Michael Webb
Showing 1–4 of 4 transcripts.
- 80,000 Hours2h 19m
Serendipity, weird bets, & cold emails that actually work: Career advice from 16 former guests
Luisa, Holden Karnofsky, Jeff Sebo, Dean Spears, Michael Webb, Michelle Hutchinson, Benjamin Todd, Chris Olah, Karen Levy, Leah Garcés, Spencer Greenberg, Danny Hernandez, Sarah Eustis-Guthrie, Hannah Ritchie, Alex Lawsen, Pardis Sabeti, Varsha Venugopal, Matt
This event outlines a strategic framework for early-career development that prioritizes building transferable high-level aptitudes over predicting specific cause areas. It details how to leverage AI tools for rapid upskilling and social networking while identifying human-centric skills like trust-building and empathy as future-proof assets. Additionally, the discussion provides actionable protocols for managing career risk through regular re-evaluation points, testing assumptions via low-cost trials, and recognizing toxic social dynamics to ensure long-term professional resilience.
- 80,000 Hours3h 12m
AGI misconceptions & disagreements: Hashing it out with Rob, Luisa, & past guests
Luisa Rodriguez, Rob Wiblin, Ajeya Cotra, Holden Karnofsky, Ian Morris, Nick Joseph, Richard Ngo, Tom Davidson, Michael Webb, Carl Shulman, Zvi Mowshowitz, Hugo Mercier, Robert Long, Anil Seth, Lewis Bollard, Rohin Shah
Rob Wiblin, Ian Morris, and other leading experts convened to assess that human "business as usual" is unlikely given resource constraints, predicting a future defined either by extinction or a profound transformation into superhumans. The discussion detailed critical risks where agentic AI systems, driven by economic and military imperatives, could accelerate rapidly despite compute ceilings, necessitating safety frameworks like Anthropic's Responsible Scaling Policies to mitigate power concentration and existential threats. Ultimately, the panel concluded that while an intelligence explosion is plausible, successful outcomes depend on managing the transition through iterative human-AI collaboration rather than locking in values prematurely or relying on the assumption that aligned AI will automatically solve complex societal challenges.
- 80,000 Hours32 min
Highlights: Michael Webb on whether AI will soon cause job loss, lower incomes, & higher inequality
Recent analysis of AI exposure curves and historical automation precedents reveals that while advanced technologies primarily threaten high-skill professional roles, adoption is often delayed by regulatory barriers and collective action from powerful interest groups like medical and legal boards. Unlike sudden mass displacement, job elimination frequently occurs through gradual "natural wastage" or is offset by demand elasticity that expands service networks, as evidenced by the banking sector's response to ATM technology. Despite the potential for rapid technological advancement, the transition to a highly automated economy is projected to proceed over decades due to structural inertia, the necessity of reorganizing corporate processes, and enduring demand for non-cognitive human tasks.
- 80,000 Hours3h 31m
Will AI cause job loss, lower incomes and higher inequality — or the opposite? | Michael Webb
Michael Webb outlines how generative AI uniquely targets upper-middle-skilled occupations while low-skill workers see relative productivity gains, driven by faster adoption curves compared to historical technologies like electricity. Although the technology threatens specific white-collar roles through task automation, Webb argues that natural wastage and the rise of human-intensive service sectors will mitigate mass unemployment, with long-term wage stability hinging on regulatory barriers and capital distribution. To address the resulting global shortage of AI safety experts, Webb is launching the stealth organization Quantum Leap Education to bypass academic bottlenecks and rapidly train researchers in critical emerging technologies.