Economics

The actions by law enforcement were deliberately structured to seed distrust in illicit trading platforms. Did this effort succeed?

You may have seen the news earlier this year that two large darknet marketplaces, Alphabay and Hansa, have been taken down by international law enforcement. Particularly interesting about these takedowns is that they were deliberately structured to seed distrust among market participants: after Alphabay closed many traders migrated to Hansa, not aware that it had already covertly been taken over by the police. As trading continued on this smaller platform, the Dutch police and their peers kept track of account logins, private messages, and incoming orders. Two weeks later they also closed Hansa, and revealed their successful data collection efforts to the public. Many arrests followed. The message to illicit traders: you can try your best to stay anonymous, but eventually we will catch you. By coincidence, our small research team of Joss Wright, Mark Graham, and I had set out earlier in the year to investigate the economic geography of darknet markets. We had started our data collection a few weeks earlier, and the events took us by surprise: it doesn’t happen every day that a primary information source gets shut down by the police. While we had anticipated that some markets would close during our investigations, it all happened rather quickly. On the other hand, this also gave us a rare opportunity to observe what happens after such a takedown. The actions by law enforcement were deliberately structured to seed distrust in illicit trading platforms. Did this effort succeed? Let’s have a look at the data. The chart above shows weekly trading volumes on darknet markets for the period from May to July 2017. The black line shows the overall trading volume across all markets we observed at the time. Initially, Alphabay (in blue) represented a significant share of this overall trade, while Hansa (in yellow) was comparably small. When Alphabay was closed in week 27, overall sales dropped: many traders lost their primary market. The following week,…

The US accounts for almost 40% of global darknet trade, with Canada and Australia at 15% and 12%, respectively.

My colleagues Joss Wright, Martin Dittus and I have been scraping the world’s largest darknet marketplaces over the last few months, as part of our darknet mapping project. The data we collected allow us to explore a wide range of trading activities, including the trade in the synthetic opioid Fentanyl, one of the drugs blamed for the rapid rise in overdose deaths and widespread opioid addiction in the US. The map shows the global distribution of the Fentanyl trade on the darknet. The US accounts for almost 40% of global darknet trade, with Canada and Australia at 15% and 12%, respectively. The UK and Germany are the largest sellers in Europe with 9% and 5% of sales. While China is often mentioned as an important source of the drug, it accounts for only 4% of darknet sales. However, this does not necessarily mean that China is not the ultimate site of production. Many of the sellers in places like the US, Canada, and Western Europe are likely intermediaries rather than producers themselves. In the next few months, we’ll be sharing more visualisations of the economic geographies of products on the darknet. In the meantime you can find out more about our work by Exploring the Darknet in Five Easy Questions. Follow the project here: https://www.oii.ox.ac.uk/research/projects/economic-geog-darknet/ Twitter: @OiiDarknet

Martin Dittus is a Data Scientist at the Oxford Internet Institute. The stringent ethics process governing his research means he currently can’t even contact anyone on the marketplace.

We’re sitting upstairs, hunched over a computer, and Martin is showing me the darknet. I guess I have as good an idea as most people what the darknet is, i.e. not much. We’re looking at the page of someone claiming to be in the UK who’s selling “locally produced” cannabis, and Martin is wondering if there’s any way of telling if it’s blood cannabis. How would you go about determining this? Much of what is sold on these markets is illegal, and can lead to prosecution, as with any market for illegal products. But we’re not buying anything, just looking. The stringent ethics process governing his research means he currently can’t even contact anyone on the marketplace. [Read more: Exploring the Darknet in Five Easy Questions] Martin Dittus is a Data Scientist at the Oxford Internet Institute, and I’ve come to his office to find out about the OII’s investigation (undertaken with Mark Graham and Joss Wright) of the economic geographies of illegal economic activities in anonymous Internet marketplaces, or more simply: “mapping the darknet.” Basically: what’s being sold, by whom, from where, to where, and what’s the overall value? Between 2011 and 2013, the Silk Road marketplace attracted hundreds of millions of dollars worth of bitcoin-based transactions before being closed down by the FBI, but relatively little is known about the geography of this global trade. The darknet throws up lots of interesting research topics: around traffic in illegal wildlife products, the effect of healthcare policies on demand for illegal prescription drugs, whether law enforcement has (or can have) much of an impact, questions around the geographies of trade (e.g. sites of production and consumption), and the economics of these marketplaces—as well as the ethics of researching all this. OII researchers tend to come from very different disciplinary backgrounds, and I’m always curious about what brings people here. A computer scientist by training, Martin first worked as a software developer…

We caught up with Martin Dittus to find out some basics about darknet markets, and why they’re interesting to study.

Darknet marketplaces are typically set up to engage in the trading of illicit products and services, and are considered criminal in most jurisdictions. Image: Dennis Yip (Flickr).

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…

It’s important that we take a multi-perspective view of the role of digital platforms in contemporary society.

Digital platforms strongly determine the structure of local interactions with users; essentially representing a totalitarian form of control. Image: Bruno Cordioli (Flickr CC BY 2.0).

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 formalised 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-subsidisation. By contrast, if we consider ownership and organisational control, we’ll observe issues of consolidation, privatisation, enclosure, financialisation 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, colonisation, 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…

The review assesses changes in labour markets and employment practices, and proposes policy solutions.

