The Challenge
The advent of Transformative AI1, or TAI, would yield economic change on the scale of the Industrial Revolution but has the potential to occur radically faster. TAI could boost productivity levels and accelerate scientific progress, putting us in a realm beyond traditional economic modeling. At the same time, TAI risks disruption in labor markets and changes in the concentration of wealth and power. With foresight, we can adapt our institutions and create a future of widely shared prosperity.
The gap between rapidly growing technological capabilities and slowly improving economic understanding, skills, institutions, and policies is the crux of the coming decade’s societal challenges. Economics must be transformed in the face of such technological change.
There is an urgent need to understand the economic implications of Transformative AI: If machines are created that can outperform humans on a significant share of tasks, many of our existing institutions, norms, and systems will need to be reinvented. This raises questions regarding distribution, concentration, inequality, information flows, geopolitics and trade, AI safety and alignment, well-being, and a host of other important topics.
The Digital Economy Lab is actively engaged in developing a robust economic research agenda to address the potential challenges associated with TAI. The papers linked below represent a subset of ideas and thinkers we believe are shaping this conversation (email sdel-admin@stanford.edu if you have a suggested addition).
1 For our purposes, a working definition of TAI is provided by Karnofsky, 2016. “Transformative AI refers to potential future AI that precipitates a transition comparable to (or more significant than) the agricultural or industrial revolution. The concept of “transformative AI” has some overlap with concepts put forth by others, such as ‘superintelligence’ and ‘artificial general intelligence.’ However, ‘transformative AI’ is intended to be a more inclusive term, leaving open the possibility of AI systems that are ‘transformative’ despite lacking many abilities humans have.”
Primary reading
AI Could Actually Help Rebuild The Middle Class
David Autor, Noema, February 2024
noemamag.com
Artificial General Intelligence Is Already Here
Blaise Agüera y Arcas, and Peter Norvig, Noema, October 2023
noemamag.com
The Turing Trap: The Promise & Peril of Human-like Artificial Intelligence
Erik Brynjolfsson
digitaleconomy.stanford.edu
The Turing Transformation: Artificial Intelligence, Intelligence Augmentation, and Skill Premiums
Ajay Agrawal, Joshua Gans and Avi Goldfarb
brookings.edu
The AI Dilemma: Growth vs. Existential Risk
Chad Jones (2023)
NBER
Economic Possibilities for Our Grandchildren
John Maynard Keynes
PDF
Economic Policy Challenges for the Age of AI
Anton Korinek
Situational Awareness
Leopold Aschenbrenner
Transformative AI, existential risk, and asset pricing
Trevor Chow, Basil Halperin, and J. Zachary Mazlish
Supplementary reading
How Learning About Harms Impacts the Optimal Rate of Artificial Intelligence Adoption
Joshua S. Gans
NBER
Artificial Intelligence, Innovation, and Economic Growth
Agrawal, McHale, and Oettl, February 2024
Regulating Transformative Technologies
Acemoglu and Lensman (2023)
Three Risks to the Future of Competition in AI
Avi Goldfarb
Existential Risk and Growth
Aschenbrenner and Trammell (2024)
Inefficient Automation
Beraja and Zorzi (2022)
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models
Eloundou et al. (2023)
Natural Selection Favors AIs over Humans
Hendrycks (2023)
Optimal Gradualism
Lehr and Restrepo (2023)
PDF
Scenario Planning for an A(G)I Future
Korinek, IMF Finance & Development Magazine, Dec. 2023
Preparing for the (Non-Existent?) Future of Work
Korinek and Juelfs, Oxford Handbook of AI Governance, 2024
Economic Growth under Transformative AI
Trammell and Korinek, Oct. 2023
PDF
Aligned with Whom? Direct and Social Goals for AI Systems
Korinek and Balwit, Oxford Handbook of AI Governance, 2024
Simulating the Global Effect of Transformative AI: Growth, Welfare, Economic Power, and Policy Responses
Seth Gordon Benzell, Victor Yifan Ye. March 2024
Artificial Intelligence Technologies and Aggregate Growth Prospects
Timothy Bresnahan
What innovation paths for AI to become a GPT?
Timothy Bresnahan
Machines of Loving Grace
Dario Amodei