Tag: economics

Exploring the Darknet in Five Easy Questions

Many people are probably aware of something called “the darknet” (also sometimes called the “dark web”) or might have a vague notion of what it might be. However, many probably don’t know much about the global flows of drugs, weapons, and other illicit items traded on darknet marketplaces like AlphaBay and Hansa, the two large marketplaces that were recently shut down by the FBI, DEA and Dutch National Police.

We caught up with Martin Dittus, a data scientist working with Mark Graham and Joss Wright on the OII’s darknet mapping project, to find out some basics about darknet markets, and why they’re interesting to study.

Firstly: what actually is the darknet?

Martin: The darknet is simply a part of the Internet you access using anonymising technology, so you can visit websites without being easily observed. This allows you to provide (or access) services online that can’t be tracked easily by your ISP or law enforcement. There are actually many ways in which you can visit the darknet, and it’s not technically hard. The most popular anonymising technology is probably Tor. The Tor browser functions just like Chrome, Internet Explorer or Firefox: it’s a piece of software you install on your machine to then open websites. It might be a bit of a challenge to know which websites you can then visit (you won’t find them on Google), but there are darknet search engines, and community platforms that talk about it.

The term ‘darknet’ is perhaps a little bit misleading, in that a lot of these activities are not as hidden as you might think: it’s inconvenient to access, and it’s anonymising, but it’s not completely hidden from the public eye. Once you’re using Tor, you can see any information displayed on darknet websites, just like you would on the regular internet. It is also important to state that this anonymisation technology is entirely legal. I would personally even argue that such tools are important for democratic societies: in a time where technology allows pervasive surveillance by your government, ISP, or employer, it is important to have digital spaces where people can communicate freely.

And is this also true for the marketplaces you study on the darknet?

Martin: Definitely not! Darknet marketplaces are typically set up to engage in the trading of illicit products and services, and as a result are considered criminal in most jurisdictions. These market platforms use darknet technology to provide a layer of anonymity for the participating vendors and buyers, on websites ranging from smaller single-vendor sites to large trading platforms. In our research, we are interested in the larger marketplaces, these are comparable to Amazon or eBay — platforms which allow many individuals to offer and access a variety of products and services.

The first darknet market platform to acquire some prominence and public reporting was the Silk Road — between 2011 and 2013, it attracted hundreds of millions of dollars worth of bitcoin-based transactions, before being shut down by the FBI. Since then, many new markets have been launched, shut down, and replaced by others… Despite the size of such markets, relatively little is known about the economic geographies of the illegal economic activities they host. This is what we are investigating at the Oxford Internet Institute.

And what do you mean by “economic geography”?

Martin: Economic geography tries to understand why certain economic activity happens in some places, but not others. In our case, we might ask where heroin dealers on darknet markets are geographically located, or where in the world illicit weapon dealers tend to offer their goods. We think this is an interesting question to ask for two reasons. First, because it connects to a wide range of societal concerns, including drug policy and public health. Observing these markets allows us to establish an evidence base to better understand a range of societal concerns, for example by tracing the global distribution of certain emergent practices. Second, it falls within our larger research interest of internet geography, where we try to understand the ways in which the internet is a localised medium, and not just a global one as is commonly assumed.

So how do you go about studying something that’s hidden?

Martin: While the strong anonymity on darknet markets makes it difficult to collect data about the geography of actual consumption, there is a large amount of data available about the offered goods and services themselves. These marketplaces are highly structured — just like Amazon there’s a catalogue of products, every product has a title, a price, and a vendor who you can contact if you have questions. Additionally, public customer reviews allow us to infer trading volumes for each product. All these things are made visible, because these markets seek to attract customers. This allows us to observe large-scale trading activity involving hundreds of thousands of products and services.

Almost paradoxically, these “hidden” dark markets allow us to make visible something that happens at a societal level that otherwise could be very hard to research. By comparison, studying the distribution of illicit street drugs would involve the painstaking investigative work of speaking to individuals and slowly trying to acquire the knowledge of what is on offer and what kind of trading activity takes place; on the darknet it’s all right there. There are of course caveats: for example, many markets allow hidden listings, which means we don’t know if we’re looking at all the activity. Also, some markets are more secretive than others. Our research is limited to platforms that are relatively open to the public.

Finally: will you be sharing some of the data you’re collecting?

Martin: This is definitely our intention! We have been scraping the largest marketplaces, and are now building a reusable dataset with geographic information at the country level. Initially, this will be used to support some of our own studies. We are currently mapping, visualizing, and analysing the data, building a fairly comprehensive picture of darknet market trades. It is also important for us to state that we’re not collecting detailed consumption profiles of participating individuals (not that we could). We are independent academic researchers, and work neither with law enforcement, nor with platform providers.

Primarily, we are interested in the activity as a large-scale global phenomenon, and for this purpose, it is sufficient to look at trading data in the aggregate. We’re interested in scenarios that might allow us to observe and think about particular societal concerns, and then measure the practices around those concerns in ways that are quite unusual, that otherwise would be very challenging. Ultimately, we would like to find ways of opening up the data to other researchers, and to the wider public. There are a number of practical questions attached to this, and the specific details are yet to be decided — so stay tuned!

Martin Dittus is a researcher and data scientist at the Oxford Internet Institute, where he studies the economic geography of darknet marketplaces. More: @dekstop

Follow the project here: https://www.oii.ox.ac.uk/research/projects/economic-geog-darknet/

Twitter: @OiiDarknet

 

Further reading (academic):

Further reading (popular):

Martin Dittus was talking to OII Managing Editor David Sutcliffe.

Digital platforms are governing systems — so it’s time we examined them in more detail

Digital platforms are not just software-based media, they are governing systems that control, interact, and accumulate. As surfaces on which social action takes place, digital platforms mediate — and to a considerable extent, dictate — economic relationships and social action. By automating market exchanges they solidify relationships into material infrastructure, lend a degree of immutability and traceability to engagements, and render what previously would have been informal exchanges into much more formalized rules.

In his Policy & Internet article “Platform Logic: An Interdisciplinary Approach to the Platform-based Economy“, Jonas Andersson Schwarz argues that digital platforms enact a twofold logic of micro-level technocentric control and macro-level geopolitical domination, while supporting a range of generative outcomes between the two levels. Technology isn’t ‘neutral’, and what designers want may clash with what users want: so it’s important that we take a multi-perspective view of the role of digital platforms in contemporary society. For example, if we only consider the technical, we’ll notice modularity, compatibility, compliance, flexibility, mutual subsistence, and cross-subsidization. By contrast, if we consider ownership and organizational control, we’ll observe issues of consolidation, privatization, enclosure, financialization and protectionism.

When focusing on local interactions (e.g. with users), the digital nature of platforms is seen to strongly determine structure; essentially representing an absolute or totalitarian form of control. When we focus on geopolitical power arrangements in the “platform society”, patterns can be observed that are worryingly suggestive of market dominance, colonization, and consolidation. Concerns have been expressed that these (overwhelmingly US-biased) platform giants are not only enacting hegemony, but are on a road to “usurpation through tech — a worry that these companies could grow so large and become so deeply entrenched in world economies that they could effectively make their own laws”.

We caught up with Jonas to discuss his findings:

Ed.: You say that there are lots of different ways of considering “platforms”: what (briefly) are some of these different approaches, and why should they be linked up a bit? Certainly the conference your paper was presented at (“IPP2016: The Platform Society”) seemed to have struck an incredibly rich seam in this topic, and I think showed the value of approaching an issue like digital platforms from multiple disciplinary angles.

Jonas: In my article I’ve chosen to exclusively theorize *digital* platforms, which of course narrows down the meaning of the concept, to begin with. There are different interpretations as for what actually constitutes a digital platform. There has to be an element of proprietary control over the surface on which interaction takes place, for example. While being ubiquitous digital tools, free software and open protocols need not necessarily be considered as platforms, while proprietary operating systems should.

Within contemporary media studies there is considerable divergence as to whether one should define so-called over-the-top streaming services as platforms or not. Netflix, for example: In a strict technical sense, it’s not a platform for self-publishing and sharing in the way that YouTube is—but, in an economic sense, Netflix definitely enacts a multi-sided market, which is one of the key components of a what a platform does, economically speaking. Since platforms crystallize economic relationships into material infrastructure, conceptual conflation of this kind is unavoidable—different scholars tend to put different emphasis on different things.

