I was yesterday at a nice and interesting conference in Brussels on “How to coop the collaborative economy“, organized by major actors of the Belgian cooperative movement and building on the experience of a growing network of persons and organizations to enhance a cooperative view of the internet. Several themes in connection with my studies of the collaborative economy emerged, and I’d like to summarize here what were, in my view, the main lessons learned of the day.
Category Archives: Data in society
Special RFS issue on Big Data
Revue Française de Sociologie invites article proposals for a special issue on “Big Data, Societies and Social Sciences”, edited by Gilles Bastin (PACTE, Sciences Po Grenoble) and myself.
Focus is on two inextricably interwoven questions: how do big data transform society? How do big data affect social science practices?
Substantive as well as epistemological / methodological contributions are welcome. We are particularly interested in proposals that examine the social effects and/or the scientific implications of big data based on first-hand experience in the field.
The deadline for submission of extended abstracts is 28 February 2017; for full contributions, it is 15 September 2017. Revue Française de Sociologie accepts articles in French or English.
Further details and guidelines for submission are in the call for papers.
Data, health online communities and the collaborative economy: my tour of Québec
This November gave me the opportunity to give talks and participate in scientific events throughout Québec.
I started in Montréal, with a seminar at ComSanté, the health communication research centre of Université du Québec à Montréal (UQAM), where I presented my recently published book on websites on eating disorders. While most media attention focused on controversial “pro-anorexia” contents, presented as an undesirable effect of online free speech, I made the point that this part of the webosphere is rather to be seen as a symptom of the effects of current transformations of healthcare systems under austerity policies. Cuts in public health spending encourage patients to be active, informed and equipped, but the resulting social pressure creates paradoxical behaviors and risk-taking.
Also in Montréal, I was invited to a discussion with economic journalist Diane Bérard on the growth and crisis of the collaborative economy. About 50 people attended the event, co-organised by co-working space L’Esplanade, OuiShare Montréal and the journal Les Affaires. Diane summarized the essentials of the event in a blog post just the day after, and noted six main points:
- The Uber case dominates discussions and divides the audience – though the collaborative economy is not (just) Uber.
- The discussion gets easily polarized – a result of the tension between commercial and non-commercial goals of the collaborative economy.
- We still know little of the business models of these platforms and the external factors that facilitate or hinder their success.
- Sharing is in fact a niche market – now probably declining after the first enthusiasms.
- The key issue for the future is work – its transformations, and how it is re-organizing itself.
- Collaborative principles advance even outside the world of digital platforms, and sometimes permeate more traditional sectors. The near future of collaboration are sharing cities.
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Online health communities: data for doctors, patients and families
Online health communities have been demonstrated to be an important part of the self-empowering experience of today’s patients. While most attention so far has been devoted to self-styled health communities, where patients autonomously share expertise and experience, today policymakers and healthcare providers are harnessing the power of this very idea and are offering similar solutions themselves.
Earlier this week at the OuiShare Fest Barcelona – a major get-together of the Spanish-speaking collaborative economy community in Europe – a few of these initiatives were presented.
Social Diabetes is a small company founded by and for patients, that offers a mobile app for online, real-time health monitoring services. Diabete sufferers can use it to optimally adjust their insulin dosage based on their carb count and blood sugar levels; in some cases, they can also track their exercise and patterns of behavior to receive alerts whenever relevant. Patients can share this information with their doctors, also through the app; and can discuss with other patients. This is an example of a user-based innovation where autonomous patients take the initiative, aiming to take control of their health and life. Still, physicians have been allowed in: the platform has a medical advisory board, and individual doctors can register as users to follow their patients.
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Are we all data laborers?
I gave today a talk at AUTONOMY, a major festival of urban mobility in Paris, where new technologies are at center stage, from driverless cars to electric scooters, bike-sharing solutions, and connected infrastructure for the smart city. I had been asked to talk about labor in digital platforms, such as those offering mobility services.
Digital platforms are often thought of in terms of automation, but it is clear that there is labor too: we all have in mind the example of the couriers and drivers of the “on-demand” economy. But there’s more: I’ll show how platforms involve the labor of everyone, including passengers and users of all types. By labor, I mean here human activity that produces data and information – the key source of value for platforms. It is often an implicit, invisible activity of which we may not even be aware – as we tend to focus more on consumption aspects as we talk routinely about “car pooling” or “car sharing”, rather than looking at the underlying productive effort. This is what scholars call “digital labor”.
Four eco-systems
Specialist Antonio Casilli distinguishes four forms of digital labor in platforms, and I am now going to briefly outline them.
