However, I’m concerned Solid is ill-equipped to tackle the challenges of the data ownership space and deliver impact. This article explores some of the problems PDSs face and suggests we need a strategic approach that’s user centered, systemic and allows for a diversity of approaches to overcome centralisation.

Can we sell privacy?

The scandals over Cambridge Analytica’s abuse of Facebook’s app privileges, and the implications in terms of political influence and the spread of disinformation, has led to a significant rise in interest in the decentralised web. People increasingly distrust Facebook which shares your phone number with advertisers to target ads and Google which tracks your location even when tracking is explicitly disabled. More recently, the unwitting exposure of at least fifty million Facebook profiles to the prying eyes of random hackers will only increase the pressure on companies to demonstrate that they can be safe custodians of personal data. So earlier this year, myself and Simon decided to explore the personal data store space to assess the effectiveness of the approach Solid takes.

How does a Personal Data Store work?

Solid’s model is typical of a lot of the PDSs we looked at. User data lives in a datastore. The user either self hosts, or pays for someone to securely host a PDS on their behalf. Applications read/write to that data through user controlled granular permissions.

In the best case scenario of this model, app developers simply provide the interface and functionality of, for example, a calendar or journal app. The data always lives in your datastore. When you browse your journal or calendar in a web or desktop/phone app, the data from your datastore is displayed in the interface, but it’s securely transmitted between you and your datastore. No other parties are able to access it. This would be game changing.

But there are challenges

1. Most digital transactions require verified claims

Much of Tim’s narrative assumes that there is clear ownership of data, which is far from straightforward. Different entities are looking for different kinds of data:

• For the majority of digital transactions and interactions (buying things online, applying for services, booking a flight, proving my age), the most valuable data is data asserted about me from an authoritative source. For example, that I have a valid driving license or verified address, bank account, passport.
• For advertising, it’s what I bought and where I clicked as well as profile data (email address, demographic and interests info). This data is generated by the services I use (e.g. Facebook, Google, Twitter).
• For AirBnB and Uber it’s the ratings that other users have given me that’s important, which isn’t data I obviously ‘own’.

Yes, some of this can be self-asserted, but organisations often want objective data based on behaviour and decisions made about us not what we say is true. Mortgage brokers don’t just want my assertion that I have income, they want proof.

This means that Solid’s use cases will be limited unless it partners with institutions like banks and governments to assert and verify such data. Luckily there are standards being developed in the W3C to facilitate this, but we still need good frameworks and incentives for why such institutions will spend the time/energy to share and verify data about us, how this happens securely and how GDPR requirements are met.

2. If we narrow the market, the value proposition is hard

Putting aside verified claims, we then have the potential market of apps or services which only need self created data, preferences or quantified self data. This could be my calendar, todo list, journal entries, emails, messages, Apple/Google health app stored data, Fitbit data, what websites I use, time spent online, and so on. This is still a major market, but one already well catered for.

What’s the offer to users?

I want to see user research that identifies real problems users have with the current status quo which Solid will solve well enough to overcome switching cost and inertia. Most privacy concerns are centered around Facebook — but people are not on Facebook because they lack alternatives. There are numerous well designed, encrypted, decentralised and privacy preserving, even blockchain-based, alternatives. However, your current social network isn’t portable and the value of Facebook and Twitter comes from the people using it. The way we tackle this is to push for regulation around open protocols, not by expecting everyone to switch.

So if we can’t sell privacy as a product in social media, we need evidence of where else these priorities will bring users. Alternatively, decentralised or PDS-integrated tech must deliver novel and valued functionality or be solving major problems users have with existing centralised solutions.

What’s the offer to companies and app developers?

For companies, service providers and app developers the value proposition is hazy. I have yet to come across a PDS provider with an impressive or long list of partners and companies. Most existing business models depend on controlling the data and using it to improve a service and provide valuable analytics to up-sell paid plans or directly monetise the data collected through advertisers and third party data marketplaces. Giving this up requires incentives or regulation.

If Solid uptake is big enough to attract app developers, what stops the same data exploitation happening, albeit now with an extra step where the user is asked for ‘permission’ to access and use their data in exchange for a free or better service? Consent is only meaningful if there are genuine alternatives and as an industry we have yet to tackle this problem (see how Facebook, Apple, Google, Amazon ask for ‘consent’). What’s really going on when users are asked to agree to the terms and conditions of software on a phone they’ve already bought that won’t work otherwise? Or agreeing to Facebook’s data selling if there’s no other way for users to invite friends to events, message them or see their photos if those friends are Facebook users? I wouldn’t call this consent.

The answer may lie in partnering with civic or NGO organisations that have different incentives, but many users. Organisations like the BBC, governments, local authorities, the charity sector, and even financial organisations like Funding Circle and other peer-to-peer lenders. This is a worthwhile avenue to explore, but it doesn’t feel enough.

Alternative approaches

It’s time to challenge the standard economic approach when it comes to digital. The economies of scale are fundamentally different and we need bold new frameworks to ensure that technology benefits and protects everyone in society. Governments could and should invest in open infrastructure so that the basics of communicating online or connecting with people, cannot be ‘owned’ by companies, but is a shared basis like the internet or email protocol.

