Hélène Landemore: Can AI Bring Deliberation to the Masses? | 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

eventSeminar

Hélène Landemore: Can AI Bring Deliberation to the Masses?

Status
Past
Date
Wednesday, October 19, 2022 10:00 AM - 11:00 AM PST/PDT
Location
Hybrid 
Share
Link copied to clipboard!
Event Contact
Madeleine Wright
mwright7@stanford.edu

Related Events

Kristina McElheran | The Rise of Industrial AI in America: Microfoundations of the Productivity J-curve(s)
May 11, 202612:00 PM - 1:00 PM
May
11
2026

We examine the prevalence and productivity dynamics of artificial intelligence (AI) in American manufacturing. Working with the Census Bureau to collect detailed large-scale data for 2017 and 2021, we focus on AI-related technologies with industrial applications.

Event

Kristina McElheran | The Rise of Industrial AI in America: Microfoundations of the Productivity J-curve(s)

May 11, 202612:00 PM - 1:00 PM

We examine the prevalence and productivity dynamics of artificial intelligence (AI) in American manufacturing. Working with the Census Bureau to collect detailed large-scale data for 2017 and 2021, we focus on AI-related technologies with industrial applications.

Wolfgang Lehrach | Code World Models for General Game Playing
SeminarMay 13, 202612:00 PM - 1:15 PM
May
13
2026

While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.

Seminar

Wolfgang Lehrach | Code World Models for General Game Playing

May 13, 202612:00 PM - 1:15 PM

While Large Language Models (LLMs) show promise in many domains, relying on them for direct policy generation in games often results in illegal moves and poor strategic play.

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.

HAI Weekly Seminar

Can AI Bring Deliberation to the Masses?

One unsolved problem in democratic theory is how we can reconcile the twin goals of quality deliberation and mass participation. Both are arguably conditions for the full legitimacy of a democratic system. Quality deliberation, as a process through which laws and policies are generated, in theory promises good governance (output-legitimacy) as well as, at the very least, good reasons for the laws and policies put forward. Mass participation, by contrast, is a condition for the democratic input-legitimacy of the system, namely its capacity to take into account people’s needs and preferences. Unfortunately, thus far, it has proven impossible to reconcile those two goals as the quality of deliberation diminishes past a relatively low threshold of participants (a few hundreds, perhaps a few thousand people) and mass participation, on the other hand, is not conducive to the thoughtful, informed exchanges smaller numbers afford. In this presentation, Hélène Landemore explores the ways in which Artificial Intelligence may help bridge that gap, at least up to a point.

Speakers

Helene LandemoreHélène Landemore

Professor of Political Science, Yale University

No tweets available.