The “pro-ana” phenomenon: Eating disorders and social networks
A new book is just out, co-authored by myself and Antonio A. Casilli: a synthesis of our 5-odd years research on the self-styled internet communities, blogs and forums of persons with eating disorders. For years, lively controversies have surrounded these websites, where users express their distress without filters and go as far as to describe their crises, their vomiting and their desire for an impossibly thin body – thereby earning from the media a reputation for “promoting anorexia” (shortened as “pro-ana”). In France, an attempt to outlaw these online spaces last year was unsuccessful, not least because of our active resistance to it.
The book tells the story of our discovery of these communities, their members, their daily lives and their social networks. Ours was the first study to go beyond just contents, and discover the social environments in which they are embedded. We explored the social networks (not only online relationships, but day-to-day interactions at school or work, in the family, and among friends) of internet users with eating disorders, and related them to their health. The results defy received wisdom – and explain why banning these websites is not the right solution.
Internet deviance or public health budget cuts?
It turns out that “pro-ana” is less a form of internet deviance than a sign of more general problems with health systems. Joining these online communities is a way to address, albeit partially and imperfectly, the perceived shortcomings of healthcare services. Internet presence is all the more remarkable for those who live in “medical deserts” with more than an hour drive to the nearest surgery or hospital. At the time of the survey in France, a number of areas lacked specialist services for eating disorder sufferers.

These people do not always aim to refute medical norms. Rather, they seek support for everyday life, after and beyond hospitalisation. These websites offer them an additional space for socialisation, where they form bonds of solidarity and mutual aid. Ultimately, the paradoxical behaviours observed online are the result of underfunded health systems and cuts in public budgets, that impose pressure on patients. The new model of the ‘active patient’, informed and proactive, may have unexpected consequences.
A niche phenomenon with wider repercussions
In this sense, “pro-ana” websites are not just a niche phenomenon, but a prism through which we can read broader societal issues: our present obsession with body image, our changing relationships with medical authorities, the crisis and deficit of our publich health systems, as well as the growing restrictions to our freedom of expression online.
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Data and theory: substitutes or complements? Lessons from history of economics
Today, my chapter on “Formalization and mathematical modelling” is published in a new series of three reference books on History of Economic Analysis (edited by G. Faccarello and H. Kurz, Edward Elgar). The chapter draws heavily on key ideas I developed as part of my thesis on the origins of mathematical economics. But this was a long time ago and reading it again today, I see it in a different light. I notice in particular that economics developed its distinctive mathematical flavour, which makes it neatly stand out relative to the other social sciences, at times in which social research was data-poor – and it did so not despite data paucity, but precisely because of it. William S. Jevons, a 19th-century forefather of the discipline who was clearly aware of the relevance of maths, wrote in 1871:
“The data are almost wholly deficient for the complete solution of any one problem”
yet:
“we have mathematical theory without the data requisite for precise calculation”
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First steps toward “Data Inclusion”
The concept of “data inclusion” is new and still slowly seeking its way in our linguistical habits, but it is gaining ground in the minds of those who care for disadvantaged, low-income, or otherwise underserved segments of society. A recent report of the US Federal Trade Commission (FTC) does precisely this. Looking at the commercial use of big data analytics, it considers cases in which big data analytics lead companies to make choices that are detrimental to the most vulnerable segments of society, for example by excluding them from credit or from employment opportunities. Instead, it asks how big data may be used in inclusive ways.
A first set of recommendations they make is for companies to be well aware of the regulations: on financial and credit reporting, equal opportunities, consumer protection. The second set of recommendations, though specifically aimed at research done in (or for) companies, is of relevance for public research as well, and consists in asking key questions about the quality of data and models, and about the reliability and validity of results:
- How representative is your data set? In popular discourse, big data carry a promise of exhaustivity, which however is rarely fulfilled in practice (see this great FT article by Tim Hartford). In fact, big data sets are not necessarily statistically representative of the population they refer to, and information may be disproportionately missing about specific, possibly disadvantaged, populations.
- Does your data model account for biases? Selection effects, which occur whenever some members of the population are less likely to be included in the sample than others, must be controlled for in order for results to be generalizable.
- How accurate are your predictions based on big data? The issue is that most research with big data is predictive without being able to uncover the social or economic mechanisms underlying observed correlations, so that interpretation of results is potentially misleading. The report does not say, though, that recent developments in machine learning that support causality reasoning may alleviate this problem in the not-so-far future.
- Does your reliance on big data raise ethical or fairness concerns? In all honesty, this is not specifically a question for research on big data, but for research in general. If a company’s analysis of employees’ behavior lead to solutions that involve forms of, say, racial or gender-based behavior, then that analysis shouldn’t be used – whether it’s done with “big” or “small” data.
It is important that major regulators like the FTC are taking notice. Big data open the way to major improvements in our life conditions, but not because data-driven analysis will take the lead over current best practices in research. Regulations, awareness of statistical issues and potential pitfalls, and ethics are ever more necessary for big data to fulfill their potential.
