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
HAI Weekly Seminar with Lisa Simon | Stanford HAI

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

Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us
Your browser does not support the video tag.
eventSeminar

HAI Weekly Seminar with Lisa Simon

Status
Past
Date
Wednesday, December 09, 2020 10:00 AM - 11:00 AM PST/PDT
Topics
Workforce, Labor

The Future of Work and How the Workforce Adapts to Change

Share
Link copied to clipboard!

Related Events

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS
WorkshopJul 15, 20262:00 PM - 3:30 PM
July
15
2026

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

Event

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS

Jul 15, 20262:00 PM - 3:30 PM

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

Empirical Methods in the Age of AI Conference
ConferenceOct 02, 2026
October
02
2026

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

Event

Empirical Methods in the Age of AI Conference

Oct 02, 2026

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

The labor market is changing ever more rapidly, and with that, the pressure to adapt and evolve has increased on everyone, One of the main drivers of change is technological progress, with technologies such as robots, software or AI fundamentally changing how work gets done and by whom. Automation both replaces certain tasks that humans used to do, and more importantly changes the required skills in occupations that are adapting new technologies. This presentation will draw on my research that sheds light on how individual adapt to change on the labor market. I explore how individuals transition between different career pathways and how they react, when faced with negative shocks. Knowing who can adapt to change and who may need help, provides important policy implications for the future of work. The research presented uses data spanning Europe and the US as well as state-of-the art empirical methods, including machine learning.

Speaker
Lisa Simon
HAI-GSB Postdoctoral Fellow

Watch Event Recording