Urban Crime Prediction: The Data, Ethics, and Biases of Predicting Events

Explore a thought-provoking lecture from the University of Chicago's Harper Lecture Series where Professor Ishanu Chattopadhyay delves into the complex intersection of artificial intelligence and urban crime prediction. Learn about cutting-edge AI models used in law enforcement, examining both their potential benefits and ethical concerns, particularly regarding algorithmic bias and surveillance. Discover how UChicago researchers are using these technologies to analyze police resource allocation patterns and their implications for social equity. Through detailed discussions of AI methodology, including fractal networks, digital twins, and predictive performance metrics, gain insights into how these tools can be applied across various urban contexts, from Chicago to Boston. Understand the technical aspects of crime prediction, including measurement error analysis, neural network comparisons, and event logging, while considering crucial policy implications and strategies for fair law enforcement practices. The hour-long presentation addresses critical questions about racial stereotyping, the role of AI in public safety, and the future directions of predictive policing technologies.