I’m thrilled Tim is pushing forward with Solid, but we need to be thinking bigger. Let’s start tackling the broader challenges and opportunities for a decentralised web to deliver a better ecosystem for all. Solid and similar projects need user research, user centered design, marketing and coordination to ensure interoperability and a user experience that can compete with the status quo. Common authentication and authorisation standards for digital identity and login and communication standards that work across applications and services will help break down silos and create real benefits to users and companies to motivate the move away from digital monopolies. It’s time to push for serious funding and resources into such public infrastructure to create an internet and web that works for everyone, just like Tim’s original vision.

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The following texts are taken from Algorithm Observatory’s Website.

Why this project is necessary

We know that social computing algorithms are used to categorize us, but the way they do so is not always transparent. To take just one example, ProPublica recently uncovered that Facebook allows housing advertisers to exclude users by race.

Even so, there are no simple and accessible resources for us, the public, to study algorithms empirically, and to engage critically with the technologies that are shaping our daily lives in such profound ways.

That is why we created Algorithm Observatory.

Part media literacy project and part citizen experiment, the goal of Algorithm Observatory is to provide a collaborative online lab for the study of social computing algorithms. The data collected through this site is analyzed to compare how a particular algorithm handles data differently depending on the characteristics of users.

Algorithm Observatory is a work in progress. This prototype only allows users to explore Facebook advertising algorithms, and the functionality is limited. We are currently looking for funding to realize the project’s full potential: to allow anyone to study any social computing algorithm.

Who we are

This project was conceived and is currently being developed by Dr. Ulises Mejias, Associate Professor at SUNY Oswego.

Initial funding for the prototype was generously provided by LINGOs/Humentum.

Holly Reitmeier is research assistant. Tahira Abdo is project assistant.

We would also like to thank students in Prof. Mejias’ BRC 421/521 and HON 301 classes for helping us test the prototype.

Who can use our data

Data generated through this site (ie., data included in the Results page) is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International license. You can use it on any reports or projects that you want, but please cite Algorithm Observatory as the source.

Our future plans

This is a prototype, which only begins to showcase the things that Algorithm Observatory will be able to do in the future.

Eventually, the website will allow anyone to design an experiment involving a social computing algorithm. The platform will allow researchers to recruit volunteer participants, who will be able to contribute content to the site securely and anonymously. Researchers will then be able to conduct an analysis to compare how the algorithm handles users differently depending on individual characteristics. The results will be shared by publishing a report evaluating the social impact of the algorithm. All data and reports will become publicly available and open for comments and reviews. Researchers will be able to study any algorithm, because the site does not require direct access to the source code, but relies instead on empirical observation of the interaction between the algorithm and volunteer participants.

We are currently seeking funding to develop the full version of the project.

Contact us

For more information, please email info@algorithmobservatory.com.

Intentionally, we do not have any social media accounts.

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Adrian Smith: Residents living around Plaça del Sol joke that theirs is the only square where, despite the name, rain is preferable. Rain means fewer people gather to socialise and drink, reducing noise for the flats overlooking the square. Residents know this with considerable precision because they’ve developed a digital platform for measuring noise levels and mobilising action. I was told the joke by Remei, one of the residents who, with her ‘citizen scientist’ neighbours, are challenging assumptions about Big Data and the Smart City.

The Smart City and data sovereignty

The Smart City is an alluring prospect for many city leaders. Even if you haven’t heard of it, you may have already joined in by looking up bus movements on your phone, accessing Council services online or learning about air contamination levels. By inserting sensors across city infrastructures and creating new data sources – including citizens via their mobile devices – Smart City managers can apply Big Data analysis to monitor and anticipate urban phenomena in new ways, and, so the argument goes, efficiently manage urban activity for the benefit of ‘smart citizens’.

Barcelona has been a pioneering Smart City. The Council’s business partners have been installing sensors and opening data platforms for years. Not everyone is comfortable with this technocratic turn. After Ada Colau was elected Mayor on a mandate of democratising the city and putting citizens centre-stage, digital policy has sought to go ‘beyond the Smart City’. Chief Technology Officer Francesca Bria is opening digital platforms to greater citizen participation and oversight. Worried that the city’s knowledge was being ceded to tech vendors, the Council now promotes technological sovereignty.

On the surface, the noise project in Plaça del Sol is an example of such sovereignty. It even features in Council presentations. Look more deeply, however, and it becomes apparent that neighbourhood activists are really appropriating new technologies into the old-fashioned politics of community development.

Community developments

Plaça de Sol has always been a meeting place. But as the neighbourhood of Gràcia has changed, so the intensity and character of socialising in the square has altered. More bars, restaurants, hotels, tourists and youngsters have arrived, and Plaça del Sol’s long-standing position as venue for large, noisy groups drinking late into the night has become more entrenched. For years, resident complaints to the Council fell on deaf ears. For the Council, Gràcia signified an open, welcoming city and leisure economy. Residents I spoke with were proud of their vibrant neighbourhood. But they recalled a more convivial square, with kids playing games and families and friends socialising. Visitors attracted by Gràcia’s atmosphere also contributed to it, but residents in Plaça del Sol felt this had become a nuisance. It is a story familiar to many cities. Much urban politics turns on the negotiation of convivial uses of space.

