NEJM AI Grand Rounds

Interrogating AI Fairness and Bias in Dermatology and Beyond with Dr. Roxana Daneshjou

Jan 17, 2024

Dr. Roxana Daneshjou, Assistant professor at Stanford specializing in dermatology, shares her journey in AI research. She discusses AI fairness and bias in dermatology and the challenges of integrating language models in healthcare. Dr. Daneshjou emphasizes the need for interdisciplinary collaboration and highlights the importance of addressing disparities in AI performance across diverse skin tones.

01:01:07

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Episode guests

Roxana Daneshjou

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Quick takeaways

Addressing systemic bias in AI systems is crucial for healthcare fairness.

Representation and diversity in datasets are essential for improving fairness in dermatology AI.

Combining human expertise and AI capabilities can help reduce bias in large language models.

Deep dives

The importance of building fair AI systems in healthcare

Roxanna Dineshjou, an assistant professor of biomedical data science at Stanford University and a practicing dermatologist, emphasizes the need for building fair AI systems in healthcare. She discusses how biases in human data can be picked up by large language models, highlighting the importance of addressing systemic issues of bias in both humans and technology. While AI has the potential to exacerbate disparities, Roxanna stresses the need for interdisciplinary collaboration and the integration of domain-specific expertise to ensure fairness in AI in healthcare.

Introduction

3min

Career Development and Research Background in AI and Medicine

4min

Integrating AI into Dermatology and Healthcare

6min

Measurement of Skin Tone in Dermatology

20min

The Impact of Language Models in Medicine

13min

The Impact of LLMs on Medicine and a National Park Ranger's Dream Job

3min

AI, Medicine, and the Role of Clinicians

11min

The Challenges of Balancing Work and Parenthood

6min

In this episode of the AI Grand Rounds podcast, Dr. Roxana Daneshjou shares her journey from a childhood influenced by early exposure to science to her current role as an assistant professor at Stanford. Her path includes a critical shift during medical school, where her interest in computational methods and human genomics led her to pursue both an M.D. and a Ph.D. Her specialization in dermatology was driven by its visual nature and the opportunity to form long-term relationships with patients. Dr. Daneshjou emphasizes the importance of AI in addressing fairness and bias in dermatology, discussing her research on disparities in AI performance across diverse skin tones. The podcast also delves into broader issues of AI in health care, discussing the potential and challenges of integrating large language models into medical practice, and highlighting the need for interdisciplinary collaboration between clinicians and computer scientists in AI development. Dr. Daneshjou’s optimism for the future centers on the new generation of medical professionals who are increasingly concerned about fairness and equity in AI.

Transcript.

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NEJM AI Grand Rounds

Interrogating AI Fairness and Bias in Dermatology and Beyond with Dr. Roxana Daneshjou

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

The importance of building fair AI systems in healthcare

Examining algorithmic bias in dermatology AI

Challenges of algorithmic bias in large language models

The role of clinicians in AI development

Balancing academic career and parenting

Remember Everything You Learn from Podcasts