The Microeconomics of Artificial Intelligence (Open Access)
Recorded: Sept. 8, 2026, 11:09 p.m.
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The Microeconomics of Artificial Intelligence | Books Gateway | MIT Press Skip to Main Content Open Menu Close Books Open Menu Books Home Browse Books Journals Open Menu Journals Home Browse Journals CogNet About MIT Press Direct Customer Support Librarians Search Dropdown Menu header search Search input auto suggest filter your search All ContentAll Books Search Advanced Search User Tools Dropdown Register Toggle MenuMenu Browse Books The Microeconomics of Artificial Intelligence By Joshua Gans Joshua Gans Joshua Gans is Professor of Strategic Management and holds the Jeffrey S. Skoll Chair of Technical Innovation and Entrepreneurship at the University of Toronto’s Rotman School of Management. He is the author of The Disruption Dilemma (MIT Press), among other titles, and coauthor of Prediction Machines and Innovation + Equality (MIT Press). Search for other works by this author on: This Site Google Scholar The MIT Press DOI: https://doi.org/10.7551/mitpress/15248.001.0001 ISBN electronic: Publication date: A comprehensive treatment of the microeconomics associated with the adoption and use of artificial intelligence.It is well recognized that recent advances in AI are exclusively advances in statistical techniques for prediction. While this may facilitate automation, this result is secondary to AI’s impact on decision-making. From an economics perspective, predictions have their first-order impacts on the efficiency of decision-making.In The Microeconomics of Artificial Intelligence, Joshua Gans examines AI as prediction that enhances and perhaps enables decision-making, focusing on the impacts that arise within firms or industries rather than broad economy-wide impacts on employment and productivity. He analyzes what the supply and production characteristics of AI are and what the drivers of the demand for AI prediction are. Putting these together, he explores how supply and demand conditions lead to a price for predictions and how this price is shaped by market structure. Finally, from a microeconomics perspective, he explores the key policy trade-offs for antitrust, privacy, and other regulations. Open the Book PDF for in another window Share Icon Share X Bluesky Tools Icon Tools Permissions Cite Icon Cite Reader The Microeconomics of Artificial Intelligence Download citation file: Ris (Zotero) Table of Contents [ Front Matter ] Doi: https://doi.org/10.7551/mitpress/15248.003.0001 Open the PDF Link Preface Doi: https://doi.org/10.7551/mitpress/15248.003.0002 Open the PDF Link 1: The Economic Impact of AI Doi: https://doi.org/10.7551/mitpress/15248.003.0003 Open the PDF Link 2: Advances in Machine Learning Doi: https://doi.org/10.7551/mitpress/15248.003.0004 Open the PDF Link I: AI Demand 3: The Value of Prediction Doi: https://doi.org/10.7551/mitpress/15248.003.0006 Open the PDF Link 4: Substitutes for Prediction Doi: https://doi.org/10.7551/mitpress/15248.003.0007 Open the PDF Link 5: Complements to Prediction Doi: https://doi.org/10.7551/mitpress/15248.003.0008 Open the PDF Link 6: Automation Doi: https://doi.org/10.7551/mitpress/15248.003.0009 Open the PDF Link 7: System Effects Doi: https://doi.org/10.7551/mitpress/15248.003.0010 Open the PDF Link II: AI Supply 8: Generation of Input Data Doi: https://doi.org/10.7551/mitpress/15248.003.0012 Open the PDF Link 9: Generation of Training Data Doi: https://doi.org/10.7551/mitpress/15248.003.0013 Open the PDF Link III: AI Pricing 10: Pricing with Exogenous Judgment Doi: https://doi.org/10.7551/mitpress/15248.003.0015 Open the PDF Link 11: Pricing with Endogenous Judgment Doi: https://doi.org/10.7551/mitpress/15248.003.0016 Open the PDF Link 12: Pricing to a Competitive Market Doi: https://doi.org/10.7551/mitpress/15248.003.0017 Open the PDF Link 13: Pricing to a Monopoly Market Doi: https://doi.org/10.7551/mitpress/15248.003.0018 Open the PDF Link 14: Prediction for Negotiations Doi: https://doi.org/10.7551/mitpress/15248.003.0019 Open the PDF Link IV: AI Policy 15: