What challenges must be overcome to move towards cooperative economies?
This weekend, I’m here at the Platform cooperativism conference, where I’ll be talking on Saturday at 4pm. This session on “making it work” featured a series of sociologists, legal scholars, and business scholars to discuss this question.
What could the platform cooperativism movement learn from how people are experiencing peer economies? When we try to clone the heart of these platforms, what does that heart look like?
Juliet, a professor of sociology at Boston college, talks to us about her work on “connected consumption,” who has been studying the “connected” or “sharing” economy, looking at work in for-profit as well as nonprofit contexts. They’ve done over 200 interviews and hundreds of hours of participant observation with the largest time bank in the US, a food swap network, and a large makerspace (Artisans Asylum?), as well as airbnb, Turo/RelayRides, TaskRabbit, PostMates, and profit/nonprofit activities in open access education. Juliet puts these on a two-dimension access of peer-to-peer/centralized and profit/non-profit.
The first lesson from her work is that it’s important to get the value proposition correct. Many of the nonprofits aren’t delivering value to people, and the thing that will get people engaged will be if it’s valuable to them. For-profits are nailing the value proposition for consumers, which is why consumers are flocking to them. They’re also getting the right “consumer habitus” — the experience that consumers are interested in. Furthermore, workers have also been happy with their earning potential, although things may have changed since their fieldwork in 2013.
In contrast, non-profit initiatives are generally failing on value. The time bank has too little volume and struggle to create value. The food swap also had volume problems.
Secondly, these platforms can enhance inequality. Juliet points out that these platforms making working class work–blue and pink collar work– de-stigmatized for college and other higher class people. This shouldn’t be surprising, says Juliet, since the middle class is less well off than before. She argues that we’re not seeing poor people work on these platforms, so they’re not addressing inequality.
Juliet did not expect to find that the non-profits are sites of almost surprising levels of class, race, and gender exclusivity. They involve high cultural capital people who develop in-groups, developing cultures that are extremely off-putting to people who are not in those groups. Not only are the demographics of these sites so gender-segregated, so white, and so highly educated — it’s also the way people are acting in these sites. In Bordeiu’s “high cultural capital” idea of people, you get people with lots of thoughtful ideology, but in practice, they act in very different ways. “You need to start your co-operative with the people you end up with,” she argues.
Designers of platforms often promise all sorts of equality. Juliet’s research finds that this just isn’t true, either in for-profit contexts or nonprofits.
Frank Pasquale: Risk Mitigation Strategies for Platform Cooperatives
What are the evolving legal problems that might arise for platform co-ops as they gain speed. He’s going to talk about the risks to co-ops from governments, as well as from dominant platforms. He’s drawn from empirical work by Tom Slee.
In the early stage, co-operative platforms will be seen as hobbies and curiosities, tiny things that are nice and addressing some kind of problem. In this early stage, large corporations might welcome the co-ops. As government starts trying to regulate these large corporations, lawyers at these corporations will push back against regulation by pointing out the importance of supporting these co-ops. Paperwork itself is another problem for new co-operatives. Frank argues that it may be possible to get some exceptions for small and early stage co-ops at the incubator stage.
In the next stage, we might get an ecosystem of smallish competitors. At that point, we’ll start facing the paradoxes of platforms. Referring to Zak Stone’s Living and Dying on Airbnb, he points out that companies often position themselves as “just a platform” and disclaim liability. Platform co-operatives might try to take more responsibility and control over how things work, but they might also take on more liability. Uber unsuccessfully argued that it’s not responsible for discrimination on the platform, but co-operatives might take on that liability.
In a further stage, the industry may start consolidating, creating issues related to antitrust law. In the United States, antitrust law is fine with monopolies that have 80% – 90% of the market, it’s fine so long as they’re not abusing that power. In contrast, if you have lots of little firms banding together, they are often seen as a horizontal conspiracy to control trade. When publishers ganged up on Amazon, that was seen as possible conspiracy. Pasquale worries that this might happen to platform co-operatives as they try to work together or create standards together.
If there’s consolidation and the people behind the platform co-op say to the Uber drivers that they would like them to “multi-home” by taking rides from Uber and the co-op. At this point, the dominant platform might introduce a non-compete requirement. In “1099 as antitrust,” Steve Randy Waldman suggests that the IRS shouldn’t allow 1099s unless workers are also allowed to work for more than one employer.
