In the clinic, doctors rely heavily on complex images and waveforms. We have a science of molecules, genes, and proteins - where is the field that makes sense of the data doctors use every day?

I view machine learning as the technical foundation for a new science of medicine. This will help doctors make better decisions (whom to test for a heart attack), and help researchers make new discoveries (new causes of pain, personalized body temperature set-points).

I’m generally optimistic about machine learning, but my work has also shown where it can go wrong, for example how widely used algorithms automate bias. That work has impacted how organizations build and use AI, and how lawmakers and regulators hold AI accountable.

Scientific fields are built on data, but clinical data are hard to come by. I co-founded Nightingale, a nonprofit that makes imaging datasets available for research, and Dandelion, a venture-backed startup that provides the data needed to jump-start AI innovation in health.

I’m a Chan Zuckerberg Biohub Investigator, and a Research Associate at the National Bureau of Economic Research.

I was named one of the 100 most influential people in AI by TIME magazine, and an Emerging Leader by the National Academy of Medicine.