In my copy of The Vocation Lectures, edited by David Owen and Tracy B. Strong, the editors helpfully annotate Weber’s description of the occupational realities of the German academic. From pg 2:

German students used to have a Studienbuch, a notebook in which they registered the coruses they were taking in their field. They then had to pay a fixed fee for each course. For staff on a full salary – that is, professors – these tuition fees were a welcome extra. For the unsalaried Privatdozent, these fees were the sole source of income. Science as a Vocation, pg 2. 

Is this where the Uberfication of the University could lead? I find it easy to imagine a Digital Studienbuch, the killer app of educational disrupters, dispersed throughout the university system. Universities would still exist to manage the ‘student experience’, control the academics and provide infrastructure. Perhaps there would still be paid professors to replenish the knowledge system and train the Privatdozent. But the university wouldn’t be the platform, instead it would be a whole series of arenas (with declining influence as the system became embedded), facilitating extraction from a relationship between teacher and taught on the part of a distant technology company.

Weber’s description of the academic career in Germany, “generally based on plutocratic premises”, seems eerily familiar from a contemporary vantage point:

For it is extremely risky for a young scholar without private means to expose himself to the conditions of an academic career. He must be able to survive at least for a number of years without knowing whether he has any prospects of obtaining ta position that will enable him to support himself.  Science as a Vocation, pg 2. 

In his Uberworked and Underpaid, Trebor Scholz draws out an important parallel between the platform capitalism of YouTube and the near universally praised Wikipedia:

Unsurprisingly, YouTube hires countless consultants to better understand how to trigger the participation of the crowd. They wonder how they can get unpaid producers to create value. But equally, on the not-for-profit site, Wikipedia is asking how they can draw in more female editors, for instance.

Both involve an orientation to their users which sees them as objects of management, even if we might see the ends to which they are being managed in very different terms. This makes a lie of what Nick Couldry describes as the ‘myth of us’: the imaginary of platform capitalism which sees it as facilitating the free expression of natural sociability which older socio-technical systems had constrained

One of the things that I liked about Platform Capitalism, by Nick Srineck, was its concern to avoid analysing the tech sector as sui generis. By situating it in social and economic history, we are left with a much richer account of where it came from, why it is the way it is and where it is going. The myth of exceptionalism concerning technology militates against this, as the protagonists of grand disruptive projects don’t take kindly to being regarded as mundane organisations driven by environmental constraints and enablements like all others. 

The consequences of this exceptionalism aren’t just analytical though. Exceptionalism licenses a view of the digital economy as disembedded, obscuring the manifold ways in which it is dependent on the wider context. This section from Uberpaid and Underworked, by Trebor Scholz, loc 1014 illustrates this powerfully:

Rarely acknowledged are also the networks of care that sustain contingent workers. Just for one moment, think about the families that are paying the price for just-in-time scheduling of work hours. Who is caring for their children when they face unpredictable work schedules, often decided only days or hours in advance? And let’s not forget that government programs like the Food Stamp Act of 1964, introduced by President Lyndon B. Johnson, are essential in providing subsistence for crowdworkers and Walmart “associates” alike. In this way, personal networks of care, global supply chains, American taxpayers, academia, and the military sustain the digital economy.

Recognising this context makes it easier to see the grim reality underlying the lofty rhetoric of the sharing economy. From loc 1290:

What if the engine of the “sharing economy” is not the instinct to share, but rather economic desperation? Just consider the 8–10 million Americans who are unemployed and the almost eight million who are working part-time because they cannot find full-time work, according to the Bureau of Labor Statistics. 78 They are piecing together a living wage by working with companies like Uber but only few make a good living in the Hunger Games.

In Platform Capitalism, Nick Srnicek seeks to address what he sees as a profound oversight in the existing literature on digital capitalism. One set of contributions focuses on emerging technologies and their implications for privacy and surveillance but ignores the economic analysis of ownership and profitability. Another set critically analyses the values embodied in corporate behaviour but neglects the broader context of a capitalist system. A further set addresses the ills of the ‘sharing economy’ but fails to situate these in terms of broader economic trends. Finally, there are those which analyse the emerging economic trends in the technology sector but treat them in a way which is decontextualised from wider historical changes.