To conclude, Frank says that we need to learn the lessons of other data-intensive industries like search. Whenever an entity says “we’re just an app” to avoid responsibility, that self-deprecation needs to be taken seriously. Finally, whenever people try to conflate a technology with a firm by saying “Uber” or “airbnb” brought us this, we need to remember that it was people. These firms are not set in stone, he says; we’re going to need a lot of pro-active regulation and law.
Run describes the rise of what he calls crowd-based capitalism, and the ways that companies are replacing certain kinds of work with new infrastructures. These platforms take things that used to be in the personal space and blend them with the professional, “for money” world. Arun argues that we’re struggling to create new categorizations, new language that we can use to understand how to regulate them. He offers an overview of ways that platforms are addressing banking (Kiva), hotels(airbnb), retailers(etsy), high-end-retail (rent the runway), transportation (Uber), diversified labor (TaskRabbit), personal services (Shyp), corporate services, rental car companies, and risk capital intermediaries.
How do platforms affect wage rates? Arun shares data he analyzed that compared average wage rate for a region to the comparable digital wage rate in that area. For work that requires you to be present, the wage rate is greater, while for work that is remote, the wage rate is smaller.
How do these platforms affect people’s standard of living, Arun shares results from his work that suggest that people will sometimes use these platforms to access a higher standard of living, buying that Tesla because they know they can rent it out. The jury is still out however, for whether these platforms will be a path to entrepreneurship and innovation, equalize access to infrastructure, equalize channels for growing one’s human capital, or equalizing access to financial capital.
Arun concludes by talking about the relative efficiency of ownership structures. Fast-moving industries seem to favor traditional corporations, he says, while co-operatives tend to do best in slower-moving industries — exactly things like ride sharing, etc.. But could co-operatives dislodge incumbent companies? For companies that don’t require in-person work, the network effects are strong, and it will be hard to push out incumbents. On the other hand, Arun argues that the network effects of ride sharing are very local — people don’t care who the leader in LA is when they’re in New York.
Finally Arun asks if blockchain structures are going to lead to viable organizations. If we want these blockchain systems to work, he argues, we need de-centralized search and discovery, logistics, and trust.
Yochai Benkler Peer mutualism and the future of capitalism
One way of thinking about the problems we’re talking about today is as a response to a particular class of technologies and companies that have aggressive business models, says Yochai. This is not terrible, he says, but it might be more productive to look at a 40 year process of rising inequality throughout many economies. The critical reason to think of the 40 year trajectory is to understand that it also masks two distinct phenomena. The first is the separation of income growth for median income from productivity growth in the economy– the stagnation of growth for the middle class and the stratospheric rise of the top 1%, 0.1% and 0.001% independent of what was happening for the rest. For 20 years, the dominant belief was that technology was increasing returns to skills, therefore people with high skills became more productive. Income follows productivity in an efficient market, and therefore inequality grew– that was the belief.
In the last 18 months, there’s been increasing review of the last 20 years evidence, suggesting that skills-based tech change has only a weak correlation to changes, and that the other explanations are institutional ones. At the top, you have stock options, experts and compensation committees. At the bottom, you have weak labor standards, deunionization, and reduced welfare payments.
Benkler argues that we should be thinking about two things. Firstly, there’s a political theory underlying free software and cooperation: that if we roll our own we will be more effective at preserving freedom than if we build systems through government. There’s a correlation between this and co-operativism because we need to think of co-ops in relation to what. The alternative is trade unionism, you’re accepting the mode of productions and working to build political power in order to redistribute through the state and use the power of the state to regulate and contain. Co-ops are similar to the ideology of free software: we build and own our own things and shift power through changed ownership structures.
We need to imagine three sources of stress in the coming economy, says Yochai. Firstly, automation was dehumanizing and making a skilled person into an unskilled worker. Now we’re giving robots the work. Secondly, the temp economy has been generalized into things like TaskRabbit. Finally, we have the use of data to extract value, using surveillance to manipulate people. The latter two are more addressable by co-operatives, but not the first.
If the network information economy was about moving things that had been in concentrated transactional frameworks into combinations of social and market production, we’re seeing platform companies create extractive versions of commons based peer production. The same dynamics and efficiencies behind the success of things like open source and Wikipedia are being used by companies to extract value.
