Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
Adam Becker & Jon Evans | Book Talk: “More Everything Forever” and “Exadelic” | Stanford HAI
Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Fellowship Programs
    • Grants
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Navigate
  • About
  • Events
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

Your browser does not support the video tag.
eventSeminar

Adam Becker & Jon Evans | Book Talk: “More Everything Forever” and “Exadelic”

Status
Past
Date
Wednesday, January 21, 2026 12:00 PM - 1:15 PM PST/PDT
Location
353 Jane Stanford Way, Stanford, CA, 94305 | Room 119
Topics
Arts, Humanities
Industry, Innovation
Overview
Watch Event Recording

Join HAI Policy Fellow Riana Pfefferkorn for a conversation about the potential future(s) of AI and humanity with Adam Becker, author of More Everything Forever, and Jon Evans, author of Exadelic and the Gradient Ascendant newsletter.

Who are the individuals and communities predicting AI doom, AI boom, or AI as normal technology? What motivates them, and what should we make of their predictions? Amidst competing narratives of AI utopia and dystopia, what lessons can we learn from speculative fiction? How can the rest of us take action to ensure a human-centered future that serves all of us and our planet?

Speakers
Adam Becker
Journalist, Author, and Astrophysicist
Jon Evans
Author and Engineer
Moderator
Riana Pfefferkorn
Riana Pfefferkorn
Policy Fellow, Stanford HAI
Overview
Watch Event Recording
Share
Link copied to clipboard!
Event Contact
Stanford HAI
stanford-hai@stanford.edu
More from HAI and SDS seminars
  • Hari Subramonyam | Learning by Creating: A Human-Centered Vision for AI in Education
    SeminarMar 11, 202612:00 PM - 1:15 PM
    March
    11
    2026

Related Events

Zoë Hitzig | How People Use ChatGPT
Mar 09, 202612:00 PM - 1:00 PM
March
09
2026

Despite the rapid adoption of LLM chatbots, little is known about how they are used. We approach this question theoretically and empirically, modeling a user who chooses whether to complete a task herself, ask the chatbot for information that reduces decision noise, or delegate execution to the chatbot...

Event

Zoë Hitzig | How People Use ChatGPT

Mar 09, 202612:00 PM - 1:00 PM

Despite the rapid adoption of LLM chatbots, little is known about how they are used. We approach this question theoretically and empirically, modeling a user who chooses whether to complete a task herself, ask the chatbot for information that reduces decision noise, or delegate execution to the chatbot...

Joel Becker | Reconciling Impressive AI Benchmark Performance with Limited Developer Productivity Impacts
Mar 16, 202612:00 PM - 1:00 PM
March
16
2026

AI coding agents now complete multi-hour coding benchmarks with roughly 50% reliability, yet a randomized trial found experienced open-source developers took about 19% longer when allowed frontier AI tools than when tools were disallowed...

Event

Joel Becker | Reconciling Impressive AI Benchmark Performance with Limited Developer Productivity Impacts

Mar 16, 202612:00 PM - 1:00 PM

AI coding agents now complete multi-hour coding benchmarks with roughly 50% reliability, yet a randomized trial found experienced open-source developers took about 19% longer when allowed frontier AI tools than when tools were disallowed...