Hence, when it comes to normative concerns, there are numerous approaches, ranging from largely apolitical computer science and design management studies, brandishing a largely optimistic view where blithe conceptions of innovation and generativity are emphasized, to critical approaches in political economy, where things like market dominance and consolidation are emphasized.

In my article, I try to relate to both of these schools of thought, by noting that they each are normative — albeit in vastly different ways — and by noting that not only do they each have somewhat different focus, they actually bring different research objects to the table: Usually, “efficacy” in purely technical interaction design is something altogether different than “efficacy” in matters of societal power relations, for example. While both notions can be said to be true, their respective validity might differ, depending on which matter of concern we are dealing with in each respective inquiry.

Ed.: You note in your article that platforms have a “twofold logic of micro-level technocentric control and macro-level geopolitical domination” .. which sounds quite a lot like what government does. Do you think “platform as government” is a useful way to think about this, i.e. are there any analogies?

Jonas: Sure, especially if we understand how platforms enact governance in really quite rigid forms. Platforms literally transform market relations into infrastructure. Compared to informal or spontaneous social structures, where there’s a lot of elasticity and ambiguity — put simply, giving-and-taking — automated digital infrastructure operates by unambiguous implementations of computer code. As Lawrence Lessig and others have argued, the perhaps most dangerous aspect of this is when digital infrastructures implement highly centralized modes of governance, often literally only having one point of command-and-control. The platform owner flicks a switch, and then certain listings and settings are allowed or disallowed, and so on…

This should worry any liberal, since it is a mode of governance that is totalitarian by nature; it runs counter to any democratic, liberal notion of spontaneous, emergent civic action. Funnily, a lot of Silicon Valley ideology appears to be indebted to theorists like Friedrich von Hayek, who observed a calculative rationality emerging out of heterogeneous, spontaneous market activity — but at the same time, Hayek’s call to arms was in itself a reaction to central planning of the very kind that I think digital platforms, when designed in too rigid a way, risk erecting.

Ed.: Is there a sense (in hindsight) that these platforms are basically the logical outcome of the ruthless pursuit of market efficiency, i.e. enabled by digital technologies? But is there also a danger that they could lock out equitable development and innovation if they become too powerful (e.g. leading to worries about market concentration and anti-trust issues)? At one point you ask: “Why is society collectively acquiescing to this development?” .. why do you think that is?

Jonas: The governance aspect above rests on a kind of managerialist fantasy of perfect calculative rationality that is conferred upon the platform as an allegedly neutral agent or intermediary; scholars like Frank Pasquale have begun to unravel some of the rather dodgy ideology underpinning this informational idealism, or “dataism,” as José van Dijck calls it. However, it’s important to note how much of this risk for overly rigid structures comes down to sheer design implementation; I truly believe there is scope for more democratically adaptive, benign platforms, but that can only be achieved either through real incentives at the design stage (e.g. Wikipedia, and the ways in which its core business idea involves quality control by design), or through ex-post regulation, forcing platform owners to consider certain societally desirable consequences.

Ed.: A lot of this discussion seems to be based on control. Is there a general theory of “control” — i.e. are these companies creating systems of user management and control that follow similar conceptual / theoretical lines, or just doing “what seems right” to them in their own particular contexts?

Jonas: Down the stack, there is always a binary logic of control at play in any digital infrastructure. Still, on a higher level in the stack, as more complexity is added, we should expect to see more non-linear, adaptive functionality that can handle complexity and context. And where computational logic falls short, we should demand tolerable degrees of human moderation, more than there is now, to be sure. Regulators are going this way when it comes to things like Facebook and hate speech, and I think there is considerable consumer demand for it, as when disputes arise on Airbnb and similar markets.

Ed.: What do you think are the main worries with the way things are going with these mega-platforms, i.e. the things that policy-makers should hopefully be concentrating on, and looking out for?

Jonas: Policymakers are beginning to realize the unexpected synergies that big data gives rise to. As The Economist recently pointed out, once you control portable smartphones, you’ll have instant geopositioning data on a massive scale — you’ll want to own and control map services because you’ll then also have data on car traffic in real time, which means you’d be likely to have the transportation market cornered, self driving cars especially… If one takes an agnostic, heterodox view on companies like Alphabet, some of their far-flung projects actually begin to make sense, if synergy is taken into consideration. For automated systems, the more detailed the data becomes, the better the system will perform; vast pools of data get to act as protective moats.

One solution that The Economist suggests, and that has been championed for years by internet veteran Doc Searls, is to press for vastly increased transparency in terms of user data, so that individuals can improve their own sovereignty, control their relationships with platform companies, and thereby collectively demand that the companies in question disclose the value of this data — which would, by extent, improve signalling of the actual value of the company itself. If today’s platform companies are reluctant to do this, is that because it would perhaps reveal some of them to be less valuable than what they are held out to be?

Another potentially useful, proactive measure, that I describe in my article, is the establishment of vital competitors or supplements to the services that so many of us have gotten used to being provided for by platform giants. Instead of Facebook monopolizing identity management online, which sadly seems to have become the norm in some countries, look to the Scandinavian example of BankID, which is a platform service run by a regional bank consortium, offering a much safer and more nationally controllable identity management solution.

Alternative platform services like these could be built by private companies as well as state-funded ones; alongside privately owned consortia of this kind, it would be interesting to see innovation within the public service remit, exploring how that concept could be re-thought in an era of platform capitalism.

Read the full article: Jonas Andersson Schwarz (2017) Platform Logic: An Interdisciplinary Approach to the Platform-based Economy. Policy & Internet DOI: 10.1002/poi3.159.

Jonas Andersson Schwarz was talking to blog editor David Sutcliffe.

Why we shouldn’t believe the hype about the Internet “creating” development

Vast sums of money have been invested in projects to connect the world’s remaining four billion people, with these ambitious schemes often presenting digital connectivity as a means to achieve a range of social and economic developmental goals. This is especially the case for Africa, where Internet penetration rates remain relatively low, while the need for effective development strategies continues to be pressing.

Development has always grappled with why some people and places have more than others, but much of that conversation is lost within contemporary discourses of ICTs and development. As states and organisations rush to develop policies and plans, build drones and balloons, and lay fibre-optic cables, much is said about the power of ICTs to positively transform the world’s most underprivileged people and places.

Despite the vigour of such claims, there is actually a lack of academic consensus about the impacts of digital connectivity on economic development. In their new article, Nicolas Friederici, Sanna Ojanperä and Mark Graham review claims made by African governments and large international institutions about the impacts of connectivity, showing that the evidence base to support them is thin.

It is indeed possible that contemporary grand visions of connectivity are truly reflective of a promising future, but it is equally possible that many of them are hugely overblown. The current evidence base is mixed and inconclusive. More worryingly, visions of rapid ICT-driven development might not only fail to achieve their goals — they could actively undermine development efforts in a world of scarce resources. We should therefore refuse to believe it is self-evident that ICTs will automatically bring about development, and should do more to ask the organisations and entities who produce these grand visions to justify their claims.

Read the full article: Friederici, N., Ojanperä, S., and Graham, M. (2017) The Impact of Connectivity in Africa: Grand Visions and the Mirage of Inclusive Digital Development. Electronic Journal of Information Systems in Developing Countries, 79(2), 1–20.

We caught up with the authors to discuss their findings.

Ed.: Who is paying for these IT-development projects: are they business and profit-led, or donor led: and do the donors (and businesses) attach strings?

Nicolas: Funding has become ever more mixed. Foundational infrastructure like fibre-optic cables have usually been put in place through public private partnerships, where private companies lay out the network while loans, subsidies, and policy support are provided by national governments and organizations like the World Bank. Development agencies have mostly funded more targeted connectivity projects, like health or agricultural information platforms.

Recently, philanthropic foundations and tech corporations have increased their footprint, for instance, the Rockefeller Foundation’s Digital Jobs project or Facebook’s Open Cellular Base stations. So we are seeing an increasingly complex web of financial channels. What discourse does is pave the way for funding to flow into such projects.

The problem is that, while private companies may stop investing when they don’t see returns, governments and development funders might continue to pour resources into an agenda as long as it suits their ideals or desirable and widely accepted narratives. Of course, these resources are scarce; so, at the minimum, we need to allow scrutiny and look for alternatives about how development funding could be used for maximum effect.

Ed.: Simple, aspirational messages are obviously how politicians get people excited about things (and to pay for them). What is the alternative?

