This lecture is part of the Algorithmic Fairness Presidential Lecture Series in Mathematics and Computer Science.
Registration link:
https://www.eventbrite.com/e/fairness-randomness-and-the-crystal-ball-registration-243769028727
Registration is required for this in-person event.
Prediction algorithms score individuals or individual instances, assigning to each one a number in the range from 0 to 1. That score is often interpreted as a probability: What are the chances that this loan will be repaid? How likely is this tumor to metastasize? What is the likelihood that this person will commit a violent crime in the next two years? A key question lingers: What is the probability of a non-repeatable event? Without a satisfactory answer, we cannot even specify the goal of an ideal algorithm.
In this talk, Cynthia Dwork will introduce ‘outcome indistinguishability’ — a desideratum with roots in complexity theory. She will situate the concept within the 10-year history of the theory of algorithmic fairness and the four-decade literature on forecasting.
Dwork is a professor of computer science at Harvard University, affiliated faculty at Harvard Law School, and a distinguished scientist at Microsoft. Her work has established the pillars of fault-tolerant distributed systems, modernized cryptography to the ungoverned interactions of the internet and the era of quantum computing, revolutionized privacy-preserving statistical data analysis, and launched the theory of algorithmic fairness. She is the recipient of numerous awards and is a member of the National Academy of Sciences, the National Academy of Engineering, the American Academy of Arts and Sciences, and the American Philosophical Society.
SCHEDULE
Doors Open: 5:30 p.m.
Lecture: 6:00 – 7:00 p.m.