Workshop on Economic Governance of Data-driven Markets:
Understanding and shaping the economic, social, legal, and political effects of datafication
12-13 October 2017, Tilburg University, The Netherlands
- Yochai Benkler, (Harvard Law School)
- Paul Seabright, (Toulouse School of Economics)
- Joshua Tucker, (New York University)
- Marshall Van Alstyne,
Click here for the Call for Papers in PDF
For the last years, datafication has been massively impacting processes within organizations, industries and markets, and more generally throughout the society. To a large extent this development was driven by the increasing reliance on information and communication technologies, which support an increasing share of economic and social transactions and systematically record the resulting tracks, leading to a profusion of data about behaviors, processes and flows. Complement to this increased availability of data, tremendous progresses have also been made within firms and governments to analyze them and to rely on them to refine processes and manage experiments (Mayer-Schönberger and Cukier, 2013). Machine learning pushes this loop between data accumulation and innovation even further.
In “The Second Machine Age” (2014:8), Brynjolfsson and McAfee motivate their study of the contemporary effects of big data and datafication as follows:
For years we have studied the impact of digital technologies like computers, software, and communications networks, and we thought we had a decent understanding of their capabilities and limitations. But over the past few years, they started surprising us. Computers started diagnosing diseases, listening and speaking to us, and writing high-quality prose, while robots started scurrying around warehouses and driving cars with minimal or no guidance. Digital technologies had been laughably bad at a lot of things for a long time---then they suddenly got very good. How did this happen? And what were the implications of this progress, which was astonishing and yet came to be considered a matter of course?
This is a very optimistic account of the latest technological developments. But when Brynjolfsson and McAfee comment on its downsides, they focus on “spread,” which they describe as “ever-bigger differences among people in economic success – in wealth, income, mobility, and other important measures” (p.12). In this respect, they join a large group of technologists who understand the opportunities of data-driven technologies well but seem to not exhaustively account for the involved threats for individuals and society.
Then, the other extreme is represented by technology critics. Comparing the very asymmetric armament of sellers and individual consumers in data-driven markets, Acquisti and Grossklags (2007:369) note that “[c]onsumers will often be overwhelmed with the task of identifying possible outcomes related to privacy threats and means of protection. [. . . ] However, even if individuals had access to complete information, they would often be unable to process and act optimally on large amounts of data.”
Extending the big data technology critique to the political sphere, Morozov (2011:xiv) writes: Failing to anticipate how authoritarian governments would respond to the Internet, cyber-utopians did not predict how useful it would prove for propaganda purposes, how masterfully dictators would learn to use it for surveillance, and how sophisticated modern systems of Internet censorship would become. [...] Paradoxically, in their refusal to see the downside of the new digital environment, cyber-utopians ended up belittling the role of the Internet, refusing to see that it penetrates and reshapes all walks of political life, not just the ones conducive to democratization.
there seem to be two opposite approaches to current technological developments
related to big data. The first mainly underlines the positive effects of
technological progress in general, and the increased opportunities for
citizens’ participation and consumers’ customization of products that is
becoming possible through the embrace of data-driven technologies. On the other
side, scholars have pointed at the negative economic, political, and social
effects of increasing datafication and ubiquitous connectivity of today’s and
... and Economic Ecovernance
The field of economic governance studies how institutions can help to overcome free-rider and coordination problems. In particular, it regards “the structure and functioning of the legal and social institutions that support economic activity and economic transactions by protecting property rights, enforcing contracts, and taking collective action to provide physical and organizational infrastructure” (Dixit, 2009). By its nature, economic governance necessitates the application of a broad set of methodologies, including game-theoretic modeling, empirical investigations, and case studies, connecting the disciplines of economics, law, sociology, history, political science, and potentially others.
After three economic governance workshops that focused on the role of competition (in 2010), organizations (in 2013), and social preferences (in 2015), respectively, we now strive to stimulate the debate about the economic, social, legal, and political effects of datafication. Combining approaches from institutional economics, industrial organization, and law & economics – and extending to neighboring disciplines such as political science, management, or information science – the goal of this workshop is threefold:
- What problems are specific to data-driven markets? What is the theory of harm, and what are the underlying mechanisms that lead to the potential harm identified?
