Open Letter and Principles for Ethical Research on the Gig Economy
To add your name to this letter, please email gigeconomyresearchersunited [at] gmail [dot] com with your name, title, and affiliation.
30 July 2020
We are a group of scholars from different disciplines who study the “gig economy” at institutions of higher education around the world. We believe that rigorous research must guide public conversation about labor issues in this sector and help to build a more just, sustainable economy. Accordingly, we commit ourselves to the adoption of a set of core principles for ethical research on the gig economy.
These principles are grounded in the understanding that academic research about gig companies, their workplaces, and their workforces is central to policy debates at municipal, state, national, and even international levels. For the past decade, gig companies have actively and aggressively lobbied governments to create a regulatory environment suitable to their business practices and interests. In the process, misleading studies created through and with corporate partnerships have had an undue influence on regulatory disputes. Often, when policymakers attempt to collect data to do their own research to inform policy decisions, the gig companies have restricted government access to even the most basic data on the operation of their services.
For these reasons, we are most recently disappointed in the white paper authored by Louis Hyman, Erica Groshen, Adam Seth Litwin, Martin Wells, Kwelina Thompson, and Kyrylo Chernyshov and published by Cornell University’s School of Industrial and Labor Relations (hereafter Uber-Lyft-Hyman study) estimating the earnings of Seattle ride-hail drivers. We highlight three ethical problems with this study to lay the framework for the research principles that follow.
First, the integrity of the Uber-Lyft-Hyman data and research is suspect, as it was funded by Uber and Lyft. The companies have repeatedly made the false legal claims that the de-identified data needed to determine wage trends is proprietary and protected competitive information. Accordingly, they refused to comply with the data requests of the independent economists hired by the City of Seattle. By accepting the data and the companies’ claims of ownership, Hyman et al. conducted a study that cannot be replicated. The acceptance of the company’s data and analytical parameters, especially when policymakers have commissioned a study on this very matter, normalizes the companies’ systematic withholding of basic information needed by regulators to govern.
Second, the paper obfuscates the actual working conditions of gig workers. The study excludes many of the costs borne by workers on the theory that most of the workforce does not work full time and so these costs are incidental. Costs borne by workers include those directly related to driving and to health of workers. This analytic framework ignores evidence that full-time drivers, many of them immigrants and people of color, conduct the majority of work for Uber and Lyft in the U.S. In addition, the study includes drivers’ tips in its wage calculation, an employer practice prohibited by the state of Washington because tips are undependable sources of income.
Third, the study makes controversial extrapolations about driver behaviors and labor standards. The authors determine that “hourly earnings” of Uber and Lyft drivers in Seattle “are not exceptional, but neither are they terrible.” This conclusion is made alongside their finding that “many drivers earn below the minimum wage.” For policy purposes, wage variation in which some drivers earn below the minimum wage is an undesirable — — even “terrible” — — outcome. Elsewhere, the study uses normative statements to buttress questionable analytical assumptions about how drivers should behave, as opposed to how they actually do: “[I]f drivers’ cars are more expensive than [a certain] price, they are spending more than they need to spend.” The study also asserts that “incorporating fixed costs are not how, we believe, casual drivers…should think about costs” (our emphasis). These statements burden drivers with responsibility rather than Uber, even as Uber and Lyft control driver pay rates.
In response to these ethical issues in the Uber-Lyft-Hyman study, we call for research on the gig economy that adheres to the following principles:
(1) Research should not be conducted when data is withheld, or the parameters of analysis is set, by corporate actors. In support of robust inquiry, public debate, and enlightened policy making, we advocate for data transparency that allows scholars and policymakers to analyze data independent of corporate influence. As problems of replication of research findings have surfaced across the social and natural sciences, it is imperative that studies of gig work claiming generalizability follow what are now basic procedures for research integrity. For the Uber-Lyft-Hyman, for example, the relevant policy would be the American Economic Association principles, which require submitting data and code to an open repository.
(2) Research should illuminate how risks — — especially financial and legal risks — — are allocated, accumulated, and navigated. When calculating income, research should account for all business expenses (including taxes and vehicle expenses) that workers must bear. Similarly, research about hourly wages should account for all time that workers spend laboring. While gig companies argue that labor time is only constituted when a worker is serving a customer (i.e., a ride-hail driver has a passenger in their car), research must consider the time spent waiting for an assignment and driving to an assignment.
(3) Researchers should be vigilant about how their research may be used to undermine collective efforts of workers to unionize or gain power in their workplaces. For example, the day after its release the Uber-Lyft-Hyman study was leveraged by the companies’ public relations campaigns in California to sway voter opinion on their proposed ballot initiative, which, if passed, would codify devastatingly low working conditions in this sector of work. California gig worker groups have been fighting the initiative.
As the Covid-19 pandemic rages across the world, hitting poor and BIPOC communities the hardest, the dire working conditions of gig workers demand attention and informed policy responses. Gig workers across the United States, for example, have fought to receive state unemployment insurance as employees rather than pandemic unemployment assistance as contractors, which provides hundreds less per month. As these workers await assistance, many have been forced to drive or deliver food to make ends meet, sometimes becoming ill and even dying without health insurance, workers’ compensation, or personal protective equipment.