Nicolas: We’re not saying that the rhetoric of politicians is the problem here. We’re saying that many of the actors who are calling the shots in development are stubbornly evading valid concerns that academics and some practitioners have brought forward. The documents that we analyze in the article — and these are very influential sources — pretend that it is an unquestionable fact that there is a causal, direct and wide-spread positive impact of Internet and ICTs on all facets of development, anywhere. This assertion is not only simplistic, it’s also problematic and maybe even dangerous to think about a complex and important topic like (human, social) development in this way.

The alternative is a more open and plural conversation where we openly admit that resources spent on one thing can’t be spent on another, and where we enable different and critical opinions to enter the fray. This is especially important when a nation’s public is disempowered or misinformed, or when regulators are weak. For example, in most countries in Europe, advocacy groups and strong telecoms regulators provide a counterforce to the interests of technology corporations. Such institutions are often absent in the Global South, so the onus is on development organizations to regulate themselves, either by engaging with people “on the ground” or with academics. For instance, the recent World Development Report by the World Bank did this, which led the report to, we think, much more reliable and balanced conclusions compared to the Bank’s earlier outputs.

Ed.: You say these visions are “modernist” and “techno-determinist” — why is that? Is it a quirk of the current development landscape, or does development policy naturally tend to attract fixers (rather than doubters and worriers..). And how do we get more doubt into policy?

Nicolas: Absolutely, development organizations are all about fixing development problems, and we do not take issue with that. However, these organizations also need to understand that “fixing development” is not like fixing a machine (that is, a device that functions according to mechanical principles). It’s not like one could input “technology” or “the Internet,” and get “development” as an output.

In a nutshell, that’s what we mean when we say that visions are modernist and techno-determinist: many development organizations, governments, and corporations make the implicit assumption that technological progress is fixing development, that this is an apolitical and unstoppable process, and that this is working out in the same way everywhere on earth. This assumption glances over contestation, political choices and trade-offs, and the cultural, economic, and social diversity of contexts.

Ed.: Presumably if things are very market-led: the market will decide if the internet “solves” everything: ie either it will, or it won’t. Has there been enough time yet to verify the outcomes of these projects (e.g. how has the one-laptop initiative worked out)?

Nicolas: I’m not sure I agree with the implication that markets can decide if the Internet solves everything. It’s us humans who are deciding, making choices, prioritizing, allocating resources, setting policies, etc. As humans, we might decide that we want a market (that is, supply and demand matched by a price mechanism) to regulate some array of transactions. This is exactly what is happening, for instance, with the spread of mobile money in Kenya or the worldwide rise of smartphones: people feel they benefit from using a product and are willing to pay money to a supplier.

The issue with technology and development is (a) that in many cases, markets are not the mechanism that achieves the best development outcomes (think about education or healthcare), (b) that even the freest of markets needs to be enabled by things like political stability, infrastructure, and basic institutions (think about contract law and property rights), and (c) that many markets need regulatory intervention or power-balancing institutions to prevent one side of the exchange to dominate and exploit the other (think about workers’ rights).

In each case, it is thus a matter of evaluating what mixture of technology, markets, and protections works best to achieve the best development outcomes, keeping in mind that development is multi-dimensional and goes far beyond economic growth. These evaluations and discussions are challenging, and it takes time to determine what works, where, and when, but ultimately we’re improving our knowledge and our practice if we keep the conversation open, critical, and diverse.

Ed.: Is there a consensus on ICT and development, or are there basically lots of camps, ranging from extreme optimists to extreme pessimists? I get the impression that basically “it’s complicated” — is that fair? And how much discussion or recognition (beyond yourselves) is there about the gap between these statements and reality?

Nicolas: ICT and development has seen a lot of soul-searching, and scholars and practitioners have spent over 20 years debating the field’s nature and purpose. There is certainly no consensus on what ICTD should do, or how ICTs effect/affect development, and maybe that is an unrealistic — and undesirable — goal. There are certainly optimistic and pessimistic voices, like you mention, but there is also a lot of wisdom that is not widely acknowledged, or not in the public domain at all. There are thousands of practitioners from the Global North and South who have been in the trenches, applied their critical and curious minds, and seen what makes an impact and what is a pipe dream.

So we’re far from the only ones who are aware that much of the ICTD rhetoric is out of touch with realities, and we’re also not the first ones to identify this problem. What we tried to point out in our article is that the currently most powerful, influential, and listened to sources tend to be the ones that are overly optimistic and overly simplistic, ignoring all the wisdom and nuance created through hard scholarly and practical work. These actors seem to be detached from the messy realities of ICTD.

This carries a risk, because it is these organizations (governments, global consultancies, multilateral development organizations, and international tech corporations) that are setting the agenda, distributing the funds, making the hiring decisions, etc. in development practice.

Read the full article: Friederici, N., Ojanperä, S., and Graham, M. (2017) The Impact of Connectivity in Africa: Grand Visions and the Mirage of Inclusive Digital Development. Electronic Journal of Information Systems in Developing Countries, 79(2), 1–20.

Nicolas Friederici was talking to blog editor David Sutcliffe.

Could data pay for global development? Introducing data financing for global good

“If data is the new oil, then why aren’t we taxing it like we tax oil?” That was the essence of the provocative brief that set in motion our recent 6-month research project funded by the Rockefeller Foundation. The results are detailed in the new report: Data Financing for Global Good: A Feasibility Study.

The parallels between data and oil break down quickly once you start considering practicalities such as measuring and valuing data. Data is, after all, a highly heterogeneous good whose value is context-specific — very different from a commodity such as oil that can be measured and valued by the barrel. But even if the value of data can’t simply be metered and taxed, are there other ways in which the data economy could be more directly aligned with social good?

Data-intensive industries already contribute to social good by producing useful services and paying taxes on their profits (though some pay regrettably little). But are there ways in which the data economy could directly finance global causes such as climate change prevention, poverty alleviation and infrastructure? Such mechanisms should not just arbitrarily siphon off money from industry, but also contribute value back to the data economy by correcting market failures and investment gaps. The potential impacts are significant: estimates value the data economy at around seven percent of GDP in rich industrialised countries, or around ten times the value of the United Nations development aid spending goal.

Here’s where “data financing” comes in. It’s a term we coined that’s based on innovative financing, a concept increasingly used in the philanthropical world. Innovative financing refers to initiatives that seek to unlock private capital for the sake of global development and socially beneficial projects, which face substantial funding gaps globally. Since government funding towards addressing global challenges is not growing, the proponents of innovative financing are asking how else these critical causes could be funded. An existing example of innovative financing is the UNITAID air ticket levy used to advance global health.

Data financing, then, is a subset of innovative financing that refers to mechanisms that attempt to redirect a slice of the value created in the global data economy towards broader social objectives. For instance, a Global Internet Subsidy funded by large Internet companies could help to educate and and build infrastructure in the world’s marginalized regions, in the long run also growing the market for Internet companies’ services. But such a model would need well-designed governance mechanisms to avoid the pitfalls of current Internet subsidization initiatives, which risk failing because of well-founded concerns that they further entrench Internet giants’ dominance over emerging digital markets.

Besides the Global Internet Subsidy, other data financing models examined in the report are a Privacy Insurance for personal data processing, a Shared Knowledge Duty payable by businesses profiting from open and public data, and an Attention Levy to disincentivise intrusive marketing. Many of these have been considered before, and they come with significant economic, legal, political, and technical challenges. Our report considers these challenges in turn, assesses the feasibility of potential solutions, and presents rough estimates of potential financial impacts.

Some of the prevailing business models of the data economy — provoking users’ attention, extracting their personal information, and monetizing it through advertising — are more or less taken for granted today. But they are something of a historical accident, an unanticipated corollary to some of the technical and political decisions made early in the Internet’s design. Certainly they are not any inherent feature of data as such. Although our report focuses on the technical, legal, and political practicalities of the idea of data financing, it also invites a careful reader to question some of the accepted truths on how a data-intensive economy could be organized, and what business models might be possible.

Read the report: Lehdonvirta, V., Mittelstadt, B. D., Taylor, G., Lu, Y. Y., Kadikov, A., and Margetts, H. (2016) Data Financing for Global Good: A Feasibility Study. University of Oxford: Oxford Internet Institute.

The blockchain paradox: Why distributed ledger technologies may do little to transform the economy

Bitcoin’s underlying technology, the blockchain, is widely expected to find applications far beyond digital payments. It is celebrated as a “paradigm shift in the very idea of economic organization”. But the OII’s Professor Vili Lehdonvirta contends that such revolutionary potentials may be undermined by a fundamental paradox that has to do with the governance of the technology.

