What does it take to fund a Nobel Prize-winning idea? Apparently, not a Nobel Prize. AlphaFold solved the shape of 200 million proteins in one shot, a problem that used to take a PhD four years per protein, and biotech investment still fell. Funding isn’t the only problem tech is facing: it has also never been good at talking to the people it builds for. Is that a coincidence?
In this episode, we speak with Dorothy Chou, who ran Google DeepMind's Public Engagement Lab for nine years. She now advises DeepMind and chairs UCLPartners, an organization connecting new technology to the UK's National Health Service.
We cover:
Chapters:
0:00 Cold open
1:00 Why Dorothy Chou is leaving Google DeepMind after nine years
4:26 How do we actually use AI for good?
6:12 What is DeepMind's public engagement lab?
9:53 The AlphaFold breakthrough, explained
12:37 Why funding science is stuck in the 20th century
15:30 How governments and investors should fund AI for science
19:21 Other AI for science projects worth watching
22:11 What is blended finance for science?
24:44 Is funding for AI-driven science finally picking up?
26:05 What could an AlphaFold moment look like in 10 years?
28:33 Why venture capital and biotech investors don't understand each other
30:08 How AI could level the playing field for science funding
31:43 The fusion project Dorothy wishes more people knew about
33:04 Why public imagination matters as much as public policy
36:06 How do we build more public imagination?
39:11 Advice for people who want to work at this intersection of AI and science
41:11 The best advice Dorothy's ever received
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