Regulators all over the world have begun to address the unacceptable working conditions created by Uber and Lyft and similar companies in the gig economy. In the coming months and years, lawmakers will face important political and economic decisions to help foster secure, stable jobs for the future of workers. Amidst devastating economic, racial, and social inequalities, we commit, as academics, to using the above ethical principles in our own research on the gig economy so as to contribute to policies that reverse these destructive trends.
Antonio Aliosi, Assistant Professor of European and Comparative Labour Law, IE University
Moritz Altenried, Post-doctoral Researcher, Centre for Digital Cultures (CDC), Leuphana Universität Lüneburg
Mohammad Amir Anwar, Lecturer in African Studies and International Development, University of Edinburgh
Alice M. Brawley Newlin, Assistant Professor of Management, Gettysburg College
Enda Brophy, Associate Professor of Communication, Simon Fraser University
Damion Bunders, PhD Candidate, Utrecht University
Mehmet Cansoy, Assistant Professor of Sociology, Fairfield University,
Rodrigo Carelli, Professor of Labor Law, Universidade Federal do Rio de Janeiro
Yujie “Julie” Chen, Assistant Professor of Communication, University of Toronto
Miriam Cherry, Professor of Law, Saint Louis University
Rogério Christofoletti, Assistant Professor of Journalism, Universidade Federal de Santa Catarina, Brazil
Ruth Collier, Heller Professor of the Graduate School, University of California at Berkeley
Declan Cullen, Assistant Professor of Geography, George Washington University
José Eduardo de Resende Chaves Júnior, Visiting Professor of the Doctoral Program at the Faculty of Law of the Federal University of Minas Gerais, Brazil
Valerio De Stefano, Research Professor of Law, University of Leuven
Allessandro Delfanti, Associate Professor of Culture and New Media, University of Toronto
Elaine Dewhurst, Senior Lecturer, University of Manchester
Brian Dolber, Assistant Professor of Communication, California State University San Marcos
Veena Dubal, Professor of Law, University of California Hastings
Koen Frenken, Professor of Innovation Studies, Utrecht University
Barbara Gomes, Lecturer, Polytechnique Hauts-De-France University
Mark Graham, Professor of Internet Geography, University of Oxford
Seamus Bright Grayer, MA Student, Simon Fraser University
Karen Gregory, Lecturer in Digital Sociology, University of Edinburgh
Rafael Grohmann, Assistant Professor, Unisinos University
Erin Hatton, Associate Professor of Sociology, University at Buffalo
Heiner Heiland, Assistant Professor in Sociology, Technical University
Ursula Huws, Professor of Labour & Globalisation, University of Hertfordshire
Christian Lyhne Ibsen, Associate Professor, School of Human Resources and Labor Relations, Michigan State University
Lilly Irani, Associate Professor of Communication, University of California San Diego
Simon Joyce, Research Fellow, Leeds University Business School
Anne Keegan, Full Professor of Human Resource Management, University College Dublin
Tamara Kneese, Assistant Professor of Media Studies, University of San Francisco
Chenjerai Kumanyika, Assistant Professor of Journalism and Media Studies, Rutgers University
Laura Lam, PhD Student, University of Toronto
Morshed Mannan, PhD Candidate, Leiden University
Ana Flávia Marquez, PhD Student, School of Communications and Arts, University of São Paulo
Liz B. Marquis, PhD Candidate, School of Information, University of Michigan
Biju Mathew, Associate Professor of Information Systems, Rider University
Matthew P. McAllister, Professor, Pennsylvania State University
Ewan McGaughey, Senior Lecturer in Law, King’s College, London
Jeroen Meijerink, Assistant Professor of Human Resource Management, University of Twente, The Netherlands
Gayatri Nair, Assistant Professor, Sociology, Indraprashthra Institute of Information Technology, Delhi
Sanjukta Paul, Assistant Professor of Law, Wayne State University
Luca Perrig, PhD Candidate, Department of Sociology, University of Geneva
Rich Phan, PhD Candidate, School of Historical and Philosophical Studies (SHAPS), University of Melbourne
Julian Posada, PhD student, University of Toronto
Winifred Poster, Lecturer, Washington University in St. Louis
Alexandrea Ravenelle, Assistant Professor of Sociology, The University of North Carolina at Chapel Hill
Jude Ritchie, Lecturer in Human Resource Management, Royal Docks School of Business & Law
Hilary Robinson, Associate Professor of Law and Sociology, Northeastern University
Isabel Roque, Researcher, Center for Social Studies, University of Coimbra
Michelle Rodino-Colocino, Associate Professor of Media Studies, Pennsylvania State University
Daria Rothmayr, Richard L. and Antoinette S. Kirtland Professor of Law, University of Southern California
Juliet Schor, Professor of Sociology, Boston College
Aaron Shapiro, Assistant Professor of Technology Studies, The University of North Carolina at Chapel Hill
Cheryll Ruth Soriano, Professor, De La Salle University-Manila