What made Plaça del Sol stand out can be traced to a group of technology activists who got in touch with residents early in 2017. The activists were seeking participants in their project called Making Sense, which sought to resurrect a struggling ‘Smart Citizen Kit’ for environmental monitoring. The idea was to provide residents with the tools to measure noise levels, compare them with officially permissible levels, and reduce noise in the square. More than 40 neighbours signed up and installed 25 sensors on balconies and inside apartments.

The neighbours had what project coordinator Mara Balestrini from Ideas for Change calls ‘a matter of concern’. The earlier Smart Citizen Kit had begun as a technological solution looking for a problem: a crowd-funded gadget for measuring pollution, whose data users could upload to a web-platform for comparison with information from other users. Early adopters found the technology trickier to install than developers had presumed. Even successful users stopped monitoring because there was little community purpose. A new approach was needed. Noise in Plaça del Sol provided a problem for this technology fix.

Through meetings and workshops residents learnt about noise monitoring, and, importantly, activists learnt how to make technology matter for residents. The noise data they generated, unsurprisingly, exceeded norms recommended by both the World Health Organisation and municipal guidelines. Residents were codifying something already known: their square is very noisy. However, in rendering their experience into data, these citizen scientists could also compare their experience with official noise levels, refer to scientific studies about health impacts, and correlate levels to different activities in the square during the day and night.

The project decided to compare their square with other places in the city. At this point, they discovered the Council’s Sentilo Smart City platform already included a noise monitor in their square. Officials had been monitoring noise but not publicising the open data. Presented with citizen data, officials initially challenged the competence of resident monitoring, even though official data confirmed a noise problem. But as Rosa, one of the residents, said to me, “This is my data. They cannot deny it”.

Thick data

Residents were learning that data is rarely neutral. The kinds of data gathered, the methods used, how it gets interpreted, what gets overlooked, the context in which it is generated, and by whom, and what to do as a result, are all choices that shape the facts of a matter. For experts building Big Data city platforms, one sensor in one square is simply a data point. On the other side of that point, however, are residents connecting that data to life in all its richness in their square. Anthropologist Clifford Geertz argued many years ago that situations can only be made meaningful through ‘thick description’. Applied to the Smart City, this means data cannot really be explained and used without understanding the contexts in which it arises and gets used. Data can only mobilise people and change things when it becomes thick with social meaning.

Noise data in Plaça del Sol was becoming thick with social meaning. Collective data gathering proved more potent than decibel levels alone: it was simultaneously mobilising people into changing the situation. Noise was no longer an individual problem, but a collective issue. And it was no longer just noise. The data project arose through face-to-face meetings in a physical workshop space. Importantly, this meant that neighbours got to know one another better, and had reasons for discussing life in the square when they bumped into one another.

Attention turned to solutions. A citizen assembly convened in the square one weekend publicised the campaign and discuss ideas with passers-by. Some people wanted the local police to impose fines on noisy drinkers, whereas others were wary of heavy-handed approaches. Some suggested installing a children’s playground. Architects helped locals examine material changes that could dampen sound.

The Council response has been cautious. New flowerbeds along one side of the square remove steps where groups used to sit and drink. Banners and community police officers remind people to respect the neighbourhood. The Council recently announced plans for a movable playground (whose occupation of the centre of the square can be removed for events, like the Festa Major de Gràcia). Residents will be able to monitor how these interventions change noise in the square. Their demands confront an established leisure economy. As local councillor Robert Soro explained to me, convivial uses have also to address the interests of bar owners, public space managers, tourism, commerce, and others. Beyond economic issues are questions of rights to public space, young peoples’ needs to socialise, neighbouring squares worried about displaced activity, the Council’s vision for Gràcia, and of course, the residents suffering the noise.

The politics beneath Smart City platforms

For the Council, technology activists, and residents of Plaça del Sol, data alone cannot solve their issues. Data cannot transcend the lively and contradictory social worlds that it measures. If data is to act then it needs ultimately to be brought back into those generative social contexts – which, as Jordi Giró at the Catalan Confederation of Neighbourhood Associations reminds us, means cultivating people skills and political capacity. Going beyond the Smart City demands something its technocratic efficiency is supposed to make redundant: investment in old-fashioned, street-level skills in community development. Technology vendors cannot sell such skills. They are cultivated through the kinds of community activism that first brought Ada Colau to prominence, and eventually into office.

Adrian Smith is Professor of Technology and Society at the Science Policy Research Unit at the University of Sussex, and Visiting Professor at the Centro de Innovación en Tecnología para el Desarrollo Humano at the Universidad Politécnica de Madrid. This blog comes from a European research project analysing the knowledge politics of smart urbanism. He is on Twitter as @smithadrianpaul

Reposted from The Guardian, with the permission of the author.

