3 ms·
> It depends - These models are often non-transparent in terms of how they calculate, so what if the AI/model decides/calculate that a higher percentage of mino
by bko 5y ago
> It depends - These models are often non-transparent in terms of how they calculate, so what if the AI/model decides/calculate that a higher percentage of minorities in an area is a high predictor of crime, thus indirectly creates a policy that, for instance, areas with high levels of ethnic minorities require higher levels of policing or harsher restrictions (i.e. curfews, more CCTV e.t.c.).
It's pretty simple to make the models transparent. Just select the inputs you want the model to have access to. You shouldn't be feeding your model the percentage of minorities in an area.
What's not transparent is how humans make decisions. You can't tell a human to consider only these characteristics but not these others ones.
> If it's just a basic 'well murders happen between these hours on this street so we will put a police officer there' then of course that should happen, but that's not really policing based on AI/ML, it's just based on basic statistics.
I don't see how you make a meaningful separation between the two. Either you can use predictive models or not. It's hard to carve out "use predictive models but not too predictive". The more likely scenario is just not using any model and distributing police resources uniformly regardless of need.
- Closi 5y ago> It's pretty simple to make the models transparent. Just select the inputs you want the model to have access to. You shouldn't be feeding your model the percentage of minorities in an area. That doesn't make the model transparent, it just makes the input and output transparent, but it's still a black box. It's nice to say that everyone will ensure that the model isn't fed with information which will allow it to make decisions or be biased based on sex / gender / race / income but in reality accidental racial bias has already shown up multiple times in applications where it should be easier to detect than an invisible 'crime prediction' algorithm that the general public won't have access to but public policy will be implemented on the basis of. > I don't see how you make a meaningful separation between the two. Either you can use predictive models or not. It's hard to carve out "use predictive models but not too predictive". The more likely scenario is just not using any model and distributing police resources uniformly regardless of need. I make a meaningful separation because one has clear logic which can be viewed to be unbiased, and the other has a black box calculating it.
- bko 5y agoAgain, whats the alternative? Human being making this decisions. Human beings with their own biases and life experiences. I trust a model where I can at least control the inputs it considers, is auditable, and created by intelligent thoughtful people than some police chief. > accidental racial bias has already shown up multiple times in applications where it should be easier to detect than an invisible 'crime prediction' algorithm that the general public won't have access to but public policy will be implemented on the basis of. The primary victims of violence are often of this same race as the "accidental racial bias" you're talking about. You're not doing anyone any favors by misallocating police resource to be more "equitable" without considering actual need. Only 7% of Americans want less policing in their neighborhoods. I imagine people that live in high crime areas would prefer more policing. https://thehill.com/hilltv/what-americas-thinking/562738-poll-44-percent-want-more-police-in-their-community-compared-to https://thehill.com/hilltv/what-americas-thinking/562738-pol...