In AI We Trust?

Ziad Obermeyer is a Professor of Health Policy and Management
at the UC Berkeley School of Public Health where he conducts research at the intersection of machine learning, medicine, and health policy. Previously, he was a professor at Harvard Medical School and consultant at McKinsey & Co. He continues to practice emergency medicine in underserved parts of the US and is also a co-founder of Nightingale Open Science, a computing platform giving
researchers access to massive new health imaging datasets. In this episode, you'll hear how he ended up co-authoring the seminal study to identify bias in AI health systems, published in Science in 2019, and whether you should be using his Algorithmic Bias Playbook.

Links to referenced articles and playbook:
http://ziadobermeyer.com/research/

https://www.chicagobooth.edu/research/center-for-applied-artificial-intelligence/research/algorithmic-bias

Show Notes

Ziad Obermeyer is a Professor of Health Policy and Management
at the UC Berkeley School of Public Health where he conducts research at the intersection of machine learning, medicine, and health policy. Previously, he was a professor at Harvard Medical School and consultant at McKinsey & Co. He continues to practice emergency medicine in underserved parts of the US and is also a co-founder of Nightingale Open Science, a computing platform giving
researchers access to massive new health imaging datasets. In this episode, you'll hear how he ended up co-authoring the seminal study to identify bias in AI health systems, published in Science in 2019, and whether you should be using his Algorithmic Bias Playbook.

Links to referenced articles and playbook: 
http://ziadobermeyer.com/research/

https://www.chicagobooth.edu/research/center-for-applied-artificial-intelligence/research/algorithmic-bias

What is In AI We Trust??

In AI We Trust? is a podcast with Miriam Vogel of EqualAI and Kay Firth-Butterfield of the Centre for Trustworthy Technology that surveys the global landscape for inspiration and lessons in developing responsible, trustworthy artificial intelligence. Each episode aims to answer a ‘big question' in ethical AI with prominent lawmakers, leading thinkers, and internationally renowned authors.