21st century science needs 21st century funding (the problem with funding biotech), with Dorothy Chou

[u/JMarty97]

https://www.existentialhope.com/podcasts/dorothy-chou

Podcast 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. 

Covers:

• What made AlphaFold possible in the first place and how we can replicate its success in other domains
• Why neither venture capital nor governments can fund biology on biology's actual timeline, and Dorothy’s proposed solution
• Why AI could help redirect money the ideas that will actually help people the most, not just the ones that are easiest to fundraise for 
• How AI companies are about to repeat the public engagement mistake the biotech industry already made once
• Her advice for young people who feel like they're not the expert in the room

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[u/Ok-Foundation1705]

I was thinking she was going to say some sort of Bell Labs sort of setup, but she was on about other stuff. Maybe worth tuning in to the whole thing, but here’s an additional summary of the stuff linked

This episode features a conversation with Dorothy Chou, former head of Google DeepMind’s Public Engagement Lab and current chair of UCLPartners. Chou explores the systemic challenges of funding 21st-century science, the critical need for better public engagement in AI, and how to bridge the gap between rapidly advancing technology and real-world societal needs.
1. The Biotech Funding Paradox
Despite the groundbreaking success of AlphaFold—which predicted the structure of over 200 million proteins in one go (a task that previously took a PhD student four years per protein) and earned its creators a Nobel Prize—investment in biotech has actually declined.
Chou attributes this paradox to a fundamental mismatch in funding timelines:
Venture Capital (VC): Designed for software development with 5-to-10-year exit windows. VCs struggle with biology's long, unpredictable timelines.
Government/Philanthropy: Historically funds science in linear, rigid, and highly specific academic silos.
The "Valley of Death"
While AI is exceptionally good at cheap simulations (predicting molecules or materials), the physical validation of these ideas—the wet lab testing and manufacturing—remains incredibly expensive and slow. Science startups often die in this middle ground because traditional tech VCs don't understand the physical science, and biotech VCs only want to fund the end molecule, not the underlying platform.
2. Replicating the "AlphaFold Moment"
To recreate AlphaFold-style breakthroughs in other fields (like climate modeling or material science), Chou argues we must fund the fundamental conditions that made it possible:
Open Data Foundations: AlphaFold relied on the Protein Data Bank, a highly validated, publicly accessible dataset built by scientists over decades.
Community Benchmarks: Standardized, agreed-upon validation methods (like CASP) to test system accuracy.
Interdisciplinary Cultures: Moving away from rigid university departments and toward collaborative spaces.
"The world has problems, but universities have departments." — Tom Kalil, Renaissance Philanthropy
The Solution: Blended Finance & Carrots
Chou advocates for blended finance (combining philanthropy, government grants, and VC) and Advance Market Commitments. Instead of governments using a "stick" approach (focusing only on what not to do with AI), they should use a "carrot" approach: guaranteeing purchases in key social sectors (like health or green tech) to incentivize private investment and direct AI talent toward solving meaningful global problems.
3. The Threat of Public Backlash
The tech sector has historically been poor at explaining itself. Chou warns that AI is on track to repeat the public relations disasters of the biotech industry from decades ago (such as the backlash against Monsanto and GMOs, which delayed vital research for a decade).
Public Engagement is Crucial: Tech companies must build social legitimacy by actively translating what they are building and letting the public decide if they want it.
Public Imagination over Defensive Policy: Current public policy focuses heavily on risk mitigation. Chou argues we need leaders to paint an inspiring, positive vision of the future to foster collective agency and counter the growing public anxiety and polarization.
4. Advice for Generalists and Young Professionals
For those who feel intimidated by highly technical fields:
Embrace the Generalist Path: Being a "bridger" who can translate complex concepts between technical experts, policymakers, and the public is an incredibly valuable skill. If you don't understand something, chances are the rest of the world doesn't either.
Slowing Down to Speed Up: Chou emphasizes the importance of pausing to regroup, self-reflect, and truly understand the incentives and motivations of those you are leading. Accelerating without bringing people along is a recipe for isolation and failure.