In contrast, he intends to offer “an economic history of capitalism and digital technology, while recognising the diversity of economic forms and the competitive tensions inherent in the contemporary economy” (loc 155). This involves “abstracting from them as cultural actors defined by the values of the Californian ideology, or as political actors seeking to wield power” (loc 166) and instead simply taking “major tech companies” as “economic actors within a capitalist mode of production”. Such an undertaking requires that we distinguish the technology sector from the digital economy. The former is relatively small, employing around 2.5% of the US labour force and contributing around 6.8% of the value added by private companies (loc 157). In contrast, the digital economy has taken on a systemic importance that is obscured if we analyse it on a sectoral basis:

we can say that the digital economy refers to those businesses that increasingly rely upon information technology, data, and the internet for their business models. This is an area that cuts across traditional sectors –including manufacturing, services, transportation, mining, and telecommunications –and is in fact becoming essential to much of the economy today. Understood in this way, the digital economy is far more important than a simple sectoral analysis might suggest. In the first place, it appears to be the most dynamic sector of the contemporary economy –an area from which constant innovation is purportedly emerging and that seems to be guiding economic growth forward. The digital economy appears to be a leading light in an otherwise rather stagnant economic context. Secondly, digital technology is becoming systematically important, much in the same way as finance. As the digital economy is an increasingly pervasive infrastructure for the contemporary economy, its collapse would be economically devastating. Lastly, because of its dynamism, the digital economy is presented as an ideal that can legitimate contemporary capitalism more broadly. The digital economy is becoming a hegemonic model: cities are to become smart, businesses must be disruptive, workers are to become flexible, and governments must be lean and intelligent.

Loc 157-178

His analysis locates the nascent importance of the digital economy against a backdrop of a “long decline in manufacturing probability” across a “sluggish production sector”. Digitalisation has been seized upon a set of mechanisms through which these problems might be ameliorated, leading to the growth of the platform as the business model best able to ensure returns from these emerging opportunities (loc 178). This represents a historicisation of the platform, drawing out the linkages between the contemporary platforms which dominate the breathless discourse of ‘disruption’ and earlier upheavals in capitalism which digitalisation played an (often under-acknowledged) part in. For instance, consider the technological prerequisites which allowed a transition from Fordism to post-Fordism, driven by a crisis of overcapacity and overproduction in global markets:

Companies were increasingly told by shareholders and management consultants to cut back to their core competencies, any excess workers being laid off and inventories kept to a minimum. This was mandated and enabled by the rise of increasingly sophisticated supply chain software, as manufacturers would demand and expect supplies to arrive as needed. And there was a move away from the mass production of homogeneous goods and towards increasingly customised goods that responded to consumer demand.

Loc 294

The point is not that technology was the agent of these changes but rather that it facilitated new ways of organising production in time and space. Recognising the political agency involved in the onset of neoliberal ‘reforms’ shouldn’t detract from an appreciation of the role technology played in allowing the reorganisation of production. Historicising the digital economy necessitates that we understand this interplay between digitalisation and financialisation from the outset, something which of course came to the fore with the dot com boom. 

Astonishingly, nearly 1% of US GDP consisted of VC invested in tech companies at the height of the sector in the late 1990s, with 50,000 companies formed and over $256 billion invested in them. This influx of capital facilitated a ‘growth before profits’ model which is still familiar today, licensed by the expectations of immense wealth to be generated if enough market share was captured in a still hazily envisioned digital economy. This speculative boom led to a vast investment in digital infrastructure through which our contemporary digital economy was able to emerge:

This excitement about the new industry translated into a massive injection of capital into the fixed assets of the internet. While investment in computers and information technology had been going on for decades, the level of investment in the period between 1995 and 2000 remains unprecedented to this day. In 1980 the level of annual investment in computers and peripheral equipment was $ 50.1 billion; by 1990 it had reached $ 154.6 billion; and at the height of the bubble, in 2000, it reached an unsurpassed peak of $ 412.8 billion. 16 This was a global shift as well: in the low-income economies, telecommunications was the largest sector for foreign direct investment in the 1990s –with over $ 331 billion invested in it. Companies began spending extraordinary amounts to modernise their computing infrastructure and, in conjunction with a series of regulatory changes introduced by the US government, 18 this laid the basis for the mainstreaming of the internet in the early years of the new millennium. Concretely, this investment meant that millions of miles of fibre-optic and submarine cables were laid out, major advances in software and network design were established, and large investments in databases and servers were made.

