[Colloquium] *Correction* [TTIC Talks] 10/14 TTIC Colloquium: Olga Russakovsky, Princeton University

[Alicia McClarin]

*When:*      *Monday, October 14th* at 11:00 am

*Where:*     TTIC, 6045 S. Kenwood Avenue, 5th Floor, Room 526

*Who:         *Olga Russakovsky, Princeton University

*Title:         *Fairness in visual recognition

*Abstract:  *Computer vision models trained on unparalleled amounts of data
hold promise for making impartial, well-informed decisions in a variety of
applications. However, more and more historical societal biases are making
their way into these seemingly innocuous systems. Visual recognition models
have exhibited bias by inappropriately correlating age, gender, sexual
orientation and race with a prediction. The downstream effects of such bias
range from perpetuating harmful stereotypes on an unparalleled scale to
increasing the likelihood of being unfairly predicted as a suspect in a
crime (when face recognition, which is notoriously less accurate on Black
than White faces, is used in surveillance cameras). In this talk, we'll
dive deeper both into the technical reasons and the potential solutions for
algorithmic fairness in computer vision. Among other things, we will
discuss our most recent work (in submission) on training deep learning
models that de-correlate a sensitive attribute (such as race or gender)
from the target prediction.


Host: Greg Shakhnarovich <greg at ttic.edu>

-- 
*Alicia McClarin*
*Toyota Technological Institute at Chicago*
*6045 S. Kenwood Ave., **Office 518*
*Chicago, IL 60637*
*773-834-3321*
*www.ttic.edu* <http://www.ttic.edu/>
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