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When & Where
Date: 
Fri, February 26, 2021 - 2:00 PM to 4:00 PM
Location: 
Remote (Zoom link sent by email and calendar invite)
Description
Type: 

Machine learning models are used far and wide, from criminal justice to health to content moderation. In practice, machine learning can often replicate and amplify biases against marginalized groups. How do we identify and measure these biases? What are different metrics used in fairness audits of machine learning models? This 2-hr workshop reviews critical and technical components for FairML. By the end of the workshop, participants will be armed with tools and theory to articulate fairness concerns and evaluate machine learning models.

Training Keywords: 
Machine Learning
Primary Tool: 
None
Details
Training Learner Level: 
Beginner
Training Host: 
D-lab Facilitator: 
Evan Muzzall
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