mathematics

computer science

social science

medicine

AI/ML learning theory and applications

Complex systems

Implication of AI in Future of Societay

University of Chicago Medicine

The Laboratory for Zero Knowledge Discovery

ishanu chattopadhyay

Problem: Event-level prediction in social systems,

e.g. predicting crime before it happens

Predictive intelligence for security

Can we predict complex spatio-temporal stochastic processes?

Rotaru, Victor, Yi Huang, Timmy Li, James Evans, and Ishanu Chattopadhyay. "Event-level prediction of urban crime reveals a signature of enforcement bias in US cities." Nature human behaviour 6, no. 8 (2022): 1056-1068.

Clip from Joe Rogan's Podcast aired July 2022 for educational/non-commercial purposes under fair use guidelines.

The Problem of Free Will

social

behavior

prediction

Predict the spatio-temporal event risk
NOT individual people
CANNOT be used for individual "pre-arrests"

No manual selection of factors
No "lists"
Uses only de-identified data

Can use the models to "audit" the state
Identify and reveal enforcement biases
Democratization of AI

The Underlying Math

Hotspots?

Very different from past efforts

Not based on standard "Deep Learning"

The Underlying Math

Not based on standard "Deep Learning"

Forecasting rare events in multi-variable stochastic evolution requires new modeling architecture

Learn local "activation functions" as symbolic probabilistic transducers

Assemble these local predictors into a "fractal net"

Applies to any rare/extreme event phenomena

Ishanu Chattopadhyay, Yi Huang, James Evans et al. Deep Learning Without Neural Networks: Fractal-nets for Rare Event Modeling, 26 October 2020, PREPRINT (Version https://doi.org/10.21203/rs.3.rs-86045/v1

93% accuracy

87% AUC

~70% specificity at ~80% sensitivity

Chicago Predictive Performance

10 actual crimes:

11 predicted:

8 correct:

2 missed:

3 false alarms

1 Week in advance

Within ~2 city blocks

ONLY Past eventlog as input