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Stanford University (link is external)
One Hundred Year Study on Artificial Intelligence (AI100)
One Hundred Year Study on Artificial Intelligence (AI100)
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Menu
 * Search this site Submit Search
 * Home
 * About
   * History
     * IJCAI 2015
   * People
     * Past AI100 Officers
   * Framing
 * 2021 Report
   * Preface
     * Participants
     * Acknowledgements
   * Introduction
   * Standing Questions and Responses
     * SQ1. What are some examples of pictures that reflect important progress
       in AI and its influences?
     * SQ2. What are the most important advances in AI?
       * Underlying Technologies
       * Language Processing
       * Computer Vision and Image Processing
       * Games
       * Robotics
       * Mobility
       * Health
       * Finance
       * Recommender Systems
     * SQ3. What are the most inspiring open grand challenge problems?
       * Turing Test
       * RoboCup
       * International Math Olympiad
       * The AI Scientist
       * Broader Challenges
     * SQ4. How much have we progressed in understanding the key mysteries of
       human intelligence?
       * Collective Intelligence
       * Cognitive Neuroscience
       * Computational Modeling
       * The State of the Art
     * SQ5. What are the prospects for more general artificial intelligence?
       * Self-Supervised Learning With the Transformer Architecture
       * Making Deep Reinforcement Learning More General
       * Making Deep Reinforcement Learning More General
       * Common Sense
     * SQ6. How has public sentiment towards AI evolved, and how should we
       inform/educate the public?
       * Primary Drivers of Public Understanding and Sentiment
       * Improving and Widening Public Understanding of AI: Where Do We Go From
         Here?
     * SQ7. How should governments act to ensure AI is developed and used
       responsibly?
       * Law, Policy, and Regulation
       * AI Research & Development as a Policy Priority
       * Cooperation and Coordination on International Policy
       * Case Study: Lethal Autonomous Weapons
       * From Principles to Practice
       * Dynamic Regulation, Experimentation, and Testing
     * SQ8. What should the roles of academia and industry be, respectively, in
       the development and deployment of AI technologies and the study of the
       impacts of AI?
       * Research and Innovation
       * Research into Societal and Ethical Issues
       * Development and Deployment
       * Education and Training
       * Societal Impact: Monitoring and Oversight
     * SQ9. What are the most promising opportunities for AI?
       * AI for Augmentation
       * AI Agents on Their Own
     * SQ10. What are the most pressing dangers of AI?
       * Techno-Solutionism
       * Dangers of Adopting a Statistical Perspective on Justice
       * Disinformation and Threat to Democracy
       * Discrimination and Risk in the Medical Setting
     * SQ11. How has AI impacted socioeconomic relationships?
       * The Story So Far
       * AI and Inequality
       * Localized Impact
       * How the Pie Is Sliced
       * Market Power
       * The Future
     * SQ12. Does it appear “building in how we think” works as an engineering
       strategy in the long run?
   * Workshop Questions and Responses
     * WQ1. How are AI-driven predictions made in high-stakes public contexts,
       and what social, organizational, and practical considerations must
       policymakers consider in their implementation and governance?
     * WQ2. What are the most pressing challenges and significant opportunities
       in the use of artificial intelligence to provide physical and emotional
       care to people in need?
   * Conclusions
   * Annotations on the 2016 Report
     * Preface (Annotated)
     * Executive Summary (Annotated)
     * Overview (Annotated)
       * What’s Next for AI Research? (Annotated)
       * AI Policy, Now and in the Future (Annotated)
     * Section I: What is Artificial Intelligence? (Annotated)
       * Defining AI (Annotated)
         * The Human Measure (Annotated)
         * An Operational Definition (Annotated)
       * AI Research Trends (Annotated)
         * Overall Trends and the Future of AI Research (Annotated)
     * Section II: AI by Domain (Annotated)
       * Transportation (Annotated)
         * Smarter Cars (Annotated)
         * Self-driving Vehicles (Annotated)
         * Transportation Planning (Annotated)
         * On-demand Transportation (Annotated)
         * Interacting with People (Annotated)
       * Home/Service Robots (Annotated)
         * Vacuum Cleaners (Annotated)
         * Home Robots 2030 (Annotated)
       * Healthcare (Annotated)
         * The Clinical Setting (Annotated)
         * Healthcare Analytics (Annotated)
         * Healthcare Robotics (Annotated)
         * Mobile Health (Annotated)
         * Elder Care (Annotated)
       * Education (Annotated)
         * Teaching Robots (Annotated)
         * Intelligent Tutoring Systems and Online Learning (Annotated)
         * Learning Analytics (Annotated)
         * Challenges and Opportunities (Annotated)
         * Broader Societal Consequences (Annotated)
       * Low-resource Communities (Annotated)
       * Public Safety and Security (Annotated)
       * Employment and Workplace (Annotated)
       * Entertainment (Annotated)
         * Imagining the Future (Annotated)
     * Section III: Prospects and Recommendations for Public Policy (Annotated)
       * AI Policy, Now and in the Future (Annotated)
         * Policy and Legal Considerations (Annotated)
         * Guidelines for the Future (Annotated)
     * Appendix I: A Short History of AI (Annotated)
 * 2016 Report
   * Preface
     * Participants
     * Acknowledgements
   * Executive Summary
   * Overview
     * What’s Next for AI Research?
     * AI Policy, Now and in the Future
   * Section I: What is Artificial Intelligence?
     * Defining AI
       * The Human Measure
       * An Operational Definition
     * AI Research Trends
       * Overall Trends and the Future of AI Research
   * Section II: AI by Domain
     * Transportation
       * Smarter Cars
       * Self-driving Vehicles
       * Transportation Planning
       * On-demand Transportation
       * Interacting with People
     * Home/Service Robots
       * Vacuum Cleaners
       * Home Robots 2030
     * Healthcare
       * The Clinical Setting
       * Healthcare Analytics
       * Healthcare Robotics
       * Mobile Health
       * Elder Care
     * Education
       * Teaching Robots
       * Intelligent Tutoring Systems and Online Learning
       * Learning Analytics
       * Challenges and Opportunities
       * Broader Societal Consequences
     * Low-resource Communities
     * Public Safety and Security
     * Employment and Workplace
     * Entertainment
       * Imagining the Future
   * Section III: Prospects and Recommendations for Public Policy
     * AI Policy, Now and in the Future
       * Policy and Legal Considerations
       * Guidelines for the Future
   * Appendix I: A Short History of AI
   * Annotations on the 2016 Report
 * AI100 Competition
 * AI Index
 * Related Publications & Seminars
 * Press Coverage


