Building Consensus on AI Systems with the Chicago Police Department
We will discuss how to balance competing aims in the policy space -- namely, (1) how can you use AI modeling so it's interpretable for completely non-technical people, (2) how can you build trust in that AI system to produce policy interventions among stakeholders with competing goals, and (3) what considerations should you make during deployment to ensure buy-in for the system created? In this session, we will consider simplified examples from the criminal justice space in order to come up with best practices. I'll draw on my work at the UChicago Crime Lab, where I've spent the past few years helping to build a data-driven Early Intervention System (EIS) for police officers. This discussion will be in general terms from my own personal view.
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