Loc 314-333

Coping with the eventual crash through lowering mortgage rates in turn sowed the seeds of the future housing bubble. The story is one of a continued ‘asset-price Keynesianism’ where interest rate reductions were used to encourage continued rises in asset prices, seeking to encourage investment and consumption in the absence of deficit financed stimulus or any resurgence in the manufacturing sector. This low interest rate environment within the global economy has, argues Srnicek, provided “a  key enabling condition for parts of today’s digital economy to arise” (loc 377) by reducing returns on a range of assets and encouraging investors to seek higher yields elsewhere. This is the context within which platforms emerged and were readily able to find vast investment, even in the absence of profitability. But what are platforms?

What are platforms? At the most general level, platforms are digital infrastructures that enable two or more groups to interact. They therefore position themselves as intermediaries that bring together different users: customers, advertisers, service providers, producers, suppliers, and even physical objects. More often than not, these platforms also come with a series of tools that enable their users to build their own products, services, and marketplaces. Microsoft’s Windows operating system enables software developers to create applications for it and sell them to consumers; Apple’s App Store and its associated ecosystem (XCode and the iOS SDK) enable developers to build and sell new apps to users; Google’s search engine provides a platform for advertisers and content providers to target people searching for information; and Uber’s taxi app enables drivers and passengers to exchange rides for cash. Rather than having to build a marketplace from the ground up, a platform provides the basic infrastructure to mediate between different groups. This is the key to its advantage over traditional business models when it comes to data, since a platform positions itself between users, and as the ground upon which their activities occur, which thus gives it privileged access to record them.

Loc 596-618

He identifies three key characteristics of platforms which are interconnected:

  1. Platforms mediate interaction between groups, providing an epistemic privilege in relation such interactions (and their potential monetisation). They are a mechanism for producing and extracting data from interactions.
  2. Platforms are reliant on network effects, such that their value to users grows in line with the number of such users. This leads to a ‘winner-takes-all’ or ‘winner-takes-most’ dynamic. The more a platform grows, the easier it is for it to grow more and the potential value of its epistemic privilege increases in line with this.
  3. Platforms often use cross-subsidisation to encourage more users on to the network, exhibiting a dynamic pricing structure often entailing free products and services because of the gains that can be made elsewhere. This helps encourage more users on to the platform.

The mediating character of platforms means they “gain not only access to more data but also control and governance over the rules of the game” (loc 636). With this comes the challenge of facilitating continued growth within a competitive environment, using cross-subsidisation and leveraging network effects to position oneself as the central platform within a domain of activity. However in spite of these shared characteristics, different types of platform have emerged within different spheres of social life. Srnicek identifies 5 types:

The first type is that of advertising platforms (e.g. Google, Facebook), which extract information on users, undertake a labour of analysis, and then use the products of that process to sell ad space. The second type is that of cloud platforms (e.g. AWS, Salesforce), which own the hardware and software of digital-dependent businesses and are renting them out as needed. The third type is that of industrial platforms (e.g. GE, Siemens), which build the hardware and software necessary to transform traditional manufacturing into internet-connected processes that lower the costs of production and transform goods into services. The fourth type is that of product platforms (e.g. Rolls Royce, Spotify), which generate revenue by using other platforms to transform a traditional good into a service and by collecting rent or subscription fees on them. Finally, the fifth type is that of lean platforms (e.g. Uber, Airbnb), which attempt to reduce their ownership of assets to a minimum and to profit by reducing costs as much as possible.

Loc 657

Much of his subsequent analysis concerns the competitive conditions under which each type of platform operates, as well as how this is shaping the emerging field and platform capitalism as a whole. I don’t agree with all of it but it’s definitely worth reading in full. I understand his core points to be the following:

  1. The necessity of ‘data extraction’ has a basis in a longer term crisis of profitability within capitalism. These are, in effect, technical fixes for a systemic deterioration afflicting manufacturing and platforms represent a formalisation of these into a new emergent form.
  2. The financial conditions under which this platform economy has been able to emerge were historically specific and should not be assumed to continue indefinitely. The infrastructure through which ‘data extraction’ become technically viable, as well as the emergence of platforms as operating businesses were deeply dependent upon this.
  3. Platforms as emergent forms exhibit characteristics which shape competition between them, as well as guiding the unfolding of the digital economy as a whole. The fierce competition between them, the competitive challenges specific to categories of platforms, the dynamics of network effects and the affordances of their cash hoarding are leading to platform isomorphism. They have an inevitable drive towards monopoly, further incentivised by the dynamics of accruing investment, which leaves them orientated towards becoming owners of the infrastructure of society.

