Ask HN: Any open source code/materials on predicting future crimes based on data?

It's a similar problem to using ML to give people credit scores.

If the training data includes a lot of minorities and poor people breaking laws / delinquent payments, then your ML will simply key on race/economic status as a predictor.

So you've built a system that simply targets those groups.

But you might object and say that this race/economic status targeting gives the highest accuracy! It was only learned in the training data, after all. You can make a great classifier that is extremely unfair.

So you have to realize there is a conflict here between accuracy and fairness. This means there is a conflict between observational data (training), and using that data to produce decisions/outcomes.

If you make decisions/outcomes that reinforce the training data, you do not give racial groups/low economic status people a chance to improve their lives.

That is extremely inhuman, predatory, and unfair.

https://www.youtube.com/watch?v=MfThopD7L1Y

Basically, one instance of bias is the fact that many crime-prediction models are trained on police data, which means they will predict crime in places more often targeted by the police anyway. Then the model predictions even amplify that effect, since more training data may be generated from the places now more often policed, etc.

There's lots of resources out there on AI fairness these days. I think everyone who tries stuff like crime prediction should read up on that topic.