Hype around AI in medicine often ignores two key risks:
- patterns of automation contribute to centralization of power
- medical knowledge is limited by the systemic refusal to trust patient expertise
MSc Immunology student; cofounder fast.ai // past: math PhD, director USF Center for Applied Data Ethics, professor at QUT, data scientist
Hype around AI in medicine often ignores two key risks:
- patterns of automation contribute to centralization of power
- medical knowledge is limited by the systemic refusal to trust patient expertise
Even though my main interests are immunology & AI, I was pleasantly surprised to learn several fascinating facts about insects in my microbiology classes last semester! I wrote a post:
It was a nice walk down memory lane going through the fastai blog archives choosing posts to port over-- lots of stuff I had forgotten about. https://www.fast.ai/#listing-listing-page=5
Going forward, I will be blogging at https://rachel.fast.ai/ I still believe deeply in the mission of fastai, but I'm currently focused on studying immunology.
I have ported some of my old posts from both fastai & medium over to the new site.
@erikavaris Thank you ๐
@algal Thanks Alexis!
After over a decade working as a data scientist and AI researcher, I have gone back to school for a Masters in Immunology. When I become fascinated by a topic, I want to learn as much as I can.
My ultimate goal is to apply my machine learning & data ethics skills to immunology, but I want to make sure I fully understand the underlying domain & relevant context first. With ML, itโs important to not just be a hammer searching for a nail.