Weekly Top 5 Papers – January 22, 2018

1. Undocumented Immigrants, U.S. Citizens, and Convicted Criminals in Arizona by John R. Lott (Crime Prevention Research Center)

2. The Games They Will Play: Tax Games, Roadblocks, and Glitches Under the New Legislation by Reuven S. Avi-Yonah (University of Michigan Law School), Lily L. Batchelder (New York University School of Law), J. Clifton Fleming Jr. (Brigham Young University – J. Reuben Clark Law School), David Gamage (Indiana University Maurer School of Law), Ari D. Glogower (Ohio State University (OSU) – Michael E. Moritz College of Law), Daniel Jacob Hemel (University of Chicago – Law School), David Kamin (New York University School of Law), Mitchell Kane (New York University (NYU)), Rebecca M. Kysar (Brooklyn Law School; Fordham University School of Law), David S. Miller (Proskauer Rose LLP), Darien Shanske (University of California, Davis – School of Law), Daniel Shaviro (New York University School of Law) and Manoj Viswanathan (University of California Hastings College of the Law)

3. The Games They Will Play: An Update on the Conference Committee Tax Bill by Reuven S. Avi-Yonah (University of Michigan Law School), Lily L. Batchelder (New York University School of Law), J. Clifton Fleming Jr. (Brigham Young University – J. Reuben Clark Law School), David Gamage (Indiana University Maurer School of Law), Ari D. Glogower (Ohio State University (OSU) – Michael E. Moritz College of Law), Daniel Jacob Hemel (University of Chicago – Law School), David Kamin (New York University School of Law), Mitchell Kane (New York University (NYU)), Rebecca M. Kysar (Brooklyn Law School; Fordham University School of Law), David S. Miller (Proskauer Rose LLP), Darien Shanske (University of California, Davis – School of Law), Daniel Shaviro (New York University School of Law) and Manoj Viswanathan (University of California Hastings College of the Law)

4. Blockchain Technology: Principles and Applications by Marc Pilkington (Université Bourgogne Franche Comté)

5. Should We Treat Data as Labor? Moving Beyond ‘Free’ by Imanol Arrieta Ibarra (Stanford University) and Leonard Goff (Columbia University) and Diego Jiménez Hernández (Stanford University) and Jaron Lanier (Microsoft Corporation) and E. Glen Weyl (Microsoft Research)

With anxieties about Artificial Intelligence (AI) displacing a significant fraction of existing jobs and more broadly about the direction of the digital economy, this paper brings a fresh perspective to the issue —that of Jaron’s 2013 book Who Owns the Future?— into the language of academic economics. The paper also draws on ideas from Glen’s forthcoming book Radical Markets, as well as forthcoming empirical work on online labor markets and conversations with many colleagues at Microsoft Research. Like many others, we want to be proactive about thinking about where the economy is headed in the digital age. Is paying users for their data something we should do as a society? We argue in the affirmative, suggesting large gain both to data creators and to broader economic efficiency by both giving users a sense of digital dignity, and companies a source of higher quality data.

We expose three ideas in the paper: First, that data is increasingly being procured by a few tech companies (which Jaron calls “siren servers”) as part of an inefficient barter economy where consumers give away their data in exchange for free services. These data are then used for targeted advertising or to train machine learning systems, which are just clever ways of aggregating human effort for algorithms to learn a certain task. So, while humans are still central in the production of AI services, we’re being objectified as capital by the firms, rather than respected as labor providers.    We argue that this “data as capital” perspective, rather than “data as labor”, is likely to exacerbate inequality as well as limit the productivity gains from the AI revolution. Second, that we arrived at the current trajectory due to some historical baggage, but also because of the creation of natural monopsonies (siren servers) in which only a few companies are the sole consumers of data. Finally, we discuss ways that could move society towards a “data as labor” world, including increased competition, the role of regulation, and even some form of collective bargaining with siren servers. – Glen Weyl

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