Mark Stuart, Professor, University of Leeds
Kathy Thelen, Ford Professor of Political Science, Massachusetts Institute of Technology
Jill Toh, PhD Candidate, Institute for Information Law, University of Amsterdam
Julia Tommassetti, Assistant Professor of Law, City University of Hong Kong
Fábio Tozi, Assistant Professor of Geography, Federal University of Minas Gerais
Steven Vallas, Professor of Sociology, Northeastern University
Harry E. Vanden, Professor Emeritus of Political Science, University of South Florida
Niels Van Doorn, Assistant Professor of New Media and Digital Culture, University of Amsterdam
Matthieu Vicente, PhD student, University of Strasbourg
Shannon Walsh, Department of Theatre and Film, University of British Columbia
Katie Wells, Urban Studies Foundation Postdoctoral Research Fellow, Georgetown University
Meredith Whittaker, Research Professor, New York University
Alice Wickström, Researcher, Aalto University School of Business
Todd Wolfson, Associate Professor of Journalism and Media Studies, Rutgers University
Alex Wood, Lecturer in the Sociology of Work, University of Birmingham
Lorenzo Zamponi, Assistant Professor in Political and Social Sciences, Scuola Normale Superiore
 We use this colloquial term to refer to the on-demand labor market created through companies like Uber, Lyft, Instacart, Postmates, DoorDash, and Amazon Mechanical Turk. We recognize that the business model used by these companies to create “gig work” is not new or innovative but part of a half-century trend of corporations shifting risk and liability onto workers. Peck, J., & Theodore, N. (2012). Politicizing contingent work: Countering neoliberal labor market regulation… from the bottom up?. South Atlantic Quarterly, 111(4), 741–761.
 One study by the National Employment Law Project (2018) found that in 2016 the number of lobbyists for Uber and its peers outnumbered those for Amazon, Microsoft, and Walmart combined. In 2016 alone, Uber had 370 active lobbyists in 44 U.S. states. Smith, R., Borkholder, J., Montgomery, M., Chen, M. S. (2018). Uber State Interference: How TNCs Buy, Bully, and Bamboozle Their Way to Deregulation. Available at https://www.nelp.org/publication/uber-state-interference/.
 Such studies abound. For example, in 2016, Uber economist Jonathan Hall worked with the late Alan Krueger to produce a working paper based on survey data alleging that Uber drivers were content with the flexibility of the Uber model and their pay. Hall, J. V., & Krueger, A. B. (2018). An analysis of the labor market for Uber’s driver-partners in the United States. ILR Review, 71(3), 705–732. Before the paper’s final publication, Hall and Krueger’s findings were used in any number of regulatory contexts at the federal, state, and municipal levels to attest to the virtues of Uber’s business model. Yet, the study, which was fraught with methodological problems, painted an incomplete and grossly oversimplified picture of driver experiences. Berg, Janine, and Hannah Johnston. “Too good to be true? A comment on Hall and Krueger’s analysis of the labor market for Uber’s driver-partners.” ILR Review 72, no. 1 (2019): 39–68.
 Mishel, L. (2018). Uber and the Labor Market: Uber drivers’ compensation, wages, and the scale of Uber and the gig economy. Washington: Economic Policy Institute.
 Id. at 16.
 Hyman, L., Groshen, E. L., Litwin, A. S., Wells, M. T., Thompson, K. P., & Chernyshov, K. (2020). Platform Driving In Seattle. P1.
 Id. at 112. This is a particularly troubling statement given the history of predatory loans facilitated by Uber. For example, Uber’s Vehicle Solutions Program from November 2013 to April 2016 offered both current and prospective drivers predatory auto installment loans through partnerships with three subprime auto lenders. See Complaint at 8, Federal Trade Commission v. Uber Technologies, Inc., No 3:17-cv-00261 (N.D. Cal. Jan. 19, 2017).
 Hyman et al. at 45.
 The AEA principles are available here: https://www.aeaweb.org/journals/policies/data-code.
 This commitment to account for all time working in wage calculations reflects social norms, workers’ lives and understandings, and the law. “Engaged waiting time” under the Fair Labor Standards Act’s minimum wage and overtime regulations is considered compensable work time if that time is spent primarily for the benefit of the employer. Armour & Co. v. Wantock, 323 U.S. 126, 132, 65 S.Ct. 165, 168, 89 L.Ed. 118 (1944). Uber and Lyft drivers report spending roughly half of their working time awaiting fares, often driving to areas where the companies insist demand is higher. During this engaged time, drivers are bombarded with nudges and texts from the companies who use behavioral psychology and algorithmic control to push drivers to work not just in certain areas, but also for longer periods of time. If they reject fares, drivers report that they receive stern warnings, threatened deactivation, fewer and worse rides, and/or lower overall earnings. The engaged waiting time in between rides benefits the companies and their on-demand business model.