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Why a leading computer scientist believes co-ops are the future of data ownership?

Weekly newsletter of Coop Exchange
Weekly newsletter of Coop Exchange
The godfather of GDPR has turned into an evangelist of cooperatives, with a big and practical plan for reprogramming the entire data economy.

Alex Pentland
Alex Pentland
How the godfather of GDPR turned into a cooperative evangelist?
Alex Pentland is one of the most cited computer scientists in the world. He has played a pioneering role in shaping how the data economy works - not least by being one of the architects of the GDPR regulation, which is considered by many to be one of the most important pieces of data legislation in a generation.
In recent years, he has become a passionate advocate for cooperative ownership of data. In his vision, the 125 million members of the 5,000 credit unions (which are customer-owned cooperatives) in the US would be in an ideal position to reprogram the entire data economy by forming “data cooperatives” through which members would pool their data together in order to collectively bargain for it to be used in ways that are more beneficial for them and the society as a whole. Similar to how credit unions provide a space for depositing money, they could also provide a “vault” for members to store data. The credit union would not own the data; it would just host it, just like how money deposited in a credit union account is still owned by the customer. It would be different from how data works in the prevailing economic system, where it’s captured by the tech billionaires who own the platforms in which the data is produced, rather than by the ordinary people who produce the data by using the platforms.
 Pentland explains: 
What we discovered… is that there are certain sorts of cooperatives which are licensed by law, to manage peoples’ data. Just by accident in the US, credit unions are licensed to handle your digital data, which is basically everything about you. They can act as your legal representatives. They don’t own your data, they host it. They could for instance, and we built software for this, have you just check a little box, and your credit union would download all your data… It is practically possible to automatically record and organise all the data that citizens knowingly or unknowingly give to companies and the government, and to store these data in credit union vaults. In addition, almost all credit unions already manage their accounts through regional associations that use common software, so widespread deployment of data cooperative capabilities could become surprisingly quick and easy.” 
What could this look like in the everyday life of the ordinary credit union member?
One often mentioned idea relevant to data ownership is that of a “data dividend”, a payment one would receive from having their data used by technology companies to generate profits. However, Pentland dismisses this idea and believes more benefits could be provided in this instance by using the data to collectively bargain for shared benefits and “bundled offers”. Thomas Hardjono, a coauthor of one of his papers about the topic, gives an example of a data cooperative that “discovers that 25% percent of its membership are families with young children. They could turn around and go to Costco and negotiate a better deal for diapers, so instead of giving cash, you give them immediate benefits.
Pooling of data with others makes this possible. It is not very valuable for an individual credit union member to know how much cat food they buy. But pool that data together with others, and the credit union could help members who regularly purchase cat food to do joint-purchasing and therefore bargain a lower price. From the point of view of an ordinary member’s everyday life, it might be as simple as receiving a coupon code for cat food on their email or app. 
As Pentland explains: “The power of 100 million US credit union members who are practically and legally in control of their data would be a force to be reckoned with by all organisations that use citizen data and would be one very decisive way to hold these organisations accountable. The same potential for credit unions to balance today’s data monoliths exists in most countries around the world… From a software point of view, we’re there. From a legal point of view, we’re there… We just need a couple of examples to demonstrate exactly how this works.
He mentions a discussion he had with a leading data management software provider for the entire credit union sector, who he persuaded to add a few adjustments to the software used by practically the entire sector to enable the formation of these cooperative “data vaults”. As he described it, “we added some of our special magic to all the credit unions without them knowing” and explains that, from the credit unions’ perspective, they will continue running software like usual without even noticing a new update that enables giving members more choice over their data. The credit union seems, almost accidentally and without being aware, to be in an ideal position to enable people to radically reshape how the most valuable resource in the modern economy is owned. It is an opportunity they simply cannot afford to miss.
Over time, it might mean that coupon codes and other member-exclusive special offers might change from a supplementary perk into one core incentive of credit union membership. Some credit unions might reinvent themselves as sort of “coupon code machines”, facilitating members to collectively bargain for online discounts more effectively. 
