front cover of Economic Analysis of the Digital Economy
Economic Analysis of the Digital Economy
Edited by Avi Goldfarb, Shane M. Greenstein, and Catherine E. Tucker
University of Chicago Press, 2015
As the cost of storing, sharing, and analyzing data has decreased, economic activity has become increasingly digital. But while the effects of digital technology and improved digital communication have been explored in a variety of contexts, the impact on economic activity—from consumer and entrepreneurial behavior to the ways in which governments determine policy—is less well understood.
           
Economic Analysis of the Digital Economy explores the economic impact of digitization, with each chapter identifying a promising new area of research. The Internet is one of the key drivers of growth in digital communication, and the first set of chapters discusses basic supply-and-demand factors related to access. Later chapters discuss new opportunities and challenges created by digital technology and describe some of the most pressing policy issues. As digital technologies continue to gain in momentum and importance, it has become clear that digitization has features that do not fit well into traditional economic models. This suggests a need for a better understanding of the impact of digital technology on economic activity, and Economic Analysis of the Digital Economy brings together leading scholars to explore this emerging area of research.
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front cover of The Economics of Artificial Intelligence
The Economics of Artificial Intelligence
An Agenda
Edited by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
University of Chicago Press, 2019
Advances in artificial intelligence (AI) highlight the potential of this technology to affect productivity, growth, inequality, market power, innovation, and employment. This volume seeks to set the agenda for economic research on the impact of AI. It covers four broad themes: AI as a general purpose technology; the relationships between AI, growth, jobs, and inequality; regulatory responses to changes brought on by AI; and the effects of AI on the way economic research is conducted. It explores the economic influence of machine learning, the branch of computational statistics that has driven much of the recent excitement around AI, as well as the economic impact of robotics and automation and the potential economic consequences of a still-hypothetical artificial general intelligence. The volume provides frameworks for understanding the economic impact of AI and identifies a number of open research questions.

Contributors:
Daron Acemoglu, Massachusetts Institute of Technology
Philippe Aghion, Collège de France
Ajay Agrawal, University of Toronto
Susan Athey, Stanford University
James Bessen, Boston University School of Law
Erik Brynjolfsson, MIT Sloan School of Management
Colin F. Camerer, California Institute of Technology
Judith Chevalier, Yale School of Management
Iain M. Cockburn, Boston University
Tyler Cowen, George Mason University
Jason Furman, Harvard Kennedy School
Patrick Francois, University of British Columbia 
Alberto Galasso, University of Toronto
Joshua Gans, University of Toronto
Avi Goldfarb, University of Toronto
Austan Goolsbee, University of Chicago Booth School of Business
Rebecca Henderson, Harvard Business School
Ginger Zhe Jin, University of Maryland
Benjamin F. Jones, Northwestern University
Charles I. Jones, Stanford University
Daniel Kahneman, Princeton University
Anton Korinek, Johns Hopkins University
Mara Lederman, University of Toronto
Hong Luo, Harvard Business School
John McHale, National University of Ireland
Paul R. Milgrom, Stanford University
Matthew Mitchell, University of Toronto
Alexander Oettl, Georgia Institute of Technology
Andrea Prat, Columbia Business School
Manav Raj, New York University
Pascual Restrepo, Boston University
Daniel Rock, MIT Sloan School of Management
Jeffrey D. Sachs, Columbia University
Robert Seamans, New York University
Scott Stern, MIT Sloan School of Management
Betsey Stevenson, University of Michigan
Joseph E. Stiglitz. Columbia University
Chad Syverson, University of Chicago Booth School of Business
Matt Taddy, University of Chicago Booth School of Business
Steven Tadelis, University of California, Berkeley
Manuel Trajtenberg, Tel Aviv University
Daniel Trefler, University of Toronto
Catherine Tucker, MIT Sloan School of Management
Hal Varian, University of California, Berkeley
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front cover of The Economics of Artificial Intelligence
The Economics of Artificial Intelligence
Health Care Challenges
Edited by Ajay Agrawal, Joshua Gans, Avi Goldfarb, and Catherine E. Tucker
University of Chicago Press, 2024

A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system.

In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI.

The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.

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front cover of The Economics of Privacy
The Economics of Privacy
Edited by Avi Goldfarb and Catherine E. Tucker
University of Chicago Press, 2024

A foundational new collection examining the mechanics of privacy in the digital age.

The falling costs of collecting, storing, and processing data have allowed firms and governments to improve their products and services, but have also created databases with detailed individual-level data that raise privacy concerns. This volume summarizes the research on the economics of privacy and identifies open questions on the value of privacy, the roles of property rights and markets for privacy and data, the relationship between privacy and inequality, and the political economy of privacy regulation.

Several themes emerge across the chapters. One is that it may not be possible to solve privacy concerns by creating a market for the right to privacy, even if property rights are well-defined and transaction costs are low. Another is that it is difficult to measure and value the benefits of privacy, particularly when individuals have an intrinsic preference for privacy. Most previous attempts at valuation have focused only on quantifiable economic outcomes, such as innovation. Finally, defining privacy through an economic lens is challenging. The broader academic and legal literature includes many distinct definitions of privacy, and different definitions may be appropriate in different contexts. The chapters explore a variety of frameworks for examining these questions and provide a range of new perspectives on the role of economics research in understanding the benefits and costs of privacy and of data flows. As the digital economy continues to expand the scope of economic theory and research, The Economics of Privacy provides the most comprehensive survey to date of this field and its next steps.

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