Image: Making Sense (Talking about noise in Plaça del Sol)

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For a sizable portion of the people running the established cooperatives in the United States, I’ve found, the internet is still regarded as a kind of alien invasion, an ever-bewildering source of trouble. Along with the hassle of building and maintaining a website, the internet has brought new competitors—especially venture-backed startups that love nothing more than to disrupt the kinds of intermediary roles in value chains where co-ops have held niches for decades. And many co-ops seem stuck playing catch-up. They buy the latest software and hire expensive consultants, but it’s never quite enough. The disruptions keep coming.

Playing catch-up is never the role co-ops are best suited for, anyway. They’re at their best when they’re doing another kind of business—when they’re finding value that investors don’t see, when they’re meeting needs that Wall Street doesn’t bother figuring out how to meet.

This is what a new generation of cooperative entrepreneurs is doing. I’d like to introduce you to some of them, and to some of the ways that they’re doing better than catching up to the internet of venture capitalists and aspiring monopolists. They’re letting co-op values and principles guide them to a vision for a different kind of internet economy. As they do, they’re also rediscovering the competitive advantages of cooperation—old strategies, really, that powered this model in generations past but that can be too easily forgotten.

First, take a foray with me into the mind of one of our eminent internet overlords. Consider it a survey of the terrain.

In February 2017, as Facebook CEO Mark Zuckerberg was still coming to terms with the previous year’s election cycle, he published a post called “Building Global Community,” a manifesto of sorts. “In the last year,” he wrote, “the complexity of the issues we’ve seen has outstripped our existing processes for governing the community.” Then he admitted, remarkably, that he couldn’t rule a platform shared by billions of human beings out of the wisdom of his own head.

And so he called for something that sounds almost like democracy: “Building an inclusive global community requires establishing a new process for citizens worldwide to participate in community governance. I hope that we can explore examples of how collective decision-making might work at scale.”

As autocracy and oligarchy run aground, he reluctantly falls back on democracy, then announces it as if it were the latest software update. Should we or should we not tell him that cooperatives have been practicing forms of “collective decision-making at scale” for a long, long time? Perhaps they have something to teach him. Perhaps they can do what Facebook’s investor-owners can’t.

Business model innovation

The designers of the internet didn’t set out to build infrastructure for cat-meme-sharing on social-media monopolies. Paul Baran, who conceived of the “packet switching” system by which the cat memes and all else travel from server to server, was concerned about a Soviet missile attack. In the 1960s, Baran worked for the RAND Corporation, which was helping to build the military communications tool that would later evolve into the civilian internet. The system relied on a complex collaboration among peers to avoid any single, vulnerable point of failure.

Radically centralized systems like Facebook are a departure from the network’s underlying structure. They arose not for technical reasons but economic ones—to deliver the profits that early investors demanded. Centralizing Baran’s distributed scheme has been a gradual, expensive process. Much more akin to the internet’s design are standards-setting organizations like the World Wide Web Consortium, which balance the needs of diverse stakeholders. The internet, like a co-op, is built for federation.

Over and over, we have seen old, cooperative practices imitated online. Take the wonders of crowdfunding, which enable businesses and products to launch without the need for loans or profit-seeking investors; well, co-ops were the original crowdfunding. When people needed something the market wasn’t furnishing, they pooled their money and built a cooperative to provide it. And they got more than one gets in the usual Kickstarter: real ownership and accountability. Around half of U.S. households have an Amazon Prime membership, which delivers convenience to customers and loyalty to the company—but, again, without shared ownership and accountability to back it up. The internet giants are getting by with a pale imitation of what co-ops have in their bones.

The technology has added something new, however. When we talk about the online economy, we’re not just talking about slapping websites on existing business models. The real disruptions have been bigger than e-commerce; they’re happening through platforms. Platforms are a kind of business model that the internet has supercharged: multi-sided markets that generate value through interactions among users, not just through what the company provides to them. The canonical and over-used examples are platforms like Airbnb, the hotel chain that owns no hotels, and Uber, the taxi company that owns no cars.

Once again, cooperatives got to it first. When rural electric co-ops were forming across the U.S. in the 1940s, they depended on their members’ collaboration and sweat equity to build a shared asset. Marketing co-ops have enabled independent producers to set the terms on which they sell and even compete. For decades, Italian “social co-ops” have maintained balanced markets between care providers and patients who co-own their companies together.

With age, however, many co-ops have conformed themselves to the business models of their corporate competitors. They’ve come to focus on the value the co-op can deliver to members, not on the unpredictable interconnections it might facilitate. It’s service more than sharing. The rise of online platforms thus presents itself as a terrifying disruption, when it should be an opportunity for co-ops to take the lead.

The investor-owned platforms have been ambivalent creatures. In come Amazon’s conveniences, and out go the local retailers that co-ops enabled to thrive. In come flexible schedules on gig platforms like TaskRabbit, and out go protections and benefits that workers have fought for centuries to achieve. Inequality and conglomeration accelerate. And there’s no going back; the perks are too irresistible. But what if co-ops could face those disruptions on their own terms, with their own strengths? What if they invested in a new generation of cooperative innovation instead?