Community ownership of data
However, even more importantly, data could be used in more broadly beneficial ways than providing discounts or similar purely economic benefits. Cooperative ownership would enable data to be used in ways that conventional companies would not have an incentive to do. 
To illustrate the limitations of innovation by conventional enterprises, let’s imagine that Facebook would start using data to develop a new feature that would make it easier for users to organise live events, and as a result, people would spend more time going to events at the expense of being on Facebook. The feature would harm shareholder profits as users would spend less time looking at ads, and it would therefore be removed even if users would find it beneficial. In other words, there is a conflict of interest between owners and users of the platform. If, on the other hand, Facebook were a cooperative owned by its users, it could simply decide that the benefits of the feature to members would exceed the costs. A conflict of interest between users and owners can be dismantled by making users into owners. 
For Pentland, cooperatively owned “community data” could enable what he describes as “people in a community asking each other questions’‘. To understand what he means, let’s imagine a scenario where a person notices their neighbour has their arm in a cast and asks them what happened. He replies by describing how he fell on a bicycle because the roads are more slippery than usual and recommends warning others about it. With a data cooperative, similar knowledge could be derived in a more sophisticated manner by detecting that an increased number of residents in the community have been in cycling accidents, which can prompt them to organise better pavement gritting. Pentland’s ideas about “community data” are not just theoretical - he has been involved in creating numerous successful pilots, including one in Senegal that revealed a new way to organise public transportation with a 15% improvement in effectiveness without any additional costs.
Previously there was a mention of an imaginary credit union that would use a data cooperative for organising members to collectively bargain discounts on cat food. They might also discover that many cat owners have a challenge in finding someone to catsit for them. The data cooperative could enable them to form mutual aid circles where people catsit for each other: if a member looks after another member’s cat for a week, they could have their cat being looked after by some other member for a week. For capitalist firms, there would be no incentive to do this. Because people make reciprocal favours instead of paying each other, there are no financial transactions to profit from. Credit union members, on the other hand, might simply decide that it is in their interest. In fact, the credit union could help members to start an independent cat-sitting cooperative for this purpose with an online platform, which would be relatively effortless to build using existing free, open-source software such as Wordpress. Because the platform would be owned by the users, the incentive would be to lower the transaction costs to a minimum, instead of the almost opposite incentive conventional platform companies have: to maximise transaction commissions.
Community data can be produced, and is in fact often more effective to produce, in a privacy respective manner. For example, Pentland points out that one major existing example of community data, that of government censuses, are able to tell the number of residents and their average age, income, etc. in a given area without knowing any personal details of any individual resident, let alone having to create an equivalent of a phonebook like directory with a detailed profile of every resident. I won’t go into much technical details about his solutions for ensuring privacy, but those interested can look into “Open Algorithms”, or “OPAL” for more details. Briefly summarised, the key mechanism behind OPALs is that the data is never moved or copied from the “data vault” and “algorithms are moved to the data” instead. The current norm is the opposite - collecting a lot of data into one location where algorithms are run on it. Instead, with OPAL, each personal data vault runs the algorithm independently and returns an answer that is aggregated in a way that does not risk the privacy of any individual. This somewhat resembles other forms of community data, such as the national census mentioned previously.
Pentland also makes the case on how this could tackle the “cold-start” problem in which incumbent tech giants possess a big advantage over new competitors due to having access to more data. With data cooperatives, the data would no longer be hoarded by the monopolistic giants, but would allow equal opportunity for all individuals and businesses to present their ideas on how it could be used for the benefit of the members.
This radical restructuring of the key source of power for the currently most powerful companies in the world could help usher in an era of more accountable and equitable technology companies - spearheaded by cooperatives. The cooperative movement needs to avoid trying to simply catch up and copy its capitalist competitors and instead realise that it can radically restructure the future course of technological progress in ways its competitors can’t.  For cooperatives to explore and establish themselves in new and emerging sectors, new forms of financing for cooperatives need to emerge. Pursuing this is what drives us at Coop Exchange, and if you think it’s a goal worth pursuing, join us in this endeavour by subscribing to this newsletter.
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