The analysis of platform tendencies is probably my favourite part of the book. He talks about expansion of extraction, positioning as a gatekeeper, convergence of markets and enclosure of ecosystems. These are analysed in the final chapter in some detail and offer a convincing meso-level account of the claimed macro tendency towards monopoly or oligopoly.

There’s an excellent discussion in Nick Srnicek’s Platform Capitalism of the immense cash reserves that technology companies have built up in recent years. As he notes, the headline figures don’t tell the whole story because these reserves don’t take into account the other debts and liabilities of these corporations. But the broader financial context is one in which, due to low corporate yields, it’s cheaper to take on new debt rather than bringing these cash reserves back on shore and having them be subject to corporation tax.

screen-shot-2017-01-12-at-17-14-21
From loc 442

Recognising these points seems extremely important to understanding this corporate behaviour. Much of the ambition of the book is to see technology companies in terms of a broader post-crisis political economy and this is why the caveats on the headline figures of cash reserves are so crucial. These behaviours do not emerge sui generis from the technology sector but rather reflect corporations acting rationally within a more expansive context.

The public perception of the corporations in question, as well as the shiny and attention-grabbing investments they make with these cash reserves, create a tendency to evaluate them in their own terms. But these behaviours reflect economic mechanisms which are not unique to the technology sector. As Srnicek notes, “the use of corporate debt by these companies therefore needs to be set in the context of a tax avoidance strategy” (loc 442). These two conditions are crucial to these behaviour: (a) low corporate yields and the capacity to take on debt afforded by them (b) off-shoring of wealth and large scale avoidance of corporation tax. Both conditions are central to our post-crisis political economy rather than being sectoral phenomena.

Understanding this macro-economic context helps avoid the aforementioned trend of seeing the technology sector in sui generis terms. Yes, it’s new and shiny, but these are still corporations within a capitalist system, albeit one currently undergoing systemic change. To understand these changes, what Srnicek calls ‘platform capitalism’ and what I tend to think of as ‘digital capitalism’, requires that we cut through the thickets of bullshit which are being promulgated about the ‘digital age’. He writes on loc 536:

Since the 2008 crisis, has there been a similar shift? The dominant narrative in the advanced capitalist countries has been one of change. In particular, there has been a renewed focus on the rise of technology: automation, the sharing economy, endless stories about the ‘Uber for X’, and, since around 2010, proclamations about the internet of things. These changes have received labels such as ‘paradigm shift’ from McKinsey1 and ‘fourth industrial revolution’ from the executive chairman of the World Economic Forum and, in more ridiculous formulations, have been compared in importance to the Renaissance and the Enlightenment. 2 We have witnessed a massive proliferation of new terms: the gig economy, the sharing economy, the on-demand economy, the next industrial revolution, the surveillance economy, the app economy, the attention economy, and so on. The task of this chapter is to examine these changes.

Understanding cash hoarding is central to moving beyond this breathless discursive explosion because it’s what facilitates many of the shiniest investments which appear to be at frontier of the ‘digital revolution’. It also facilitates the early acquisition of potential competitors, bringing them into the fold and often liberating them of their technology long before they might come to rival the platform giant. Cash hoarding protects from project uncertainty, facilitating open-ended investments in developments that lack a quantifiable market. But all the these factors which operate at the level of innovation need to be seen in terms of a political economy within which this corporate ‘autonomy’ becomes feasible and widespread.

It would be a mistake however to dismiss talk of ‘disruption’ and ‘innovation’ as epiphenomenal. Firstly, real innovations are underway, albeit ones which are pervasively mischaracterised as the linear unfolding of technological mastery rather than an uneven and lop-sided progress driven by the weird dynamics of the tech sector, distorted by the aforementioned vortex created by the new platform overlords. Secondly, innovation talk has become all pervasive within organisations, performing an important culture role that can’t be adequately understood if we simply subsume it under the category of ‘ideology’:

A search of annual and quarterly reports filed with the Securities and Exchange Commission shows companies mentioned some form of the word “innovation” 33,528 times last year, which was a 64% increase from five years before that.

