aix 2022 on demand hero 09

End-to-End Bias Mitigation

Preventing AI bias is a serious issue for every AI project. The increase in AI adoption has also led to a greater risk of companies implementing systems that behave in a biased manner. See how DataRobot offers an end-to-end workflow for tackling AI bias. Understand the tools that help detect and mitigate biased behavior, perform root cause analysis, and monitor biased behavior over time.

Key Objectives

  • Define model bias and understand the risks associated with model bias.
  • Understand how to use DataRobot to test models for bias.
  • Mitigate model bias using DataRobot and evaluate any tradeoffs that come with mitigation.


Natalie Bucklin
Natalie Bucklin

Senior Product Manager, DataRobot

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