Silicon Valley likes to have us believe that innovation is the purview of its investor-driven formula. But when you look at a lot of the most successful companies there, they didn’t begin with a miraculous invention. From the GPS behind Uber to Google’s original search algorithm, the tech often comes from publicly funded research in government and universities. The Silicon Valley magic, more often, lies in spinning up a seamless interface and the means to monetize it.

According to Fred Wilson, a renowned investor at Union Square Ventures, “Business model innovation is more disruptive than technological innovation.” What innovations can the co-op model deliver?

The rise of platform cooperativism

I’ve been dwelling in abstractions so far, and please forgive me for that, because what I’m talking about is not an abstraction at all. I came to notice the potential that cooperative business might have for reinventing the online economy not through theoretical reflection but, as a reporter, by noticing how people were already making it happen.

Starting around 2014, hiding behind the fanfare and controversy surrounding “sharing economy” platforms like Airbnb and Uber, I began coming across startups that were trying to build a real sharing economy. This usually meant adopting cooperative models. They were working in isolation, not aware of one another, with little in the way of mentoring or co-op-friendly financing to support them. But there they were. By the end of that year, I was publishing about what I’d found, and one of my sources, the New School media professor Trebor Scholz, put a name to it all: “platform cooperativism.” The following year, we organized the first conference on the subject in New York, and more than a thousand people came. Even The Washington Post called it “a huge success.” Something real was indeed afoot.

At first, we had the idea that we could simply copy the Ubers and Airbnbs of the world, slap a co-op label on, and the world would switch over. But the more I’ve watched this platform co-op ecosystem grow, the more I get excited about how cooperation allows these businesses to do things differently. Cooperative ownership isn’t just some add-on mutation, it’s another sort of genome.

Quality, not monopoly

One of the earliest, most successful platform co-ops is Stocksy United, a Canadian stock photo platform owned by its photographers and employees. Its founders were executives for a much bigger platform who concluded investor-ownership was stiffing the photographers and hurting the quality of their work. The founders realized that if they made their startup accountable to its photographers, they could prioritize quality. After just a few years, the company is thriving in a crowded industry.

Stocksy also breaks a cardinal rule for tech startups. You’re supposed to achieve scale at all costs, but the thousand-or-so photographer-owners have been cautious about accelerating their growth. They don’t want to dilute what they offer. They’re growing, but only at their own pace and far slower than they could. They’re making their own rules.

Control over what’s ours

It has become an implicit social contract of life online that—in exchange for useful services like Gmail and Uber—we give up heaps of data about ourselves to who-knows-who for who-knows-what. But for platform co-ops, this trade-off tends to disappear. Users really can be the owners of their data from start to finish. There’s no more need for all the funny business hidden in the legalese no one reads.

MIDATA, for instance, is a Swiss co-op for personal medical data funded through the voluntary use of that data for medical research. Users get a convenient repository over which they have full control. Savvy Cooperative, based in New York, is a platform where medical researchers and startups can benefit from the data of patient feedback—on the patients’ terms, because the patients are the owners. Farmers are doing something similar through the Grower Information Services Cooperative, which allows them to benefit from the data their ever-more computerized machines produce without relinquishing it to third parties.

Federation not centralization

Social.coop brings that kind of user control to social media. It is a small experiment that operates an open-source alternative to Twitter called Mastodon—a federated system in which people can keep their data with a provider they know and trust, while still interacting with the wider network. Federated social networks like this are great for privacy, and the technology has been around for a while. They’ve just lacked a business model, since investors have so much to gain from highly centralized networks. Co-ops might be uniquely suited to change that.

Social.coop is unusual in other ways. It’s not legally incorporated; instead, it operates through Open Collective, a co-op-friendly platform that enables groups of people anywhere to collect money and distribute it without their own bank account. Accounting on Open Collective is public, for all to see and inspect. Social.coop members make decisions about how to use those resources and more on Loomio, a decision-making platform built by a New Zealand-based worker co-op. Most of them—well, us—have never met each other in person. We’ve built the trust we need to cooperate through transparency.

Trust on a trustless network

When the Bitcoin digital currency system first appeared in 2009, it promised the possibility of “trustless,” pseudonymous transactions over a network that would rely on no central authorities, like Visa or the Federal Reserve. Companies like Goldman Sachs and Walmart are now adopting the underlying “blockchain” technology. So are credit unions. A project called CU Ledger uses blockchain technology to better manage, secure and share data about credit union members’ identities. The credit unions, that is, are applying Bitcoin’s software to purposes nearly opposite from what others have in mind: to build on institutional trust and to better collaborate.

As the blockchain economy grows, co-ops may be poised to play a vital role. RChain, for instance, is built on a supposition that the co-op model can solve some of the technical bottlenecks that Bitcoin and its cousins have faced. In Berlin, Seedbloom puts the co-ownership back into crowdfunding with blockchains. Already, it has aided the development of Resonate, a music-streaming cooperative co-owned, over its own blockchain, by fans and musicians alike. Moeda, starting in Brazil, is a co-op that uses blockchains to help credit unions expand financial inclusion and to finance its own growth.

