ASGE Annual Postgraduate Course: Clinical Challenges and Real-Time Decision Making in GI Endoscopy (Live and Virtual) | May 2023-Clinicians Trust in AI, Fairness and Bias-Why is it Important?

Video Transcription

Video Summary

Dr. Sravanti Parasa discusses the importance of clinicians' trust in AI and addresses the issues of bias and fairness in AI algorithms. She emphasizes the need for clinicians to understand how AI works and adapt to it in order to provide better care to patients. Dr. Parasa highlights the existence of bias in AI algorithms, stating that they perpetuate the biases present in the data sets they are trained on. She gives examples of algorithms in healthcare that have exhibited bias, such as predicting higher healthcare costs for white patients due to the biased data used in their development. Dr. Parasa outlines key considerations for clinicians when evaluating AI algorithms, including relevance of the use case to their patient population, understanding of the algorithm and its metrics, data transparency, and the need for trustworthy AI. She also touches on the topics of model governance, explainability, transparency, and data security. Dr. Parasa concludes by mentioning the efforts of various organizations in developing guidelines and frameworks to address ethical and fairness issues in AI.

Asset Subtitle

Sravanthi Parasa, MD

Keywords

trust in AI

bias in AI algorithms

clinicians and AI

algorithm bias in healthcare

ethical guidelines for AI