Dear workshop community,
We will convene for the Applied Statistics Workshop (Gov 3009) tomorrow on
Wednesday (2/13).
The speaker is* Ilya Shpitser *(Johns Hopkins Computer Science) who will be
presenting his work "Fair Inference on Outcomes."
*Where:* CGIS Knafel Building, Room K354 (see this link
<https://map.harvard.edu/?bld=04471&level=9> for directions).
*When: *Wednesday, February 13th at 12 noon - 1:30 pm.
*Abstract: *Systematic discriminatory biases present in our society
influence the way data is collected and stored, the way variables are
defined, and the way scientific findings are put into practice as policy.
Automated decision procedures and learning algorithms applied to such data
may serve to perpetuate existing injustice or unfairness in our society.
We consider how to solve prediction and policy learning problems in a way
which breaks the cycle of injustice'' by correcting for the unfair
dependence of outcomes, decisions, or both, on sensitive features (e.g.,
variables that correspond to gender, race, disability, or other protected
attributes). We use methods from causal inference and constrained
optimization to learn outcome predictors and optimal policies in a way that
addresses multiple potential biases which afflict data analysis in
sensitive contexts. Our proposal comes equipped with the guarantee that
solving prediction or decision problems on new instances will result in a
joint distribution where the given fairness constraint is satisfied. We
illustrate our approach with both synthetic data and real criminal justice
data.
*All are welcome! Lunch is provided! *
Best,
Connor Jerzak
Applied Statistics Workshop -- Graduate Student Coordinator
An anonymous feedback form for the workshop can be found here at this link
<https://docs.google.com/forms/d/e/1FAIpQLScp4lPVBtp4Akf6K6ggmfcTUSIUHEJX89-CU8HWrQPpe9pjTw/viewform?usp=sf_link>.
Workshop listserv sign-up at this link
<https://lists.fas.harvard.edu/mailman/listinfo/gov3009-l>.
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