More than 250 books with “innovation” in the title have been published in the last three months, most of them dealing with business, according to a search of Amazon.com.

http://www.wsj.com/articles/SB10001424052702304791704577418250902309914

Technology concerns aren’t necessarily the worst offenders. AppleInc. and Google Inc. mentioned innovation 22 times and 14 times, respectively, in their most recent annual reports. But they were matched by Procter & Gamble Co. (22 times), Scotts Miracle-Gro Co.(21 times) and Campbell Soup Co. (18 times).

http://www.wsj.com/articles/SB10001424052702304791704577418250902309914

The pervasive discourse of ‘innovation’ and ‘disruption’ helps mystify fundamental changes in capitalism, propped up by even more pervasive ideas of open/closed, fast/slow and modern/traditional. But it also does important work at a meso-social level, not least of all within higher education:

Equally, in a world where academics are obliged to offer up each piece of work to be evaluated as internationally significant, world leading etc., they will seek to signal such a rating discursively. A study by Vinkers et al. in the British Medical Journal uncovered a new tendency towards hyperbole in scientific reports. They found the absolute frequency of positive words increased from 2.0% (1974-80) to 17.5% (2014), which amounts to a relative increase of 880% over four decades. 25 individual positive words contributed to the increase, particularly the words “robust,” “novel,” “innovative,” and “unprecedented,” which increased in relative frequency up to 15 000%”). The authors comment upon an apparent evolution in scientific writing to ‘look on the bright side of life’.

https://www.thesociologicalreview.com/blog/the-rise-of-the-trump-academic.html

We need to cut through this rhetoric, understanding its cumulative macro-cultural effects while also recognising the performative work it does across organisations and civil society. Doing so will inevitably be a complex exercise but it’s an important one. Doing this goes hand-in-hand with an account of digitalisation at the level of political economy rather than simply technology. This is what I take Srnicek to be doing on loc 568:

Data are not immaterial, as any glance at the energy consumption of data centres will quickly prove (and the internet as a whole is responsible for about 9.2 per cent of the world’s electricity consumption). 6 We should also be wary of thinking that data collection and analysis are frictionless or automated processes. Most data must be cleaned and organised into standardised formats in order to be usable. Likewise, generating the proper algorithms can involve the manual entry of learning sets into a system. Altogether, this means that the collection of data today is dependent on a vast infrastructure to sense, record, and analyse. 7 What is recorded? Simply put, we should consider data to be the raw material that must be extracted, and the activities of users to be the natural source of this raw material. 8 Just like oil, data are a material to be extracted, refined, and used in a variety of ways. The more data one has, the more uses one can make of them. Data were a resource that had been available for some time and used to lesser degrees in previous business models (particularly in coordinating the global logistics of lean production). In the twenty-first century, however, the technology needed for turning simple activities into recorded data became increasingly cheap; and the move to digital-based communications made recording exceedingly simple. Massive new expanses of potential data were opened up, and new industries arose to extract these data and to use them so as to optimise production processes, give insight into consumer preferences, control workers, provide the foundation for new products and services (e.g. Google Maps, self-driving cars, Siri), and sell to advertisers.

But what I find odd about this is it how it adopts the trope of ‘data as new oil’ without critically examining its embedding in the aforementioned rhetoric of disruption and innovation. I’m not yet sure if this is a disagreement with Srnicek’s argument or simply a request for further analysis. But I’m thus far finding the book thought provoking and highly recommend it.

This struck me as an interesting case that reveals a broader truth about the sharing economy. A description of the very early merger of two companies offering city wide access to unused capacity in fitness classes, from Sweat Equity, by Jason Kelly, loc 1343:

“When you look at quality fitness inventory in each city, there aren’t thousands of studios,” Kapoor says. “You’re talking in the hundreds range, so the supply is limited. It’s difficult for more than one marketplace to win aggregating this type of supply. We asked ourselves, ‘Do we want to go head to head like Uber and Lyft? Maybe it makes sense to come together. It doesn’t seem like it’s going to help the industry for us to spend time and resources fighting each other versus focusing on our partners and consumers.’”

The evolution of one of the two companies is itself quite interesting, detailed on the same location in the book:

Founder Kadakia created the company, initially called Classtivity, as a one-time (one-month) sampler; the service was called the Passport, and it allowed the user to try out various workouts with the assumption that she’d settle on a favorite and join up. The Passport holder was entitled to skip around, depending on mood and availability of classes, and pick what to do that day. One New York magazine writer dubbed it “How to have an open relationship with exercise.” It was such a good idea that people wanted to do it for more than a month.