The Taylor Review of Modern Working Practices in the UK was published last week. The review assesses changes in labour markets and employment practices, and proposes policy solutions. One of the big themes in the report is the rise of platform-mediated gig work. I have been doing research on platform-mediated work for a few years now, and am currently leading a major European Research Council funded research project on the topic. This article is my hot take on some of the topics covered in the report. Overall the report takes a relatively upbeat view of the gig economy, but engages with its problematic points as well. A third way in employment classification In the U.S. policy debate around the gig economy, many have called for a ‘third category’ between protected employment and unprotected self-employment. The interesting thing is that in the UK such a category already exists. An employment tribunal decision last year determined that Uber drivers were not employees or contractors, but ‘workers’, enjoying some of the benefits of employment but not all. The review recommends making use this ‘worker’ category and renaming it ‘dependent contractor’. The review calls for greater emphasis on control over one’s work as a factor in determining whether someone is a ‘dependent contractor’ or genuinely self-employed. The question of control has featured prominently in recent research on gig economy platforms (see, for example: Rosenblat & Stark 2016, Graham et al. 2017). Uber promises freedom, but in practice uses a variety of nudges and constraints to manage workers quite closely. Platforms for digitally delivered work like graphic design don’t necessarily try to control the workers in the same way at all. So focusing on control can help distinguish between the employment status implications of different platforms, which can be quite different. Of course, the fact that someone is genuinely self-employed doesn’t necessarily mean that they are well off. Self-employed people are often relatively poor and…

Considered to be a successful example of empowered democratic governance, participatory budgeting has spread among many cities in Brazil.

Image: a youth occupation of Belo Horizonte to present and discuss different forms of occupation of urban space, by upsilon (Flickr CC BY-SA).

There is a general understanding that public decision-making could generate greater legitimacy for political decisions, greater trust in government action and a stronger sense of representation. One way of listening to citizens’ demands and improving their trust in politics is the creation of online communication channels whereby issues, problems, demands, and suggestions can be addressed. One example, participatory budgeting, is the process by which ordinary citizens are given the opportunity to make decisions regarding a municipal budget, by suggesting, discussing, and nominating projects that can be carried out within it. Considered to be a successful example of empowered democratic governance, participatory budgeting has spread among many cities in Brazil, and after being recommended by the World Bank and UN-Habitat, also implemented in various cities worldwide. The Policy & Internet article “Do Citizens Trust Electronic Participatory Budgeting? Public Expression in Online Forums as an Evaluation Method in Belo Horizonte” by Samuel A. R. Barros and Rafael C. Sampaio examines the feelings, emotions, narratives, and perceptions of political effectiveness and political representation shared in these forums. They discuss how online messages and feelings expressed through these channels can be used to assess public policies, as well as examining some of the consequences of ignoring them. Recognised as one of the most successful e-democracy experiences in Brazil, Belo Horizonte’s electronic participatory budgeting platform was created in 2006 to allow citizens to deliberate and vote in online forums provided by the city hall. The initiative involved around 174,000 participants in 2006 and 124,000 in 2008. However, only 25,000 participants took part in the 2011 edition, indicating significant loss of confidence in the process. It is a useful case to assess the reasons for success and failure of e-participation initiatives. There is some consensus in the literature on participants’ need to feel that their contributions will be taken into consideration by those who promote initiatives and, ideally, that these contributions will have effects and practical…

Basic income is an interesting solution for the gig economy, because it addresses its problems from a new angle.

Platforms like eBay, Uber, Airbnb, and Freelancer are thriving, growing the digital economy and disrupting existing business. The question is how to ensure that the transformations they entail have a positive impact on society. Here, universal basic income may have a role to play. Few social policy ideas are as hot today as universal basic income. Social scientists, technologists, and politicians from both ends of the political spectrum see it as a potential solution to the unemployment that automation and artificial intelligence are expected to create. It has also been floated as a potential solution to the rise of the gig economy, where work is centred around on-demand tasks and short-term projects as opposed to regular full-time employment. This is the kind of employment that platforms like Uber and Freelancer are based on. Automation and the gig economy are actually closely linked. Isolating and codifying a job task in such a way that it can be outsourced to a gig worker can be the first step towards automating that task. Once a task has been automated, gig workers are used to train and supervise the algorithm. Meanwhile, expert online contractors are hired to fine-tune the technology. More often than not, a finished artificial intelligence system is actually an ensemble of machines and human workers acting in concert. Basic income is an interesting solution for the gig economy, because it addresses its problems from a new angle. One of the most problematic aspects of the gig economy has to do with its negative job characteristics. Though gig work can provide autonomy and good earnings for some, it also involves uncertainty and insecurity, and for many can entail working antisocial hours for little pay. A sort of default policy response therefore tends to be to regulate gig work back into the mould of standard employment, consisting of things like guaranteed working hours and notice periods. Basic income takes a different angle. It…

Are there ways in which the data economy could directly finance global causes such as climate change prevention, poverty alleviation and infrastructure?

“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…

Applying elementary institutional economics to examine what blockchain technologies really do in terms of economic organisation, and what problems this gives rise to.

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 organisation”. 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 “revolutionise 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 organisation, 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. 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…