Hierarchy, market or network? The disruptive world of the digital platform
Economics traditionally considered firms and markets as two alternative ways of coordinating economic activities. Nobel prize winner Ronald H. Coase (1937) demonstrated that it all hinges on “transaction costs”, such as the need to search for a trade partner, the time needed to negotiate a contract, the legal expenses to draw it up and if necessary, to enforce it. When these costs are high, then hiring people in a firm is the right solution. When they are low, then a harmonious state will emerge spontaneously from the choices of independent, self-employed individuals. The difference, further emphasized by the work of Oliver Williamson, another Nobel, is between the world of bureaucracy, hierarchy and salaried work, and the world of the market and myriad micro-entrepreneurs.
This dichotomous description seemed reductive to economic sociologists, and Mark Granovetter (1985) pointed to social networks as coordination devices. Networks enable circulation of knowledge, formation of trust, emergence of shared norms in informal ways, thereby lowering costs and smoothing economic transactions. Walter W. Powell (1990) saw networks as an alternative to market and hierarchy, while others thought of it as a complement rather than a substitute. In some cases, the relevance of networks is flagrant: think of “collegial“, horizontal organizations such as legal partnerships, which are clearly not markets, and which have no vertical hierarchy either.
The rise of online platforms challenges these older views today. Powered by digital data and matching algorithms, platforms are meeting places for actors on the two sides of a market: riders and drivers (Uber, Lyft, BlaBlaCar), guests and hosts (Airbnb), buyers and sellers (eBay), and so on. Officially, platforms are intermediaries only, able to put in touch, say, those who need a lift and those who have a car, so that they can share the ride. Platforms don’t employ drivers and don’t own cars.
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Discussing platform cooperativism
On Monday, 7 December 2015 at Telecom ParisTech, I was discussant at a seminar by New School scholar Trebor Scholz on “Unpacking Platform Cooperativism“.
Internet platforms carry an unprecedented potential of value creation, exploiting the extraordinary power of data and algorithms to extract and distribute information to an extent never seen before. Information, we know since Hayek’s times, is the fuel that keeps markets going, that eliminates “lemons” and ensures an ever-better coordination between buyers and sellers, borrowers and lenders, or landlords and tenants. At the same time, the internet has channeled the dream of a viable non-market society, since Rheingold’s 1993 revival of the “community” and Barbrook’s 1998 “hi-tech gift economy“. So, can we put this informational efficiency to the service of a more humane economy, based on relationships, solidarity and reciprocation, rather than on the sheer market system?
The so-called “sharing economy” suggests answers, but also displays a tension: the efforts of myriad grassroots associations to develop collaboration as a value and a practice, sharply contrasts the spectacular growth of firms like Airbnb and Uber, now large multinationals, and their alleged cavalier attitude to anti-trust regulations and workers’ rights. If some say Uber is not really about sharing and collaboration, it is difficult to draw the line.
This ambiguity is fostered by a public discourse that focuses on the sharing of assets – the spare room in your home, or a sit in your car – that digital platforms enable. Asset-sharing has economic and social appeal: it increases efficiency by preventing assets from lying idle, while reducing waste, shifting emphasis away from consumerist values (“access is better than ownership“), and facilitating sociality beyond mere consumption.
But it is often forgotten that asset-sharing does not produce value by itself: it involves extra labour. In economic jargon, capital and labour and complementary production factors. In practice, if you want to put your spare room on Airbnb, you must produce an ad, monitor your message inbox and reply swiftly. You must clean the room and do the laundry before and after a guest’s visit. You must show your guests around when they arrive.
More importantly, the very opportunity of asset-sharing changes the incentives that shape labour supply – people’s willingness to sell their time and effort against a payment. Because of the expected compensation, some people will renounce use of a (non-spare) room to accommodate visitors instead, and others will do more journeys to drive passengers around – so it’s not really about sharing unused assets, it is about self-employment and starting a micro-business. A work opportunity as a complement to (and sometimes a substitute for) a main job.
This is where debates on internet platforms and the sharing economy rejoin the growing literature on digital labour — and where the contribution of Trebor Scholz is illuminating. Where others see assets (ie, capital), he sees labour. He shows us that the bottlenecks here are about labour, not capital, and that the success — be it economic or social– of the sharing economy is closely tied to the destiny of labour. Whether it appears on the surface as self-employment, micro-entrepreneurship or salaried work, doesn’t really matter. Trebor reminds us of Marx’s fundamental principle that production relations are central to our (capitalist) society, and value generation rests ultimately on labor. If this very crucial part of the human experience goes wrong, even the best side of the sharing economy – the one that endorses trust, reciprocity, and zero-waste – may fail to perform any transformative effects on society.