The author makes the interesting point that the transitory nature of the ensuing experience erodes the shared experiences which he argues are integral to understanding the fitness boom. From loc 1374:

One thing ClassPass lacks is a community. Sure, there are lots of ClassPassers running around, and users may collude by text and e-mail to grab a couple of free spots in the same cycling or barre class. But ClassPass removes a key element of what makes so many of its client boutiques so attractive in the first place—the ability to show up, on a regular basis, with your people.

One of the most interesting developments in the so-called sharing economy is the growing tendency for the largest of these companies to try and mobilise their users as lobbying and protest groups at the municipal level

But when Airbnb’s executives look out at the world, they don’t see a fragmented puzzle of local politics and planning codes. They see Moscow, where Russians are renting out rooms on Airbnb as a means of surviving the country’s current recession. They see Havana, where Cubans were listing their homes in droves https://nextcity.org/features/view/cuba-airbnb-houses-for-rent-sharing-economy-havana. They see, as Lehane said to a room full of reporters over breakfast the morning after the election, a global network of guests and hosts that, if politically organized by and in favor of the company, could be enormously powerful.

And so organizing and training them is exactly what Airbnb plans to do, using its victory in San Francisco to unite Airbnb’s most passionate users into a series of clubs in cities around the world. The goal is to have created 100 of them by 2016. When election season rolls around that year, legions of customer advocates will be ready and waiting to come out against any group or individual who doesn’t wholeheartedly embrace Airbnb and what it stands for.

http://www.buzzfeed.com/carolineodonovan/the-road-forward-for-airbnb?utm_term=.bc5407K9g#.cj2mP6j0Q

This would always be sinister in-and-of-itself. But what really worries me is the dependency and/or loyalty of these users and how that may play itself out politically as this trend develops. I just came across this remarkable devotional essay: Why I’m thankful for the sharing economy.

At the end of the day, the sharing economy is the most necessary thing I need to survive. Not a day goes by without my pulling out my phone and tapping a couple apps to make my life in this crazy world a little bit easier

http://vator.tv/news/2015-11-26-why-i-m-thankful-for-the-sharing-economy#rX3SZo23vhE1f04Y.99

How many people experience these companies as something essential for their day-to-day life? This strikes me as a really urgent empirical question, particularly given the aforementioned political questioned posed by the increasingly aggressive lobbying of these companies in municipalities throughout the world.

Location: Thursday 22 – Friday 23 September 2016, University of Oxford.
Convenors: Helen Margetts (OII), Vili Lehdonvirta (OII), Jonathan Bright (OII), David Sutcliffe (OII), Andrea Calderaro (EUI / ECPR).
Abstract deadline: 14 March 2016.
Contact: policyandinternet@oii.ox.ac.uk

This conference is convened by the Oxford Internet Institute for the OII-edited academic journalPolicy and Internet, in collaboration with the European Consortium of Political Research (ECPR) standing group on Internet and Politics.

Rationale

Large scale internet platforms such as Google, Facebook, Amazon and Uber play an increasingly important role in contemporary society. These platforms facilitate connections between friends and family members, between politicians and voters, between governments and citizens, between consumers and producers, and between employers and employees. As such, they are becoming venues where large segments of contemporary life are played out.

The data collected and in some cases made openly available by these platforms creates huge opportunities for advancing research in many fields of social science. Exciting advances have already been made in understanding, for example, how information spreads across networks and the importance of social influence on personal action. Yet researchers have only scratched the surface of the possibilities offered by new data sources and analysis methods.

At the same time, the decisions made by these platforms increasingly shape contemporary life.Whether taking employment through Upwork, purchasing goods on Amazon, seeking information via Google, remitting money via PayPal, or debating politics on Twitter or joining a campaign on change.org our actions are enabled and constrained by sophisticated algorithms and company policies. Meanwhile, the concept of ‘government as a platform’ offers the potential to reshape the entire policy-making environment. The decisions, assumptions and interests reflected in these algorithms and platforms will have significant consequences for society at large, yet understanding of these processes is still very limited.