- In sectors where a theory of harm can be carved out, is there a need for intervention in markets, communities, or political landscapes? What kind of intervention might solve or mitigate the problems identified? Or is it best to leave these highly-innovative markets untouched, even if market failures were found, and rely on the next disruptive innovation to arrive spontaneously?
- What is the best way of intervention to tackle which problem? How should data- driven markets or political systems be governed? By national or supranational regulation (public ordering)? Or by self-governance of industry-participants in some form (private ordering)? Should behavior be monitored by private associations or public-private partnerships? What are critical elements for the corporate governance structure of monitoring or regulatory bodies?
The Governance and Regulation Chair at the University Paris-Dauphine/PSL and the Tilburg Law and Economics Center (TILEC) are joining forces for a two-day workshop to discuss topics related to these goals.
Specific Topics include (but are not limited to)
- What types of markets are affected most by the rise of big data and algorithms, and what is the defining element of these markets?
- How is the competitive process influenced by datafication? Would algorithms be able to oversee the competitive process?
- How could social, legal or political institutions be affected by data-driven business models?
- What exactly are problems stemming from limited privacy? Are mechanisms aimed at controlling privacy implementable given the reach of statistical inferences?
- How may opinions and beliefs be shaped by algorithms and data-driven processes? Does the answer to this question have implications for the future of democracy, rule of law, collective governance capabilities, openness of (economic and political) competition?
- Can the postulated negative effects on data-driven markets that were advanced by theoretical research be substantiated empirically?
- Are there case studies that compare several types of governance structures — e.g. private vs. public; national vs. transnational — aimed at regulating industries that are transformed by big data?
- How to deal with the attempts of governments — both democratic and authoritarian — in relying on digital services to monitor citizens and organizations of all kinds?
- Hervé Alexandre (Paris-Dauphine/PSL)
- Lisa Bernstein (Chicago)
- Marc Bourreau (TélécomParisTech)
- Eric Brousseau (Paris-Dauphine/PSL)
- Eric van Damme (Tilburg)
- Ruben Enikolopov (Pompeu Fabra & New Economic School)
- David Ettinger (Paris-Dauphine/PSL)
- Lapo Filistrucchi (Florence & Tilburg)
- Martin Husovec (Tilburg)
- Henri Isaac (Paris-Dauphine/PSL)
- Julien Jourdan (Paris-Dauphine/PSL)
- Tobias Klein (Tilburg)
- Wieland Müller (Vienna & Tilburg)
- Etienne Pfister (French Competition Authority)
- Jens Prüfer (Tilburg)
- Stéphane Saussier (Sorbonne Business School)
- Christoph Schottmüller (Copenhagen)
- Florian Schütt (Tilburg)
- Joelle Toledano (Centrale-Supélec/Paris-Saclay)
The program will be announced in due time
The workshop will take place at Tilburg University, the Netherlands, from October 12 to 13, 2017 and is planned for two full days. Regular presentations (30 minutes) will be followed by a discussant (10 minutes) and public discussion (20 minutes). For keynote speakers, the format will be 45 minutes presentation and 30 minutes of public discussion. There will be plenty of time for informal discussion and social interaction. Additionally, a poster session may be held during both lunch breaks if the quality of dedicated submitted papers suggests it.
Fees and Reimbursement Policy
There is no conference fee. The hosting organizations will cover the accommodation and travel expenses of speakers in the regular sessions (not in the poster session) and the accommodation expenses of discussants.
The deadline for submissions is May 14, 2017. Papers should be submitted in PDF format to email@example.com
Long abstracts are accepted but full papers are preferred. Unless otherwise mentioned with the submission, it is understood that the author submitting a paper is also the presenter and present throughout the workshop. Submitters should indicate whether they want their paper to be considered for a poster session. If accepted for a poster session, authors are responsible themselves for producing their poster.
Authors of accepted papers will be notified by June 30, 2017. Speakers might be asked to discuss another paper. Completed drafts of accepted papers are due by September 30, 2017, and will be made available for download on the conference website.
- Jens Prüfer (Tilburg University), firstname.lastname@example.org
- Eric Brousseau (University Paris-Dauphine/PSL), email@example.com