AI tools are already being used in hospitals, clinics and doctors’ offices. Who is making treatment decisions, and who is responsible if an AI gets it wrong? To address these questions, Science and Technology editor Eric Smalley hosted a webinar with panelists Dr. Jodyn Platt, an Associate Professor Health Management and Policy at the University of Michigan, and Dr. David Kao, Medical Director at the Colorado Center for Personalized Medicine.
Platt’s work explores how data and technology can be used responsibly to improve health while earning and sustaining public trust. Kao’s research is focused on using big data analysis to personalize management of heart disease, most notably heart failure.
Eric Smalley: What are the main types of AI that you see being used in healthcare?
David Kao: There’s a temptation to think of AI in healthcare in sort of a binary way: You’re either doing it like the old country doctor or like Skynet from Terminator where it’s automatically making decisions about living or dying for all these people. And the truth is it’s a continuum.
In Colorado, we focus on using AI to augment clinical decision-making. There are machine learning-based algorithms that will monitor the electronic health record continuously, and if someone starts to look worse, they’ll alert the team. They’re not decisions in and of themselves. They’re just better information on which to make a decision.