Topics

The aim of this conference is to bring together scholars studying platforms, both in terms of interactions taking place on platforms and the data they generate, as well as the platforms themselves and how they are shaped and operated. We welcome theoretical as well as empirical, qualitative as well as quantitative studies, from all disciplines that can provide useful perspectives on the contemporary “platform society”. Topics of interest include but are not limited to:

  • Data driven studies of platform-mediated interactions (e.g. using APIs or scraped data)
  • The viability, opportunities and challenges of ‘government as a platform’
  • Studies of how algorithms and user interfaces shape interactions (e.g. STS, HCI)
  • Impacts of platforms in a given industry or government area (e.g. taxis, local gov)
  • Formal economic modeling of platform competition, strategy and policy
  • Political mobilization around platforms (e.g. Uber and AirBnB protests)
  • Open source and distributed platforms and their politics (e.g. Bitcoin, blockchain)
  • Innovation and entrepreneurship in platform marketplaces (e.g. App Store, Google Play)
  • Issues in research use of platforms (e.g. Mechanical Turk survey practices)
  • Conflicts between public policy and platform rules (e.g. Google in Europe)
  • Studies of how platform firms manage platforms (e.g. theoretical, ethnographic)
  • Civic activism and mobilization platforms such as We the People petitions platform, change.org or Avaaz
  • Comparative studies of platforms (e.g. rules of Twitter vs. Facebook)
  • Public policy development related to platforms (e.g. EU Digital Single Market)
  • Transnational issues in platforms and digital markets (e.g. TTIP, safe harbor)
  • The ethics of algorithms and responsible innovation

Accepted papers will be organized into thematically and methodologically relevant sessions and parallel streams. 

Proposal submission

Paper proposals

Paper proposals should consist of a title and a 1,000-word extended abstract that specifies and motivates the research question, describes the methods and data used, and summarises the main findings. Abstracts will be peer reviewed, and the authors of accepted proposals are expected to submit full papers prior to the conference. Applicants will have the opportunity to co-submit their paper to the journal Policy and Internet, which will operate a fast-track review process for papers accepted to the conference.

Paper submissions can also be considered for a Best Paper Award (sponsored by the journal Policy and Internet). The prize will be awarded at the closing session of the conference. As the paper is intended to be published in a future issue of the journal, authors should indicate whether they would like their paper to be considered for the prize.

SUBMIT YOUR ABSTRACT HERE (deadline: 14 March 2016)

Poster proposals

Posters should summarise in a visually engaging manner the purpose, methods and results of an original piece of research. All accepted submissions will be considered for a Best Poster Award. The prize will be awarded at the closing session of the conference.

SUBMIT YOUR POSTER HERE (deadline: 14 March 2016)

Important dates

  • Extended abstract submission deadline: 14 March 2016
  • Decisions on abstracts: 2 May 2016
  • Full paper / poster submission deadline (for accepted abstracts): 1 September 2016
  • Conference dates: Thursday 22 – Friday 23 September 2016

This is a very interesting trend, though one I suspect could lead in some unfortunate directions:

Ever been the victim of plagiarism on Twitter—or, dare we say, the shameful purveyor of it? The social network seems to be putting an end to those pirated tweets by cracking down on users who steal jokes to inflate their Twitter cred.

The Twitter account @plagiarismbad reported Saturday that Twitter had taken down five tweets that poached a joke allegedly first posted by freelance writer Olga Lexell:

The tweets were removed at Lexell’s request, and in their place reads text that says they were “withheld in response to a report from the copyright holder.” In a tweet, Lexell explained the rationale behind her appeal, noting that the jokes were her “intellectual property” and copied without attribution

http://www.fastcompany.com/3049084/fast-feed/copied-someones-joke-on-twitter-your-tweet-may-be-deleted?partner=rss

It seems obviously valuable that a mechanism for this is in place, but it’s nonetheless worrying when one considers the potential scale of the contestation that might emerge when this becomes widespread. Will Twitter commit to providing the resources to ensure robust governance? Or will they merely err on the side of caution and take material down unless the arguments given in the counter-notice are overwhelmingly strong? On its own, this would be problematic. But as the article correctly identifies, the potential for such a system to be deliberately misused is vast:

This sounds like good news for writers and comedians who have been victims of joke theft, but as Twitter revealed in a transparency report last year, many organizations cry copyright theft even when the material in question does not meet those requirements. The Verge reports that about one-third of Twitter’s requests are not actually copyright violations—and some, in fact, are just attempts to censor criticism

http://www.fastcompany.com/3049084/fast-feed/copied-someones-joke-on-twitter-your-tweet-may-be-deleted?partner=rss