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Emily Sheehy

Created on January 20, 2026

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Real-World Impact

Click each card to explore how bias in training data shapes AI outcomes.

An algorithm used to prioritize patient care was found to systematically underestimate the health needs of Black patients because it used healthcare spending as a proxy for health needs—but Black patients historically had less access to healthcare. Additional reading:

Amazon scrapped an AI recruiting tool that penalized resumes containing the word "women's" because it was trained on a male-dominated applicant pool. Additional reading:

Risk assessment tools have shown racial disparities in predicting recidivism. Additional reading:

Use this side of the card to provide more information about a topic. Focus on one concept. Make learning and communication more efficient.

Use this side of the card to provide more information about a topic. Focus on one concept. Make learning and communication more efficient.

Use this side of the card to provide more information about a topic. Focus on one concept. Make learning and communication more efficient.

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Healthcare

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Criminal Justice

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Hiring

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Cost-Based Decisions, Unequal Care

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Predictive Tools, Uneven Outcomes

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Training Data and Hiring Bias