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Building Algorithms that Work for Everyone: Natural Language Processing Tools for Bias Reduction in Child Welfare Systems

Oftentimes, the development of algorithms are divorced from the environments where they will eventually be deployed. In high stakes contexts, like child welfare services, policymakers and technologists must exercise a high degree of caution in the design and deployment of decisionmaking algorithms or risk further marginalising already vulnerable communities. This talk will seek to explain the status quo of child welfare algorithms, what we miss when we fail to include context in the development of algorithms, and how the addition of qualitative text data can help to make better algorithms.

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This is an online event, available on the Centre for Ethics YouTube Channel, on Wednesday, March 30. Channel subscribers will receive a notification at the start. (For other events in the series, and to subscribe, visit YouTube.com/c/CentreforEthics.)

Kamilah Ebrahim
iSchool
University of Toronto

Erina Moon
iSchool
University of Toronto

Wed, Mar 30, 2022
04:00 PM - 05:30 PM
Centre for Ethics, University of Toronto
200 Larkin