Venture capital as cooperative bank

For this platform co-op ecosystem to grow, it will have to develop its own means of financing, just as co-op sectors of the past have done. Already we’ve started to see developments like Purpose Ventures, a new fund designed to grow long-term with its startups, not to sell them off for a quick buck. It’s co-op compatible; in some respects it even resembles an old-fashioned cooperative bank.

The old and the new come together. They converge. And they need each other. One of the most important developments in recent years has been to see co-op veterans start to embrace and support this new generation.

This has been done before

The conditions that have given rise to cooperation in the past are appearing in new guises—workers barely getting by on gig platforms, or customers not sure whether they can trust the companies they nonetheless rely on. It’s not enough for co-ops to tack websites on existing business models. We need co-op business models designed in and for a networked world.

I must confess, however: When I’m in a room full of leaders in big, established co-ops, I’m not sure these kinds of innovations will come from them. I bet most of them would agree. But what we need isn’t coming from the small, experimental platform co-ops I’ve mentioned either. They’re not enough. We need both. We need experienced co-op mentors stepping in to support the new, risk-taking co-op entrepreneurs who will help keep this sector vibrant.

How can that happen? First, it needs to be easier for startups to see the co-op model as a viable option—with tech-oriented co-op incubators and seed capital, as well as outreach to existing startup communities. Second, established co-ops can find ways to pool their funds to invest in promising new co-ops, then share dividends back to their members. Finally, we need to identify the financing and policy tools to help existing platforms that should be co-op converts. Too many online platforms we depend on are stuck trying to meet investor demands when they should instead be accountable to their users.

I’m a reporter, so I don’t like to make predictions. But based on the experiments out there, I’ve noticed some patterns that may become more common in the co-ops to come.

They will create value not just with the services they offer to members, but with the connections they enable among members—and the efficiencies members discover together. Their specialty will be in fostering trust on trustless networks, federating local communities across the globe. And they will build on the long cooperative legacy with forms of online governance that are more transparent than both the competition and co-ops past.

Open software and open data could help co-ops cooperative with each other more deeply than ever. Open supply-chains could display, for potential customers to see, their commitment to the highest quality sourcing. If they’re doing their jobs right, greater transparency will only make the cooperative difference more evident. And that difference matters.

I meet more and more people all the time who are warming to the co-op idea—and not because they’ve already worked for co-ops or studied co-op history. For the most part, they haven’t. A cooperative internet might seem utopian, but they hope for it anyway.

I don’t think it is so far-fetched. Cooperatives brought electricity to rural America when no one else would, and they’ve given Main Street a fighting chance against the big boxes. They help millions buy homes. They pioneered the local, organic revival and the means of delivering fair-trade products from across the planet. Next, the internet. We have done this already, and we can do it again, even better than before.

Photo by Pat Guiney

The post Next, the Internet: Building a Cooperative Digital Space appeared first on P2P Foundation.

I left Facebook in 2013, less for my own sake than for what my presence on the service was doing to others. I knew that anyone who “liked” my page could have their data harvested in ways they wouldn’t necessarily approve.

Over the past five years, people have not only become aware of this devil’s bargain but accepted it as the internet’s price of admission.”So what if they have my data,” I saw a graduate student ask her professor this week. “Why is my privacy so important?”

Bully for you if you don’t care what Facebook’s algorithms know about your sex life or health history, but that’s not the real threat. Neither Facebook nor the marketers buying your data particularly care about what you do with your clothes off, whom you’re cheating with or any other sordid details you may find embarrassing.

That’s the great fiction of social media: That you matter as a person. You don’t.

The platform cares only about your metadata, from which they can construct a psychological profile and then manipulate your behavior. They have been using and selling even the stuff you thought you were sharing confidentially with your friends in order to identify your neuroses and neurotic vulnerabilities and leverage them against you.

That’s what Facebook markets to its customers. The company has been doing it ever since its investors realized that, as owners of a mere social network, they would become only multi-millionaires; to become billionaires, they’d have to offer something more than our attention to ads. So they sold access to our brain stem.

With 2.2 billion active users, Facebook knew it had a big-data gold mine. While we’ve been busily shielding what we think of as our “personal” data, Facebook has been analyzing the stuff we think doesn’t matter: our clicks, likes and posts, as well as the frequency with which we make them. Looking at this metadata, Facebook, its psychologists and its clients put us into different psychographic “buckets.”

That’s how they came to be able to predict, with about 80% accuracy, our future behaviors, including whether we’re going to go on a diet, vote for a particular candidate or announce a change in sexual orientation. From there, the challenge is to compel the lagging 20% to fall in line — to get all the people who should be going on a diet or voting for a particular candidate to conform to what the algorithms have predicted.

