Toolkit for Addressing Algorithmic Bias

Author(s): Patrick Spencer, Paul Chernousov

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This toolkit outlines a structured approach that covers everything from initial risk assessment to ongoing monitoring, providing actionable steps for each phase. It emphasizes the importance of a multi-disciplinary team and offers a range of methods to identify and rectify bias, including data audits, stakeholder engagement, and both internal and external evaluations.

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