Yochai notes that commons based peer production was based on volunteer effort to create freely-available outputs. But a transition to peer cooperativism must deal with the challenges of worker-owned and produced cooperatives. Competition constrains operations. Although being in the market constrains your ethics, he argues that inefficiencies in the market make it possible to be wealthy. There’s no systematic data that co-ops necessarily involve higher wages. The wages might be more stable, and there might be more poverty alleviation, but there’s no evidence that they can offer higher wages. Furthermore, co-ops seem to succeed in some places and not succeed in others.
If you imagine it and do it in time, you can do it and capture the market. It just needs to happen and then it stabilizes, says Yochai.
Competing with on-demand economies is possible. It’s not clear that one can just do the same thing as companies. Uber has clearly solved the problem from a consumer-side. It wouldn’t take much change at the consumer end. But it’s not yet clear how to create reliable income for people from unreliable demand. Uber doesn’t have to solve that problem because their business model externalizes risk.
You also have to deal with the problems that consumer co-ops have had. One of the great powers of networked economies is that you have people with very different levels of engagement. In consumer co-ops you have such diffuse membership that it’s often impossible to differentiate between a loyalty card at a corporate supermarket and membership in a co-op. These problems haven’t been solved yet in peer production. We know that there are problems of concentration of power there too, Yochai says.
Yochai also talks about the idea of co-op alliances. Instead of thinking about apps that compete, he urges people to think about an ecosystem that is working together to create co-ops, as well as mobilizing politically.
Finally, Yochai urges people to commit to an open commons. The only thing that will make platform cooperativism work, he argues, will be a shift in ideologies, beliefs about what is right and wrong. It means thinking about an open commons for service models, material goods, data portability, and open access.
Rachel Sherman facilitated the discussion, and I was able to get part of it.
Trebor asks Juliet about the “habitus” of users being exclusivist. Was it because they tried to do so much in person? Juliet mentions the work on Iron Laws of Oligarchy. When you create an egalitarian system without traditional status markers, you get a new status system that comes out in the cultural realm. It’s very intense status jockeying around cultural values. She describes the idea of “ego habitus,” where egalitarianism is a high-cultural taste that is used to jockey for power in these spaces.
A participant asks about the idea of consumer cooperatives. Juliet agrees that it’s important to think about both sides of the market. If you just organize one side of the market and not the other, you deal with problems of exploitation. Frank talks about the decline of group purchasing organizations. Hospitals used to create these group purchasing orgs in order to collectively bargain with medical device suppliers, but those GPOs got captured by the suppliers.
An audience member argues that the failure of antitrust has been a political economy failure — as the U.S. offered various exemptions to different industries. How do we move back towards strong anti-trust regulation? Frank takes inspiration from the cultural battle that Zephyr Teachout is fighting. Another option is to keep hectoring regulators by comparing them to Europe. But in so many U.S. law schools, the thought is often, “how can we make it a better market” rather than, “what can we learn from others?”
An audience member asks what the opportunities for blockchain are. Arun thinks that blockchain technologies provide new codebase templates for alternative models of organizing. Discussions over the promise of the blockchain have been focused on moves by large financial institutions to create more effective, privately owned markets. Arun argues that “the initial new organizational forms we see emerge that are built on top of the blockchain may not be the distributed, collaborative organizations that people imagine.” On bitcoin, only the people managing the transactions are making money from it. He argues that it’s hard to embed a wider set of values into a system.
Yochai responds by saying that the promise of blockchain is that you will circumvent the platform that provides claims and promises as the source of concentration. You embed that in an algorithm and you will route around that particular place where concentration happens. In the case of bitcoin, concentration moves somewhere else. If you look at more recent, sophisticated systems, you can still develop oligarchies. Just like Wikipedia, you could tell people to “go fork it” but of course you can’t fork Wikipedia. So you have to bring an ethical commitment and organizational awareness to whatever new layer is open to being captured by any group, because the technology has just shifted the point where you reconcentrate.
Frank responds with worries that trusting algorithms participates in a wider, longer move to de-politicize fiscal policy and talks about what it would take to re-politicize them.
In response to the next question, Juliet talks about her hopes that platforms might reduce the transaction costs of starting a co-operative. If you can figure those out more quickly and get the right structure and rules in the platform, perhaps you might be able to scale it rapidly? She argues for a certain level of democratic consensus, but her hunch about many of the existing, offline co-operatives is that the democratic work you do to decide the rules is what holds you back– larger co-ops like Mondragon are able to scale because they’ve already made those decisions.