 

I recently gave a talk at the Alan Turing Institute (ATI) under the title The Problem of Governance in Distributed Ledger Technologies. The starting point of my talk was that it is frequently posited that blockchain technologies will “revolutionize industries that rely on digital record keeping”, such as financial services and government. In the talk I applied elementary institutional economics to examine what blockchain technologies really do in terms of economic organization, and what problems this gives rise to. In this essay I present an abbreviated version of the argument. Alternatively you can watch a video of the talk below.

 

[youtube https://www.youtube.com/watch?v=eNrzE_UfkTw&w=640&h=360]

 

First, it is necessary to note that there is quite a bit of confusion as to what exactly is meant by a blockchain. When people talk about “the” blockchain, they often refer to the Bitcoin blockchain, an ongoing ledger of transactions started in 2009 and maintained by the approximately 5,000 computers that form the Bitcoin peer-to-peer network. The term blockchain can also be used to refer to other instances or forks of the same technology (“a” blockchain). The term “distributed ledger technology” (DLT) has also gained currency recently as a more general label for related technologies.

In each case, I think it is fair to say that the reason that so many people are so excited about blockchain today is not the technical features as such. In terms of performance metrics like transactions per second, existing blockchain technologies are in many ways inferior to more conventional technologies. This is frequently illustrated with the point that the Bitcoin network is limited by design to process at most approximately seven transactions per second, whereas the Visa payment network has a peak capacity of 56,000 transactions per second. Other implementations may have better performance, and on some other metrics blockchain technologies can perhaps beat more conventional technologies. But technical performance is not why so many people think blockchain is revolutionary and paradigm-shifting.

The reason that blockchain is making waves is that it promises to change the very way economies are organized: to eliminate centralized third parties. Let me explain what this means in theoretical terms. Many economic transactions, such as long-distance trade, can be modeled as a game of Prisoners’ Dilemma. The buyer and the seller can either cooperate (send the shipment/payment as promised) or defect (not send the shipment/payment). If the buyer and the seller don’t trust each other, then the equilibrium solution is that neither player cooperates and no trade takes place. This is known as the fundamental problem of cooperation.

There are several classic solutions to the problem of cooperation. One is reputation. In a community of traders where members repeatedly engage in exchange, any trader who defects (fails to deliver on a promise) will gain a negative reputation, and other traders will refuse to trade with them out of self-interest. This threat of exclusion from the community acts as a deterrent against defection, and the equilibrium under certain conditions becomes that everyone will cooperate.

Reputation is only a limited solution, however. It only works within communities where reputational information spreads effectively, and traders may still defect if the payoff from doing so is greater than the loss of future trade. Modern large-scale market economies where people trade with strangers on a daily basis are only possible because of another solution: third-party enforcement. In particular, this means state-enforced contracts and bills of exchange enforced by banks. These third parties in essence force parties to cooperate and to follow through with their promises.

Besides trade, another example of the problem of cooperation is currency. Currency can be modeled as a multiplayer game of Prisoners’ Dilemma. Traders collectively have an interest in maintaining a stable currency, because it acts as a lubricant to trade. But each trader individually has an interest in debasing the currency, in the sense of paying with fake money (what in blockchain-speak is referred to as double spending). Again the classic solution to this dilemma is third-party enforcement: the state polices metal currencies and punishes counterfeiters, and banks control ledgers and prevent people from spending money they don’t have.

So third-party enforcement is the dominant model of economic organization in today’s market economies. But it’s not without its problems. The enforcer is in a powerful position in relation to the enforced: banks could extract exorbitant fees, and states could abuse their power by debasing the currency, illegitimately freezing assets, or enforcing contracts in unfair ways. One classic solution to the problems of third-party enforcement is competition. Bank fees are kept in check by competition: the enforced can switch to another enforcer if the fees get excessive.

But competition is not always a viable solution: there is a very high cost to switching to another state (i.e. becoming a refugee) if your state starts to abuse its power. Another classic solution is accountability: democratic institutions that try to ensure the enforcer acts in the interest of the enforced. For instance, the interbank payment messaging network SWIFT is a cooperative society owned by its member banks. The members elect a Board of Directors that is the highest decision making body in the organization. This way, they attempt to ensure that SWIFT does not try to extract excessive fees from the member banks or abuse its power against them. Still, even accountability is not without its problems, since it comes with the politics of trying to reconcile different members’ diverging interests as best as possible.

Into this picture enters blockchain: a technology where third-party enforcers are replaced with a distributed network that enforces the rules. It can enforce contracts, prevent double spending, and cap the size of the money pool all without participants having to cede power to any particular third party who might abuse the power. No rent-seeking, no abuses of power, no politics — blockchain technologies can be used to create “math-based money” and “unstoppable” contracts that are enforced with the impartiality of a machine instead of the imperfect and capricious human bureaucracy of a state or a bank. This is why so many people are so excited about blockchain: its supposed ability change economic organization in a way that transforms dominant relationships of power.

Unfortunately this turns out to be a naive understanding of blockchain, and the reality is inevitably less exciting. Let me explain why. In economic organization, we must distinguish between enforcing rules and making rules. Laws are rules enforced by state bureaucracy and made by a legislature. The SWIFT Protocol is a set of rules enforced by SWIFTNet (a centralized computational system) and made, ultimately, by SWIFT’s Board of Directors. The Bitcoin Protocol is a set of rules enforced by the Bitcoin Network (a distributed network of computers) made by — whom exactly? Who makes the rules matters at least as much as who enforces them. Blockchain technology may provide for completely impartial rule-enforcement, but that is of little comfort if the rules themselves are changed. This rule-making is what we refer to as governance.

Using Bitcoin as an example, the initial versions of the protocol (ie. the rules) were written by the pseudonymous Satoshi Nakamoto, and later versions are released by a core development team. The development team is not autocratic: a complex set of social and technical entanglements means that other people are also influential in how Bitcoin’s rules are set; in particular, so-called mining pools, headed by a handful of individuals, are very influential. The point here is not to attempt to pick apart Bitcoin’s political order; the point is that Bitcoin has not in any sense eliminated human politics; humans are still very much in charge of setting the rules that the network enforces.

There is, however, no formal process for how governance works in Bitcoin, because for a very long time these politics were not explicitly recognized, and many people don’t recognize them, preferring instead the idea that Bitcoin is purely “math-based money” and that all the developers are doing is purely apolitical plumbing work. But what has started to make this position untenable and Bitcoin’s politics visible is the so-called “block size debate” — a big disagreement between factions of the Bitcoin community over the future direction of the rules. Different stakeholders have different interests in the matter, and in the absence of a robust governance mechanism that could reconcile between the interests, this has resulted in open “warfare” between the camps over social media and discussion forums.

Will competition solve the issue? Multiple “forks” of the Bitcoin protocol have emerged, each with slightly different rules. But network economics teaches us that competition does not work well at all in the presence of strong network effects: everyone prefers to be in the network where other people are, even if its rules are not exactly what they would prefer. Network markets tend to tip in favour of the largest network. Every fork/split diminishes the total value of the system, and those on the losing side of a fork may eventually find their assets worthless.

If competition doesn’t work, this leaves us with accountability. There is no obvious path how Bitcoin could develop accountable governance institutions. But other blockchain projects, especially those that are gaining some kind of commercial or public sector legitimacy, are designed from the ground up with some level of accountable governance. For instance, R3 is a firm that develops blockchain technology for use in the financial services industry. It has enrolled a consortium of banks to guide the effort, and its documents talk about the “mandate” it has from its “member banks”. Its governance model thus sounds a lot like the beginnings of something like SWIFT. Another example is RSCoin, designed by my ATI colleagues George Danezis and Sarah Meiklejohn, which is intended to be governed by a central bank.

Regardless of the model, my point is that blockchain technologies cannot escape the problem of governance. Whether they recognize it or not, they face the same governance issues as conventional third-party enforcers. You can use technologies to potentially enhance the processes of governance (eg. transparency, online deliberation, e-voting), but you can’t engineer away governance as such. All this leads me to wonder how revolutionary blockchain technologies really are. If you still rely on a Board of Directors or similar body to make it work, how much has economic organization really changed?

