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Modules

Module 1 75 min

Algorithmic Bias — Foundations and Frameworks

Defining algorithmic bias, its taxonomy (historical, representation, measurement, aggregation), and theoretical frameworks for analyzing bias in healthcare AI systems.

Module 2 75 min

Structural Racism in Medical Data

How historical clinical practices — from race-based medicine to exclusionary research enrollment — created the training data that modern AI inherits. Analysis of key datasets and their demographic composition.

Module 3 75 min

Dermatology AI and the Skin Tone Gap

Deep dive into the threefold accuracy gap in dermatology AI across skin tones. Students analyze the Fitzpatrick scale, dataset composition studies, and proposed mitigation strategies.

Module 4 75 min

Race-Corrected Algorithms — From eGFR to Spirometry

Examining how race was embedded as a variable in kidney function, lung capacity, and cardiac risk calculations — and the ongoing effort to remove it. Case study: the 3.3 million reclassified patients.

Module 5 75 min

LLMs and the Perpetuation of Medical Myths

When every major language model perpetuates debunked race-based biological claims. Students test real AI systems and compare outputs to published evidence, examining how misinformation scales.

Module 6 75 min

Intersectionality — When Biases Compound

Gender, age, geography, socioeconomic status, and disability intersect with race to create compounding layers of algorithmic disadvantage. Framework for analyzing multi-axis bias.

Module 7 75 min

Regulation, Accountability, and the FDA Gap

The FDA has cleared 900+ AI medical devices, but consumer health chatbots operate in a regulatory vacuum. Students analyze the regulatory landscape, proposed frameworks, and accountability mechanisms.

Module 8 75 min

From Analysis to Advocacy — Capstone Project

Students select a healthcare AI system, conduct an original bias audit using course frameworks, and present findings with actionable policy or design recommendations.

Download entire college curriculum (.zip) ↓

Creative Commons BY-NC-ND 4.0

All Diagnose the Bias curriculum materials are licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Algorithmic Bias in Healthcare AI — Seminar