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

I view machine learning as the technical foundation for a new, independent scientific field: medicine. The goal of that field is helping doctors make better decisions, and helping researchers make new discoveries.

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, and Dandelion, a venture-backed startup, to bring high-quality clinical data online and jump-start innovation.

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.