And this leads me to my final point, a provocation: once you address the problem of governance, you no longer need blockchain; you can just as well use conventional technology that assumes a trusted central party to enforce the rules, because you’re already trusting somebody (or some organization/process) to make the rules. I call this blockchain’s ‘governance paradox’: once you master it, you no longer need it. Indeed, R3’s design seems to have something called “uniqueness services”, which look a lot like trusted third-party enforcers (though this isn’t clear from the white paper). RSCoin likewise relies entirely on trusted third parties. The differences to conventional technology are no longer that apparent.

Perhaps blockchain technologies can still deliver better technical performance, like better availability and data integrity. But it’s not clear to me what real changes to economic organization and power relations they could bring about. I’m very happy to be challenged on this, if you can point out a place in my reasoning where I’ve made an error. Understanding grows via debate. But for the time being, I can’t help but be very skeptical of the claims that blockchain will fundamentally transform the economy or government.

The governance of DLTs is also examined in this report chapter that I coauthored earlier this year:

Lehdonvirta, V. & Robleh, A. (2016) Governance and Regulation. In: M. Walport (ed.), Distributed Ledger Technology: Beyond Blockchain. London: UK Government Office for Science, pp. 40-45.

The blockchain paradox: Why distributed ledger technologies may do little to transform the economy

Bitcoin’s underlying technology, the blockchain, is widely expected to find applications far beyond digital payments. It is celebrated as a “paradigm shift in the very idea of economic organization”. But the OII’s Professor Vili Lehdonvirta contends that such revolutionary potentials may be undermined by a fundamental paradox that has to do with the governance of the technology.

 

I recently gave a talk at the Alan Turing Institute (ATI) under the title The Problem of Governance in Distributed Ledger Technologies. The starting point of my talk was that it is frequently posited that blockchain technologies will “revolutionize industries that rely on digital record keeping”, such as financial services and government. In the talk I applied elementary institutional economics to examine what blockchain technologies really do in terms of economic organization, and what problems this gives rise to. In this essay I present an abbreviated version of the argument. Alternatively you can watch a video of the talk below.

 

[youtube https://www.youtube.com/watch?v=eNrzE_UfkTw&w=640&h=360]

 

First, it is necessary to note that there is quite a bit of confusion as to what exactly is meant by a blockchain. When people talk about “the” blockchain, they often refer to the Bitcoin blockchain, an ongoing ledger of transactions started in 2009 and maintained by the approximately 5,000 computers that form the Bitcoin peer-to-peer network. The term blockchain can also be used to refer to other instances or forks of the same technology (“a” blockchain). The term “distributed ledger technology” (DLT) has also gained currency recently as a more general label for related technologies.

In each case, I think it is fair to say that the reason that so many people are so excited about blockchain today is not the technical features as such. In terms of performance metrics like transactions per second, existing blockchain technologies are in many ways inferior to more conventional technologies. This is frequently illustrated with the point that the Bitcoin network is limited by design to process at most approximately seven transactions per second, whereas the Visa payment network has a peak capacity of 56,000 transactions per second. Other implementations may have better performance, and on some other metrics blockchain technologies can perhaps beat more conventional technologies. But technical performance is not why so many people think blockchain is revolutionary and paradigm-shifting.

The reason that blockchain is making waves is that it promises to change the very way economies are organized: to eliminate centralized third parties. Let me explain what this means in theoretical terms. Many economic transactions, such as long-distance trade, can be modeled as a game of Prisoners’ Dilemma. The buyer and the seller can either cooperate (send the shipment/payment as promised) or defect (not send the shipment/payment). If the buyer and the seller don’t trust each other, then the equilibrium solution is that neither player cooperates and no trade takes place. This is known as the fundamental problem of cooperation.

There are several classic solutions to the problem of cooperation. One is reputation. In a community of traders where members repeatedly engage in exchange, any trader who defects (fails to deliver on a promise) will gain a negative reputation, and other traders will refuse to trade with them out of self-interest. This threat of exclusion from the community acts as a deterrent against defection, and the equilibrium under certain conditions becomes that everyone will cooperate.

Reputation is only a limited solution, however. It only works within communities where reputational information spreads effectively, and traders may still defect if the payoff from doing so is greater than the loss of future trade. Modern large-scale market economies where people trade with strangers on a daily basis are only possible because of another solution: third-party enforcement. In particular, this means state-enforced contracts and bills of exchange enforced by banks. These third parties in essence force parties to cooperate and to follow through with their promises.

Besides trade, another example of the problem of cooperation is currency. Currency can be modeled as a multiplayer game of Prisoners’ Dilemma. Traders collectively have an interest in maintaining a stable currency, because it acts as a lubricant to trade. But each trader individually has an interest in debasing the currency, in the sense of paying with fake money (what in blockchain-speak is referred to as double spending). Again the classic solution to this dilemma is third-party enforcement: the state polices metal currencies and punishes counterfeiters, and banks control ledgers and prevent people from spending money they don’t have.

So third-party enforcement is the dominant model of economic organization in today’s market economies. But it’s not without its problems. The enforcer is in a powerful position in relation to the enforced: banks could extract exorbitant fees, and states could abuse their power by debasing the currency, illegitimately freezing assets, or enforcing contracts in unfair ways. One classic solution to the problems of third-party enforcement is competition. Bank fees are kept in check by competition: the enforced can switch to another enforcer if the fees get excessive.

But competition is not always a viable solution: there is a very high cost to switching to another state (i.e. becoming a refugee) if your state starts to abuse its power. Another classic solution is accountability: democratic institutions that try to ensure the enforcer acts in the interest of the enforced. For instance, the interbank payment messaging network SWIFT is a cooperative society owned by its member banks. The members elect a Board of Directors that is the highest decision making body in the organization. This way, they attempt to ensure that SWIFT does not try to extract excessive fees from the member banks or abuse its power against them. Still, even accountability is not without its problems, since it comes with the politics of trying to reconcile different members’ diverging interests as best as possible.

Into this picture enters blockchain: a technology where third-party enforcers are replaced with a distributed network that enforces the rules. It can enforce contracts, prevent double spending, and cap the size of the money pool all without participants having to cede power to any particular third party who might abuse the power. No rent-seeking, no abuses of power, no politics — blockchain technologies can be used to create “math-based money” and “unstoppable” contracts that are enforced with the impartiality of a machine instead of the imperfect and capricious human bureaucracy of a state or a bank. This is why so many people are so excited about blockchain: its supposed ability change economic organization in a way that transforms dominant relationships of power.

Unfortunately this turns out to be a naive understanding of blockchain, and the reality is inevitably less exciting. Let me explain why. In economic organization, we must distinguish between enforcing rules and making rules. Laws are rules enforced by state bureaucracy and made by a legislature. The SWIFT Protocol is a set of rules enforced by SWIFTNet (a centralized computational system) and made, ultimately, by SWIFT’s Board of Directors. The Bitcoin Protocol is a set of rules enforced by the Bitcoin Network (a distributed network of computers) made by — whom exactly? Who makes the rules matters at least as much as who enforces them. Blockchain technology may provide for completely impartial rule-enforcement, but that is of little comfort if the rules themselves are changed. This rule-making is what we refer to as governance.

Using Bitcoin as an example, the initial versions of the protocol (ie. the rules) were written by the pseudonymous Satoshi Nakamoto, and later versions are released by a core development team. The development team is not autocratic: a complex set of social and technical entanglements means that other people are also influential in how Bitcoin’s rules are set; in particular, so-called mining pools, headed by a handful of individuals, are very influential. The point here is not to attempt to pick apart Bitcoin’s political order; the point is that Bitcoin has not in any sense eliminated human politics; humans are still very much in charge of setting the rules that the network enforces.

There is, however, no formal process for how governance works in Bitcoin, because for a very long time these politics were not explicitly recognized, and many people don’t recognize them, preferring instead the idea that Bitcoin is purely “math-based money” and that all the developers are doing is purely apolitical plumbing work. But what has started to make this position untenable and Bitcoin’s politics visible is the so-called “block size debate” — a big disagreement between factions of the Bitcoin community over the future direction of the rules. Different stakeholders have different interests in the matter, and in the absence of a robust governance mechanism that could reconcile between the interests, this has resulted in open “warfare” between the camps over social media and discussion forums.

Will competition solve the issue? Multiple “forks” of the Bitcoin protocol have emerged, each with slightly different rules. But network economics teaches us that competition does not work well at all in the presence of strong network effects: everyone prefers to be in the network where other people are, even if its rules are not exactly what they would prefer. Network markets tend to tip in favour of the largest network. Every fork/split diminishes the total value of the system, and those on the losing side of a fork may eventually find their assets worthless.