That’s where companies like Cambridge Analytica come in. They paid thousands of people to take psychology tests and to surrender their own and their friends’ Facebook data. Then they compared all this data to infer how each of us would have answered that psychology test. Armed with our real or algorithmically determined psychological profiles, Cambridge Analytica surmised our individual neurotic makeups. And they figured out how to terrify each and every one of us.

That’s the greater collateral damage of social media. It’s not simply that they can get us to buy a particular product or vote for one candidate or another. It’s that their techniques bypass our higher brain functions. They use imagery and language specifically designed to evade our logic and empathy and appeal straight to our reptilian survival instincts.

These more primitive brain regions respond only to primitive stimulus: fear, hate and tribalism. It’s the part of us that gets activated when we see a car crash or a horror movie. That’s the state of mind these platforms want us to be in, because that’s when we are most easily manipulated.

Yes, we’ve been manipulated by ads for a century now. But TV and other forms of advertising generally happened in public. We all saw the same commercials, and they often cost so much that companies knew they had to get them right. Television networks would themselves censor ads that they felt would alienate their viewers or make fraudulent claims. It was manipulative, but for the most part, consumer advertising was aspirational.

Facebook figures out who or what each of us fears most, and then sells that information to the creators of false memes and the like, who deliver those fears directly to our news feeds. This, in turn, makes the world a more fearful, hostile and dangerous place.

To ask why one should care is a luxury of privilege. Data harvesting arguably matters most when it’s used against the economically disadvantaged. It’s not just in China that social media data are used to evaluate credit worthiness and immigration status. By normalizing the harvesting of data, those of us with little to fear imperil the most vulnerable.

When Mark Zuckerberg started Facebook, a friend of his expressed surprise that people were surrendering so much personal data to the platform. “I don’t know why,” Zuckerberg said. “They trust me. Dumb …”

We may have been dumb to trust Facebook with our data in the first place. Now we know they’ve been using the data to make us even dumber.

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What is data philanthropy?

There are a number of competing definitions, but we take ‘data philanthropy’ to mean:

• an informed contribution of data to a trusted vehicle by an individual data subject for mutual benefit; or
• an informed contribution of data to a trusted vehicle by an individual data subject for public benefit; or
• a data/data insight donation to a trusted vehicle on the part of a corporate entity – allowing it to “give back in a way that produces meaningful impact and reflecting the businesses’ core competencies, while preserving or expanding value for shareholders” (Stempeck, 2014).

It reads across, then, to distinct forms of ‘trusted vehicle’ that are designed to harness ‘data for good’ – which, for our purposes, means facilitating research and innovation to transform health and care outcomes.

In our report, we explored member-controlled ‘data cooperatives’ and ‘data communities’ operated by trusted intermediaries to facilitate data philanthropy on the part of individuals – in recognition of MiData Coop initiative in Switzerland and the success of the UK Biobank. We also looked at what are commonly referred to as ‘data collaboratives’, which involve private sector organisations donating and/or analysing the data they control, to explore data philanthropy on the part of corporate entities. Here, notable examples include private enterprises supporting the UN Global Pulse initiative and Strava Metro. Ultimately, we believe a range of ‘trusted vehicles’ that reflect the values of different individuals and corporate entities could usefully be established to further research and create the conditions for innovation with the aim of transforming health and care outcomes.

Why promote data philanthropy for health and care?

We welcome the introduction of provisions to the Data Protection Bill that are designed to facilitate peer-to-peer support amongst groups characterised by particular conditions and/or disabilities. However, there is otherwise a manifest lack of provision to underpin collective action for mutual and/or public benefit in the Bill, and we have recommended the Government considers introducing measures to promote and/or facilitate ‘data philanthropy’ for the following reasons:

• Trust: there is already considerable support for ‘data philanthropy’ on the part of the general public where the aim is to further research in relation to health and care, but we believe the Data Protection Bill could function to proactively build trust by affording data subjects concrete opportunities to take a digital stake in society – in accordance with their values and irrespective of their socio-economic status. The Bill could also do more to recognise the role that businesses can play in stewarding well-being, by championing bespoke permissions and ‘trusted vehicles’ in relation to the re-use of privately controlled data for public benefit. It would then better reflect the UK Digital Strategy, which states that Government will ‘encourage innovative uses of data by making it easier, where possible, to access and use data held by both government and businesses’ (DCMS, 2017).
• Size: whilst the UK benefits from unique health data sets which are of interest to researchers right around the world, most real-time data capable of indicating a person’s wellbeing (or otherwise) is currently vested in privately controlled and siloed data repositories. Moreover, the larger a dataset is, the more valuable it becomes – in particular, where machine learning and the development of Artificial Intelligence is concerned. Measures to promote and/or facilitate ‘data philanthropy’, both on the part of individuals and corporate entities, could serve to grow the overall quantum of data made available for research and innovation in relation to wellbeing and, with that, enhance the UK’s competitive edge in relation to comparable endeavours being pursued by countries that benefit from comparatively larger populations.
• Quality and Scope: increasing the size of a dataset generally allows for extracting greater value from it, but this might not happen if ‘trusted vehicles’ are left to deal with low quality data [Carballa Smichowski, 2018]. Moreover, the capacity to link several datasets and the capacity to use a single dataset for several purposes render it more valuable still, because they increase the possibility of making good ‘descriptions, explanations, predictions and prescriptions’ [Chignard & Benyayer, 2015]. Therefore, whilst the Data Protection Bill and GDPR provide for individual Subject Access Requests and enhancements to ‘data portability’, the quality and scope of data that a ‘trusted vehicle’ might attract in promoting a standalone opportunity for ‘data philanthropy’ to individuals – on the basis of ‘explicit consent’ and in the absence of legal assurances and/or open standards and APIs – is questionable. A Government-backed data donor bank or data donation scheme could help to overcome these critically important issues.

