Machine Learning & AI for Healthcare

December 1 - 2, 2020
| Digital Summit

Bias in Machine Learning and AI Algorithms

The challenge of IT, code and algorithms is a small error can upend your entire effort. Ziad Obermeyer, associate professor at the Berkeley School of Public Health, understands this and recently uncovered how the questions asked can create serious racial and socioeconomic repercussions. By changing the wording of a simple question, Obermeyer and his team were unable to create a more equitable and fair algorithm that answered the question asked. Obermeyer and Kadija Ferryman, industry assistant professor of ethics and engineering, NYU Tandon School of Engineering, will discuss how this issue impacts patient care, how the industry can change moving forward and how technology, while progressing care and outcomes, has the ability to inadvertently keep systemic racism afloat. 

Key takeaways:
What are the questions you need to ask yourself?
What is the "right" question?
How to parse your results - how to uncover bias.

Session Details

December 1, 2020
2:26 PM - 2:59 PM


Kadija Ferryman
Industry Assistant Professor
NYU Tandon School of Engineering
Ziad Obermeyer
Blue Cross of California Distinguished Associate Professor
University of California, Berkeley