If competition doesn’t work, this leaves us with accountability. There is no obvious path how Bitcoin could develop accountable governance institutions. But other blockchain projects, especially those that are gaining some kind of commercial or public sector legitimacy, are designed from the ground up with some level of accountable governance. For instance, R3 is a firm that develops blockchain technology for use in the financial services industry. It has enrolled a consortium of banks to guide the effort, and its documents talk about the “mandate” it has from its “member banks”. Its governance model thus sounds a lot like the beginnings of something like SWIFT. Another example is RSCoin, designed by my ATI colleagues George Danezis and Sarah Meiklejohn, which is intended to be governed by a central bank.

Regardless of the model, my point is that blockchain technologies cannot escape the problem of governance. Whether they recognize it or not, they face the same governance issues as conventional third-party enforcers. You can use technologies to potentially enhance the processes of governance (eg. transparency, online deliberation, e-voting), but you can’t engineer away governance as such. All this leads me to wonder how revolutionary blockchain technologies really are. If you still rely on a Board of Directors or similar body to make it work, how much has economic organization really changed?

And this leads me to my final point, a provocation: once you address the problem of governance, you no longer need blockchain; you can just as well use conventional technology that assumes a trusted central party to enforce the rules, because you’re already trusting somebody (or some organization/process) to make the rules. I call this blockchain’s ‘governance paradox’: once you master it, you no longer need it. Indeed, R3’s design seems to have something called “uniqueness services”, which look a lot like trusted third-party enforcers (though this isn’t clear from the white paper). RSCoin likewise relies entirely on trusted third parties. The differences to conventional technology are no longer that apparent.

Perhaps blockchain technologies can still deliver better technical performance, like better availability and data integrity. But it’s not clear to me what real changes to economic organization and power relations they could bring about. I’m very happy to be challenged on this, if you can point out a place in my reasoning where I’ve made an error. Understanding grows via debate. But for the time being, I can’t help but be very skeptical of the claims that blockchain will fundamentally transform the economy or government.

The governance of DLTs is also examined in this report chapter that I coauthored earlier this year:

Lehdonvirta, V. & Robleh, A. (2016) Governance and Regulation. In: M. Walport (ed.), Distributed Ledger Technology: Beyond Blockchain. London: UK Government Office for Science, pp. 40-45.

Uber and Airbnb make the rules now — but to whose benefit?

The "Airbnb Law" was signed by Mayor Ed Lee in October 2014 at San Francisco City Hall, legalizing short-term rentals in SF with many conditions. Image by Kevin Krejci (Flickr).
The “Airbnb Law” was signed by Mayor Ed Lee in October 2014 at San Francisco City Hall, legalizing short-term rentals in SF with many conditions. Image of protesters by Kevin Krejci (Flickr).

Ride-hailing app Uber is close to replacing government-licensed taxis in some cities, while Airbnb’s accommodation rental platform has become a serious competitor to government-regulated hotel markets. Many other apps and platforms are trying to do the same in other sectors of the economy. In my previous post, I argued that platforms can be viewed in social science terms as economic institutions that provide infrastructures necessary for markets to thrive. I explained how the natural selection theory of institutional change suggests that people are migrating from state institutions to these new code-based institutions because they provide a more efficient environment for doing business. In this article, I will discuss some of the problems with this theory, and outline a more nuanced theory of institutional change that suggests that platforms’ effects on society will be complex and influence different people in different ways.

Economic sociologists like Neil Fligstein have pointed out that not everyone is as free to choose the means through which they conduct their trade. For example, if buyers in a market switch to new institutions, sellers may have little choice but to follow, even if the new institutions leave them worse off than the old ones did. Even if taxi drivers don’t like Uber’s rules, they may find that there is little business to be had outside the platform, and switch anyway. In the end, the choice of institutions can boil down to power. Economists have shown that even a small group of participants with enough market power — like corporate buyers — may be able to force a whole market to tip in favour of particular institutions. Uber offers a special solution for corporate clients, though I don’t know if this has played any part in the platform’s success.

Even when everyone participates in an institutional arrangement willingly, we still can’t assume that it will contribute to the social good. Cambridge economic historian Sheilagh Ogilvie has pointed out that an institution that is efficient for everyone who participates in it can still be inefficient for society as a whole if it affects third parties. For example, when Airbnb is used to turn an ordinary flat into a hotel room, it can cause nuisance to neighbours in the form of noise, traffic, and guests unfamiliar with the local rules. The convenience and low cost of doing business through the platform is achieved in part at others’ expense. In the worst case, a platform can make society not more but less efficient — by creating a ‘free rider economy’.

In general, social scientists recognize that different people and groups in society often have conflicting interests in how economic institutions are shaped. These interests are reconciled — if they are reconciled — through political institutions. Many social scientists thus look not so much at efficiencies but at political institutions to understand why economic institutions are shaped the way they are. For example, a democratic local government in principle represents the interests of its citizens, through political institutions such as council elections and public consultations. Local governments consequently try to strike a balance between the conflicting interests of hoteliers and their neighbours, by limiting hotel business to certain zones. In contrast, Airbnb as a for-profit business must cater to the interests of its customers, the would-be hoteliers and their guests. It has no mechanism, and more importantly, no mandate, to address on an equal footing the interests of third parties like customers’ neighbours. Perhaps because of this, 74% of Airbnb’s properties are not in the main hotel districts, but in ordinary residential blocks.

That said, governments have their own challenges in producing fair and efficient economic institutions. Not least among these is the fact that government regulators are at a risk of capture by incumbent market participants, or at the very least they face the innovator’s dilemma: it is easier to craft rules that benefit the incumbents than rules that provide great but uncertain benefits to future market participants. For example, cities around the world operate taxi licensing systems, where only strictly limited numbers of license owners are allowed to operate taxicabs. Whatever benefits this system offers to customers in terms of quality assurance, among its biggest beneficiaries are the license owners, and among its losers the would-be drivers who are excluded from the market. Institutional insiders and outsiders have conflicting interests, and government political institutions are often such that it is easier for it to side with the insiders.

Against this background, platforms appear almost as radical reformers that provide market access to those whom the establishment has denied it. For example, Uber recently announced that it aims to create one million jobs for women by 2020, a bold pledge in the male-dominated transport industry, and one that would likely not be possible if it adhered to government licensing requirements, as most licenses are owned by men. Having said that, Uber’s definition of a ‘job’ is something much more precarious and entrepreneurial than the conventional definition. My point here is not to side with either Uber or the licensing system, but to show that their social implications are very different. Both possess at least some flaws as well as redeeming qualities, many of which can be traced back to their political institutions and whom they represent.

What kind of new economic institutions are platform developers creating? How efficient are they? What other consequences, including unintended ones, do they have and to whom? Whose interests are they geared to represent — capital vs. labour, consumer vs. producer, Silicon Valley vs. local business, incumbent vs. marginalized? These are the questions that policy makers, journalists, and social scientists ought to be asking at this moment of transformation in our economic institutions. Instead of being forced to choose one or the other between established institutions and platforms as they currently are, I hope that we will be able to discover ways to take what is good in both, and create infrastructure for an economy that is as fair and inclusive as it is efficient and innovative.

Vili Lehdonvirta is a Research Fellow and DPhil Programme Director at the Oxford Internet Institute, and an editor of the Policy & Internet journal. He is an economic sociologist who studies the social and economic dimensions of new information technologies around the world, with particular expertise in digital markets and crowdsourcing.

Why are citizens migrating to Uber and Airbnb, and what should governments do about it?

protested fair taxi laws by parking in Pioneer square. Organizers want city leaders to make ride-sharing companies play by the same rules as cabs and Town cars. Image: Aaron Parecki (Flickr).
Protest for fair taxi laws in Portland; organizers want city leaders to make ride-sharing companies play by the same rules as cabs and Town cars. Image: Aaron Parecki (Flickr).

Cars were smashed and tires burned in France last month in protests against the ride hailing app Uber. Less violent protests have also been staged against Airbnb, a platform for renting short-term accommodation. Despite the protests, neither platform shows any signs of faltering. Uber says it has a million users in France, and is available in 57 countries. Airbnb is available in over 190 countries, and boasts over a million rooms, more than hotel giants like Hilton and Marriott. Policy makers at the highest levels are starting to notice the rise of these and similar platforms. An EU Commission flagship strategy paper notes that “online platforms are playing an ever more central role in social and economic life,” while the Federal Trade Commission recently held a workshop on the topic in Washington.