Ultimately, our rationale for championing ‘data philanthropy’ and ‘trusted vehicles’ flows from our aspiration to effect a step-change in health and care outcomes in the UK. If we are able to harness Voice Assistant data from Alexa and kindred devices for the purposes of conducting research, might we be in a position to identify and better support people struggling with early onset dementia or mental ill-health at an earlier stage? If we increase access to the loyalty card scheme data currently collected by retailers for marketing purposes, might we be better placed to devise new interventions with which to help tackle obesity?

The possibilities are seemingly endless but are less likely to be realised – unless we empower individuals and businesses to play an active role in stewarding well-being in our digital age.

Practical Steps to Enable Data Philanthropy

In our report, we made a number of recommendations about promoting and enabling ‘data philanthropy’, and the Government could take practical steps to introduce them in the course of the Data Protection Bill’s passage through Parliament:

• It may be appropriate, for example, to introduce a ‘duty to review provisions for data philanthropy’upon the Secretary of State for DCMS. Alternatively, the Government could simply expand the opportunities for data subjects to contribute data to electronic health and care records and other data sharing initiatives by introducing a ‘right to donate data to a third party to further research and innovation in health and care’ in the section of the Data Protection Bill concerning ‘rights of the data subject’.
• The Government could commit to explore the development of a ‘gift-aid’ style scheme for data so as to encourage and facilitate data donations to further research and innovation in health and care. The National Data Guardian could, for example, be required to investigate the circumstances in which it may be appropriate to invite the giving of explicit consent to the processing and pooling of personal data for the purposes of research and innovation in health or social care. Alternatively, the Government could add to provisions concerning Subject Access Requests and ‘data portability’ so as to mandate that businesses invite people to give their explicit consent to donate their data to a recognised third party in order to further research and innovation in health and care integral to soliciting consent in relation to their standard terms and conditions of service.
• The Government has welcomed our call to explore the development of ‘trusted data exchanges’ – most recently, in its endorsement of ‘Data and the Future of Health and Social Care’ [March, 2018]. It has also taken note of the issues raised by Baroness Neville-Jones during the Data Protection Bill’s Second Reading in the House of Lords – when she asked the Government to “think about the possibility that they should allow for the creation of governance and accountability regimes that will fit special circumstances” – adding that “the existence of the Information Commissioner should not result just in enforcing the law effectively and well; it should provide an opportunity for creativity under her auspices and the ability to create variations on governance regimes where they are needed”.

We support this sentiment and provisions that would further support the creation of ‘trusted data exchanges’ for health and care, underpinned by ‘data philanthropy’ and creative approaches to lawful consent. The Government could, however, go further and introduce provisions for ‘trusted data exchanges’ to be recognised in law as not-for-private-profit vehicles designed to safeguard data donated for the purposes of research and innovation in health and care. This would constitute a bold move and attest to the Government’s ambition to support the evolution of public, private and third sector organisations alike in the digital age. In particular, it would recognise that we currently lack a legal vehicle which benefits from the digital equivalent of the tangible ‘asset locks’ that are applicable to established charities.

There is, then, considerable scope for the Government to take action to better enable data philanthropy in the interests of transforming health and care outcomes – and there is, perhaps, no better time than at present.

REFERENCES

Carballa Smichowski, B. (2018) The value of data: an analysis of closed-urban-data-based and open-data-based business models. Available from: https://www.sciencespo.fr/ecole-urbaine/sites/sciencespo.fr.ecole-urbaine/files/2018_01%20-%20Carballa.pdf 

Chignard, S., & Benyayer, L.-D. (2015) Datanomics. Les nouveaux business models des données. FYP editions.

Department for Digital, Media, Culture and Sport (DCMS) (2017) UK Digital Strategy 2017, [online]. Available from: https://www.gov.uk/government/publications/uk-digital-strategy/uk-digital-strategy

Stempeck, M. (2014) Sharing data is a form of corporate philanthropy. Harvard Business Review, 24 July 2014, [online]. Available from https://hbr.org/2014/07/sharing-data-is-a-form-of-corporatephilanthropy

Woods, T., & Kihlstrom, E. (2018) Data and the Future of Health and Social Care. Future Health Collective, March 2018 [online]. Available from: https://www.colliderhealth.com/future-health-collective/

Reposted from Future Care Capital

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