Market Power Doi: https://doi.org/10.7551/mitpress/15248.003.0021 Open the PDF Link 16: Collusion Doi: https://doi.org/10.7551/mitpress/15248.003.0022 Open the PDF Link 17: Privacy Regulation Doi: https://doi.org/10.7551/mitpress/15248.003.0023 Open the PDF Link 18: Intellectual Property Rights Doi: https://doi.org/10.7551/mitpress/15248.003.0024 Open the PDF Link 19: Misinformation Doi: https://doi.org/10.7551/mitpress/15248.003.0025 Open the PDF Link 20: Bias and Discrimination Doi: https://doi.org/10.7551/mitpress/15248.003.0026 Open the PDF Link 21: Regulating Adoption Doi: https://doi.org/10.7551/mitpress/15248.003.0027 Open the PDF Link 22: Behavioral and Social Impacts Doi: https://doi.org/10.7551/mitpress/15248.003.0028 Open the PDF Link Notes Doi: https://doi.org/10.7551/mitpress/15248.003.0029 Open the PDF Link References Doi: https://doi.org/10.7551/mitpress/15248.003.0030 Open the PDF Link Index Doi: https://doi.org/10.7551/mitpress/15248.003.0031 Open the PDF Link Availability Key Open Access Free Available No Access Advertisement Copyright A product of The MIT Press Bluesky X YouTube MIT Press Direct About MIT Press Direct Information Accessibility at MIT MIT Press Direct VPAT MIT Press About the MIT Press Contact Us FAQ © 2026 The MIT Press Terms of Use Privacy Crossref Member COUNTER Member Close dialog Close dialog This Feature Is Available To Subscribers Only Close subscription notice Close access options Sharing Unavailable Update Cookie Preferences This site uses cookies. 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The Microeconomics of Artificial Intelligence by Joshua Gans provides a comprehensive examination of the microeconomic principles associated with the adoption and use of artificial intelligence, shifting the focus from broad economy-wide impacts on employment and productivity to the localized effects within firms and industries. Gans posits that recent advancements in AI are primarily statistical techniques for prediction, but the true economic significance lies in AI's capacity to enhance and enable decision-making. From an economic perspective, predictions exert a first-order impact on decision-making efficiency. The book analyzes the supply and production characteristics of AI and the drivers behind the demand for AI prediction, exploring how these forces interact within specific market structures. The analysis is structured around key areas concerning demand, supply, pricing, and policy. In the realm of demand, Gans investigates the value of prediction itself, examining the relationship between prediction, its substitutes, its complements, and its role in automation and system effects. This section sets the stage by defining the utility derived from predictive capabilities within an economic context. The supply side is addressed through the processes involved in generating the necessary input data and training data required for AI systems to function. The book then delves into the complex issue of pricing within the AI market, differentiating between pricing models based on exogenous judgment versus endogenous judgment. Gans explores how predictions are priced in competitive markets versus monopoly markets, and addresses specific applications such as the use of prediction in negotiations. This segment establishes the mechanisms by which economic value is assigned to predictive services depending on the market context. Finally, the work moves to the policy implications arising from these microeconomic structures. Gans explores critical trade-offs related to antitrust concerns, privacy regulations, intellectual property rights, and addressing societal issues such as misinformation, bias, and discrimination. The book systematically examines how market power and collusion affect AI development and deployment, alongside the necessary regulatory considerations for the adoption of these technologies. Ultimately, the work seeks to establish a microeconomic framework for understanding the structure, value, costs, and regulatory challenges inherent in the diffusion of artificial intelligence within specific economic environments. |