100 YEAR STUDY ON AI RELEASED ITS 2021 REPORT.

 

Read the 2021 Report 

Download the 2021 Report


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ABOUT

The One Hundred Year Study of Artificial Intelligence (AI100) is a longitudinal
study to study and anticipate how the effects of artificial intelligence will
ripple through every aspect of how people work, live and play. It is
administered out of Stanford University and managed by a Standing Committee of
AI experts from institutions around the world, chaired by Vincent Conitzer
at Carnegie Mellon University. The 2021 AI100 Report was written by a panel of
17 study authors, each of whom is deeply rooted in AI research, chaired by
Michael Littman of Brown University.

More about us


REFLECTIONS AND FRAMING

One Hundred Year Study of Artificial Intelligence (AI) has its roots in a
one-year study on Long-term AI Futures that we commissioned during my term of
service as president of the Association for the Advancement of Artificial
Intelligence (AAAI) in 2008-2009.

More information


COMMITTEES AND PANELS

One Hundred Year Study of Artificial Intelligence (AI) has its roots in a
one-year study on Long-term AI Futures that we commissioned during my term of
service as president of the Association for the Advancement of Artificial
Intelligence (AAAI) in 2008-2009.

Learn more about contributors

One Hundred Year Study on Artificial Intelligence (AI100)
One Hundred Year Study on Artificial Intelligence (AI100)
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ADDRESS

Stanford University
Faculty Director - Russ Altman
Stanford, CA 94305
United States

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RELATED LINKS

 * AAAI Asilomar meeting (2009) (link is external)
 * AI Index (link is external)
 * Stanford Human-Centered Artificial Intelligence (link is external)


EVENTS

 * IJCAI 2015 session (link is external)


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