Ep 54: Princeton Researcher Arvind Narayanan on the Limitations of Agent Evals, AI’s Societal Impact & Important Lessons from History

Unsupervised Learning

Arvind Narayanan is one of the leading voices in AI when it comes to cutting through the hype. As a Princeton professor and co-author of AI Snake Oil, he’s one of the most thoughtful voices cautioning against both unfounded fears and overblown promises in AI. In this episode, Arvind dissects the future of AI in education, its parallels to past tech revolutions, and how our jobs are already shifting toward managing these powerful tools. Some of our favorite take-aways:

[0:00] Intro
[0:46] Reasoning Models and Their Uneven Progress
[2:46] Challenges in AI Benchmarks and Real-World Applications
[5:03] Inference Scaling and Verifier Imperfections
[7:33] Agentic AI: Tools vs. Autonomous Actions
[12:07] Future of AI in Everyday Life
[15:34] Evaluating AI Agents and Collaboration
[24:49] Regulatory and Policy Implications of AI
[27:49] Analyzing Generative AI Adoption Rates
[29:17] Educational Policies and Generative AI
[30:09] Flaws in Predictive AI Models
[31:31] Regulation and Safety in AI
[33:47] Academia's Role in AI Development
[36:13] AI in Scientific Research
[38:22] AI and Human Minds
[46:04] Economic Impacts of AI
[49:42] Quickfire

With your co-hosts:

@jacobeffron

- Partner at Redpoint, Former PM Flatiron Health

@patrickachase

- Partner at Redpoint, Former ML Engineer LinkedIn

@ericabrescia

- Former COO Github, Founder Bitnami (acq’d by VMWare)

@jordan_segall

- Partner at Redpoint