Journalists and entrepreneurs have been quick to coin terms that try to capture the essence of the social and economic changes associated with online platforms: the sharing economy; the on-demand economy; the peer-to-peer economy; and so on. Each perhaps captures one aspect of the phenomenon, but doesn’t go very far in helping us make sense of all its potentials and contradictions, including why some people love it and some would like to smash it into pieces. Instead of starting from the assumption that everything we see today is new and unprecedented, what if we dug into existing social science theory to see what it has to say about economic transformation and the emergence of markets?

Economic sociologists are adamant that markets don’t just emerge by themselves: they are always based on some kind of an underlying infrastructure that allows people to find out what goods and services are on offer, agree on prices and terms, pay, and have a reasonable expectation that the other party will honour the agreement. The oldest market infrastructure is the personal social network: traders hear what’s on offer through word of mouth and trade only with those whom they personally know and trust. But personal networks alone couldn’t sustain the immense scale of trading in today’s society. Every day we do business with strangers and trust them to provide for our most basic needs. This is possible because modern society has developed institutions — things like private property, enforceable contracts, standardized weights and measures, consumer protection, and many other general and sector specific norms and facilities. By enabling and constraining everyone’s behaviours in predictable ways, institutions constitute a robust and more inclusive infrastructure for markets than personal social networks.

Modern institutions didn’t of course appear out of nowhere. Between prehistoric social networks and the contemporary institutions of the modern state, there is a long historical continuum of economic institutions, from ancient trade routes with their customs to medieval fairs with their codes of conduct to state-enforced trade laws of the early industrial era. Institutional economists led by Oliver Williamson and economic historians led by Douglass North theorized in the 1980s that economic institutions evolve towards more efficient forms through a process of natural selection. As new institutional forms become possible thanks to technological and organizational innovation, people switch to cheaper, easier, more secure, and overall more efficient institutions out of self-interest. Old and cumbersome institutions fall into disuse, and society becomes more efficient and economically prosperous as a result. Williamson and North both later received the Nobel Memorial Prize in Economic Sciences.

It is easy to frame platforms as the next step in such an evolutionary process. Even if platforms don’t replace state institutions, they can plug gaps that remain the state-provided infrastructure. For example, enforcing a contract in court is often too expensive and unwieldy to be used to secure transactions between individual consumers. Platforms provide cheaper and easier alternatives to formal contract enforcement, in the form of reputation systems that allow participants to rate each others’ conduct and view past ratings. Thanks to this, small transactions like sharing a commute that previously only happened in personal networks can now potentially take place on a wider scale, resulting in greater resource efficiency and prosperity (the ‘sharing economy’). Platforms are not the first companies to plug holes in state-provided market infrastructure, though. Private arbitrators, recruitment agencies, and credit rating firms have been doing similar things for a long time.

What’s arguably new about platforms, though, is that some of the most popular ones are not mere complements, but almost complete substitutes to state-provided market infrastructures. Uber provides a complete substitute to government-licensed taxi infrastructures, addressing everything from quality and discovery to trust and payment. Airbnb provides a similarly sweeping solution to short-term accommodation rental. Both platforms have been hugely successful; in San Francisco, Uber has far surpassed the city’s official taxi market in size. The sellers on these platforms are not just consumers wanting to make better use of their resources, but also firms and professionals switching over from the state infrastructure. It is as if people and companies were abandoning their national institutions and emigrating en masse to Platform Nation.

From the natural selection perspective, this move from state institutions to platforms seems easy to understand. State institutions are designed by committee and carry all kinds of historical baggage, while platforms are designed from the ground up to address their users’ needs. Government institutions are geographically fragmented, while platforms offer a seamless experience from one city, country, and language area to the other. Government offices have opening hours and queues, while platforms make use of latest technologies to provide services around the clock (the ‘on-demand economy’). Given the choice, people switch to the most efficient institutions, and society becomes more efficient as a result. The policy implications of the theory are that government shouldn’t try to stop people from using Uber and Airbnb, and that it shouldn’t try to impose its evidently less efficient norms on the platforms. Let competing platforms innovate new regulatory regimes, and let people vote with their feet; let there be a market for markets.

The natural selection theory of institutional change provides a compellingly simple way to explain the rise of platforms. However, it has difficulty in explaining some important facts, like why economic institutions have historically developed differently in different places around the world, and why some people now protest vehemently against supposedly better institutions. Indeed, over the years since the theory was first introduced, social scientists have discovered significant problems in it. Economic sociologists like Neil Fligstein have noted that not everyone is as free to choose the institutions that they use. Economic historian Sheilagh Ogilvie has pointed out that even institutions that are efficient for those who participate in them can still sometimes be inefficient for society as a whole. These points suggest a different theory of institutional change, which I will apply to online platforms in my next post.

Vili Lehdonvirta is a Research Fellow and DPhil Programme Director at the Oxford Internet Institute, and an editor of the Policy & Internet journal. He is an economic sociologist who studies the social and economic dimensions of new information technologies around the world, with particular expertise in digital markets and crowdsourcing.

Does a market-approach to online privacy protection result in better protection for users?

Ed: You examined the voluntary provision by commercial sites of information privacy protection and control under the self-regulatory policy of the U.S. Federal Trade Commission (FTC). In brief, what did you find?

Yong Jin: First, because we rely on the Internet to perform almost all types of transactions, how personal privacy is protected is perhaps one of the important issues we face in this digital age. There are many important findings: the most significant one is that the more popular sites did not necessarily provide better privacy control features for users than sites that were randomly selected. This is surprising because one might expect “the more popular, the better privacy protection” — a sort of marketplace magic that automatically solves the issue of personal privacy online. This was not the case at all, because the popular sites with more resources did not provide better privacy protection. Of course, the Internet in general is a malleable medium. This means that commercial sites can design, modify, or easily manipulate user interfaces to maximize the ease with which users can protect their personal privacy. The fact that this is not really happening for commercial websites in the U.S. is not only alarming, but also suggests that commercial forces may not have a strong incentive to provide privacy protection.

Ed: Your sample included websites oriented toward young users and sensitive data relating to health and finance: what did you find for them?

Yong Jin: Because the sample size for these websites was limited, caution is needed in interpreting the results. But what is clear is that just because the websites deal with health or financial data, they did not seem to be better at providing more privacy protection. To me, this should raise enormous concerns from those who use the Internet for health information seeking or financial data. The finding should also inform and urge policymakers to ask whether the current non-intervention policy (regarding commercial websites in the U.S.) is effective, when no consideration is given for the different privacy needs in different commercial sectors.

Ed: How do your findings compare with the first investigation into these matters by the FTC in 1998?

Yong Jin: This is a very interesting question. In fact, at least as far as the findings from this study are concerned, it seems that no clear improvement has been made in almost two decades. Of course, the picture is somewhat complicated. On the one hand, we see (on the surface) that websites have a lot more interactive features. But this does not necessarily mean improvement, because when it comes to actually informing users of what features are available for their privacy control and protection, they still tend to perform poorly. Note that today’s privacy policies are longer and are likely to carry more pages and information, which makes it even more difficult for users to understand what options they do have. I think informing people about what they can actually do is harder, but is getting more important in today’s online environment.

Ed: Is this just another example of a US market-led vs European regulation-led approach to a particular problem? Or is the situation more complicated?

Yong Jin: The answer is yes and no. Yes, it is because a US market-led approach clearly presents no strong statuary ground to mandate privacy protection in commercial websites. However, the answer is also no: even in the EU there is no regulatory mandate for websites to have certain interface-protections concerning how users should get informed about their personal data, and interact with websites to control its use. The difference is more on the fundamental principle of the “opt-in” EU approach. Although the “opt-in” is stronger than the “opt-out” approach in the U.S. this does not require websites to have certain interface-design aspects that are optimized for users’ data control. In other words, to me, the reality of the EU regulation (despite its robust policy approach) will not necessarily be rosier than the U.S., because commercial websites in the EU context also operate under the same incentive of personal data collection and uses. Ultimately, this is an empirical question that will require further studies. Interestingly, the next frontier of this debate will be on privacy in mobile platforms – and useful information concerning this can be found at the OII’s project to develop ethical privacy guidelines for mobile connectivity measurements.

Ed: Awareness of issues around personal data protection is pretty prominent in Europe — witness the recent European Court of Justice ruling about the ‘Right to Forget’ — how prominent is this awareness in the States? Who’s interested in / pushing / discussing these issues?

