HAI Weekly Seminar with Mitchell Stevens | Stanford HAI
Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
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
  • AI Glossary
  • 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

HAI Weekly Seminar with Mitchell Stevens

Status
Past
Date
Wednesday, April 21, 2021 10:00 AM - 11:00 AM PST/PDT
Overview
Watch Event Recording

Massive: How MOOCs Changed the Landscape of Education Research

Overview
Watch Event Recording
Share
Link copied to clipboard!
Event Contact
Celia Clark
celia.clark@stanford.edu

Related Events

Arvind Narayanan | Adapting to the Transformation of Knowledge Work
May 18, 202612:00 PM - 1:00 PM
May
18
2026

The possibility that AI will automate most cognitive labor is worth taking seriously. How should we adapt to this transformation? I start from the perspective, articulated in the essay “AI as normal technology”, that the true bottlenecks lie downstream of capabilities and that AI’s impacts will unfold gradually over decades. If this is true, there are major gaps in our current evidence infrastructure, because it over-emphasizes the capability layer.

Event

Arvind Narayanan | Adapting to the Transformation of Knowledge Work

May 18, 202612:00 PM - 1:00 PM

The possibility that AI will automate most cognitive labor is worth taking seriously. How should we adapt to this transformation? I start from the perspective, articulated in the essay “AI as normal technology”, that the true bottlenecks lie downstream of capabilities and that AI’s impacts will unfold gradually over decades. If this is true, there are major gaps in our current evidence infrastructure, because it over-emphasizes the capability layer.

Inside the 2026 AI Index Report | Stanford HAI
SeminarMay 20, 202612:00 PM - 1:15 PM
May
20
2026

The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.

Seminar

Inside the 2026 AI Index Report | Stanford HAI

May 20, 202612:00 PM - 1:15 PM

The AI Index, currently in its ninth year, tracks, collates, distills, and visualizes data relating to artificial intelligence.

Eyck Freymann | AI and Strategic Stability: A Framework for U.S.–China Technology Competition
SeminarMay 27, 202612:00 PM - 1:15 PM
May
27
2026

Strategic stability exists when neither side thinks it can improve its strategic outcome by striking first.

Seminar

Eyck Freymann | AI and Strategic Stability: A Framework for U.S.–China Technology Competition

May 27, 202612:00 PM - 1:15 PM

Strategic stability exists when neither side thinks it can improve its strategic outcome by striking first.

The embrace of massively open online courses (MOOCs) by Harvard, MIT and Stanford from 2012-2014 created buzz and anxiety among educators worldwide. While many were quick to thereafter declare the failure of MOOCs as instructional technologies, their legacy continues to transform the landscape of educational research. MOOCs demonstrated that minute instructional interactions could be observed and experimentally instrumented at scale; lured substantial new talent to educational inquiry from the burgeoning fields of data science and machine learning; dramatically expanded what counts as an instructional environment; and abetted the flow of private capital into a burgeoning sector now called “learning.” In this talk I synthesize recent scholarship to frame the promise and risks attendant to pursuit of learning research in digitally mediated environments. 

Mitchell Stevens
Professor of Education and, by courtesy, of Sociology