data they are trained with. This is why they use the right word: stereotype, instead of the charged word you used: prejudice.