Yong Jin: The general public in the U.S. has an enormous concern for personal data privacy, since the Edward Snowden revelations in 2013 revealed extensive government surveillance activities. Yet my sense is that public awareness concerning data collection and surveillance by commercial companies has not yet reached the same level. Certainly, the issue such as the “Right to Forget” is being discussed among only a small circle of scholars, website operators, journalists, and policymakers, and I see the general public mostly remains left out of this discussion. In fact, a number of U.S. scholars have recently begun to weigh the pros and cons of a “Right to Forget” in terms of the public’s right to know vs the individual’s right to privacy. Given the strong tradition of freedom of speech, however, I highly doubt that U.S. policymakers will have a serious interest in pushing a similar type of approach in the foreseeable future.

My own work on privacy awareness, digital literacy, and behavior online suggests that public interest and demand for strong legislation such as a “Right to Forget” is a long shot, especially in the context of commercial websites.

Ed: Given privacy policies are notoriously awful to deal with (and are therefore generally unread) — what is the solution? You say the situation doesn’t seem to have improved in ten years, and that some aspects — such as readability of policies — might actually have become worse: is this just ‘the way things are always going to be’, or are privacy policies something that realistically can and should be addressed across the board, not just for a few sites?

Yong Jin: A great question, and I see no easy answer! I actually pondered a similar question when I conducted this study. I wonder: “Are there any viable solutions for online privacy protection when commercial websites are so desperate to use personal data?” My short answer is No. And I do think the problem will persist if the current regulatory contours in the U.S. continue. This means that there is a need for appropriate policy intervention that is not entirely dependent on market-based solutions.

My longer answer would be that realistically, to solve the notoriously difficult privacy problems on the Internet, we will need multiple approaches — which means a combination of appropriate regulatory forces by all the entities involved: regulatory mandates (government), user awareness and literacy (public), commercial firms and websites (market), and interface design (technology). For instance, it is plausible to perceive a certain level of readability of policy statement is to be required of all websites targeting children or teenagers. Of course, this will function with appropriate organizational behaviors, users’ awareness and interest in privacy, etc. In my article I put a particular emphasis on the role of the government (particularly in the U.S.) where the industry often ‘captures’ the regulatory agencies. The issue is quite complicated because for privacy protection, it is not just the FTC but also Congress who should enact to empower the FTC in its jurisdiction. The apparent lack of improvement over the years since the FTC took over online privacy regulation in the mid 1990s reflects this gridlock in legislative dynamics — as much as it reflects the commercial imperative for personal data collection and use.

I made a similar argument for multiple approaches to solve privacy problems in my article Offline Status, Online Status Reproduction of Social Categories in Personal Information Skill and Knowledge, and related, excellent discussions can be found in Information Privacy in Cyberspace Transactions (by Jerry Kang), and Exploring Identity and Identification in Cyberspace, by Oscar Gandy.

Read the full article: Park, Y.J. (2014) A Broken System of Self-Regulation of Privacy Online? Surveillance, Control, and Limits of User Features in U.S. Websites. Policy & Internet 6 (4) 360-376.

Yong Jin Park was taking to blog editor David Sutcliffe.

Yong Jin Park is an Associate Professor at the School of Communications, Howard University. His research interests center on social and policy implications of new technologies; current projects examine various dimensions of digital privacy.

Will digital innovation disintermediate banking — and can regulatory frameworks keep up?

Many of Europe’s economies are hampered by a waning number of innovations, partially attributable to the European financial system’s aversion to funding innovative enterprises and initiatives. Image by MPD01605.
Innovation doesn’t just fall from the sky. It’s not distributed proportionately or randomly around the world or within countries, or found disproportionately where there is the least regulation, or in exact linear correlation with the percentage of GDP spent on R&D. Innovation arises in cities and countries, and perhaps most importantly of all, in the greatest proportion in ecosystems or clusters. Many of Europe’s economies are hampered by a waning number of innovations, partially attributable to the European financial system’s aversion to funding innovative enterprises and initiatives. Specifically, Europe’s innovation finance ecosystem lacks the necessary scale, plurality, and appetite for risk to drive investments in long-term initiatives aiming to produce a disruptive new technology. Such long-term investments are taking place more in the rising economies of Asia than in Europe.

While these problems could be addressed by new approaches and technologies for financing dynamism in Europe’s economies, financing of (potentially risky) innovation could also be held back by financial regulation that focuses on stability, avoiding forum shopping (i.e., looking for the most permissive regulatory environment), and preventing fraud, to the exclusion of other interests, particularly innovation and renewal. But the role of finance in enabling the development and implementation of new ideas is vital — an economy’s dynamism depends on innovative competitors challenging, and if successful, replacing complacent players in the markets.

However, newcomers obviously need capital to grow. As a reaction to the markets having priced risk too low before the financial crisis, risk is now being priced too high in Europe, starving the innovation efforts of private financing at a time when much public funding has suffered from austerity measures. Of course, complementary (non-bank) sources of finance can also help fund entrepreneurship, and without that petrol of money, the engine of the new technology economy will likely stall.

The Internet has made it possible to fund innovation in new ways like crowd funding — an innovation in finance itself — and there is no reason to think that financial institutions should be immune to disruptive innovation produced by new entrants that offer completely novel ways of saving, insuring, loaning, transferring and investing money. New approaches such as crowdfunding and other financial technology (aka “FinTech”) initiatives could provide depth and a plurality of perspectives, in order to foster innovation in financial services and in the European economy as a whole.

The time has come to integrate these financial technologies into the overall financial frameworks in a manner that does not neuter their creativity, or lower their potential to revitalize the economy. There are potential synergies with macro-prudential policies focused on mitigating systemic risk and ensuring the stability of financial systems. These platforms have great potential for cross-border lending and investment and could help to remedy the retreat of bank capital behind national borders since the financial crisis. It is time for a new perspective grounded in an “innovation-friendly” philosophy and regulatory approach to emerge.

Crowdfunding is a newcomer to the financial industry, and as such, actions (such as complex and burdensome regulatory frameworks or high levels of guaranteed compensation for losses) that could close it down or raise high barriers of entry should be avoided. Competition in the interests of the consumer and of entrepreneurs looking for funding should be encouraged. Regulators should be ready to step in if abuses do, or threaten to, arise while leaving space for new ideas around crowdfunding to gain traction rapidly, without being overburdened by regulatory requirements at an early stage.

The interests of both “financing innovation” and “innovation in the financial sector” also coincide in the FinTech entrepreneurial community. Schumpeter wrote in 1942: “[the] process of Creative Destruction is the essential fact about capitalism. It is what capitalism consists in and what every capitalist concern has got to live in.” An economy’s dynamism depends on innovative competitors challenging, and if successful, taking the place of complacent players in the markets. Keeping with the theme of Schumpeterian creative destruction, the financial sector is one seen by banking sector analysts and commentators as being particularly ripe for disruptive innovation, given its current profits and lax competition. Technology-driven disintermediation of many financial services is on the cards, for example, in financial advice, lending, investing, trading, virtual currencies and risk management.

The UK’s Financial Conduct Authority’s regulatory dialogues with FinTech developers to provide legal clarity on the status of their new initiatives are an example of good practice , as regulation in this highly monitored sector is potentially a serious barrier to entry and new innovation. The FCA also proactively addresses enabling innovation with Project Innovate, an initiative to assist both start-ups and established businesses in implementing innovative ideas in the financial services markets through an Incubator and Innovation Hub.

By its nature, FinTech is a sector that can benefit and benefit from the EU’s Digital Single Market and make Europe a sectoral global leader in this field. In evaluating possible future FinTech regulation, we need to ensure an optimal regulatory framework and specific rules. The innovation principle I discuss in my article should be part of an approach ensuring not only that regulation is clear and proportional — so that innovators can easily comply — but also ensuring that we are ready, when justified, to adapt regulation to enable innovations. Furthermore, any regulatory approaches should be “future proofed” and should not lock in today’s existing technologies, business models or processes.

Read the full article: Zilgalvis, P. (2014) The Need for an Innovation Principle in Regulatory Impact Assessment: The Case of Finance and Innovation in Europe. Policy and Internet 6 (4) 377–392.

Pēteris Zilgalvis, J.D. is a Senior Member of St Antony’s College, University of Oxford, and an Associate of its Political Economy of Financial Markets Programme. In 2013-14 he was a Senior EU Fellow at St Antony’s. He is also currently Head of Unit for eHealth and Well Being, DG CONNECT, European Commission.