🇸🇪 Allseende ögat: Mina vänner Per och Eric samtalar om digital övervakningskapitalism

Myter och Mysterier är en podcast som vindlar sig vid sidan av de mediala och politiska allfarvägarna, längs de mystiska stigar vars mål inte alltid är klara ens för den som leder en längs dem. Utan nästan någon publicitet i de stora massmedierna har Eric Schüldt och Per Johansson lyckats skapa en enorm lyssnarskara – för det de säger är genuint, lärorikt och fantasieggande.

I senaste avsnittet förs ett fint samtal om den digitala utvecklingen de senaste åren, med utgångspunkt i Shoshana Zuboffs The age of Surveillance Capitalism. Och så tar de upp hur de träffades, och rollen jag själv faktiskt spelade i det. Avsnittet handlar om beteendedata, ”diskuterbarhetshorisonten”, digital kolonialism, och det sinistra i digital kapitalism. Sammanfattningsvis pekar det hela framåt, i psykologisk och andlig riktning, mot begärets roll i det hela.

Själv är jag ju så pass bortkopplad från Facebook och liknande (dock är jag mycket aktiv på Twitter som ni kanske vet), så jag hade helt missat att de hade en ny säsong nu. Det var inte förrän en vän tipsade mig om att mitt eget namn faktiskt nämndes i det här avsnittet som jag kollade upp det. Äntligen det efterlängtade temat kapitalism och makt! Ser fram emot de kommande avsnitten, inte minst det utlovade om mänskligt begär.

En koppling jag trodde de skulle göra är en liknande den David Rosen och Aaron Santesso gjorde för några år sedan, att Saurons allseende öga är en bättre metafor för vår tids övervakningskapitalism än vad till exempel George Orwells 1984 är. Det är när ringen blir buren som ögat aktiveras, väldigt snarlikt hur det är när du använder din smartphone som du blir övervakad.

Visst låter det deppigt? Men digitaliseringen förvandlar många delar av vår tids kapitalism till övervakningskapitalism. Samtidigt kan detta märkligt nog inge hopp – eftersom den är så prylbaserad är övervakningen sällan total och det finns vägar ut.

I världarna som modernistiska författare som Orwell, Aldous Huxley och Jevgenij Zamjatin skapar så är tankepolisen som Gud – den vet allt, hela tiden. Så tänkte inte den mer katolskt präglade Tolkien, som snarare ritar upp en värld där härskare med omnipotenta ambitioner trots allt har svagheter och blottor, även de.

Över lag kan jag annars tycka att Huxleys dystopi rätt väl fångar vår tid, i det att hotet idag handlar om “underhållning till döds”, för att parafrasera medievetaren Neil Postman, snarare än någon sorts Stalinistisk lydnadskultur, som Orwells dystopi handlar om. Och därtill är Franz Kafkas Processen oerhört träffande, vad beträffar den kategorisering-på-distans som blinda byråkratier gör, och som aldrig kan överklagas. Den typen av distanserad maktutövning är mardrömslik i sin egen rätt.

Per och Eric gör flera andra, väldigt intressanta observationer:

  • Liknelsen ”data är olja” kan överföras även till en naturreligiös dimension, där många naturreligioner* menar att det är våld mot skapelsen att exploatera jorden. Om vår tids ”olja” är persondata så är det moraliska argumentet att personens integritet är okränkbar en direkt parallell till denna tidigmoderna gruvdebatt.
  • Därtill, om persondata är en näring, en industri, så bör man rimligen fråga sig vad slaggprodukterna är. Vi kan prata om destruktiva fenomen som konsumerism som en slagprodukt med direkt negativ inverkan på de planetära ekosystemen, givet vår tids produktionsvillkor.
  • Helt klart är att psykologiska föreställningar om begäret är centrala. Mattas begäret mattas de destruktiva effekterna av den digitala kolonialismen.

Detta senare också en väg jag själv allt mer har börjat förespråka. En linje som handlar om att bygga ett andligt och kunskapsbaserat immunsystem, där resurser riktas mot att stärka det större mänskliga blomstrande som rimligen borde följa på detta. Denna linje går att överföra även på andra debatter, drogdebatten till exempel.

Det behöver inte alls handla om asketism, utan precis som Per antyder så kanske en annan väg är möjlig.

Kom ihåg, det är ju inget fel med att vara luddit. Luddism är ju den kanske mest missförstådda ismen av dem alla!

* ) Och även kristna, i varje fall fram till 1500-talets debatter om gruvdrift som våldförelse på Moder Jord. Carolyn Merchant har skrivit om detta i Naturens död (på svenska 1994).

🇬🇧 Platform Logic: An Interdisciplinary Approach to the Platform-Based Economy

In September 2016, I attended an excellent academic conference, The Platform Society, arranged by the great people at Oxford University’s Internet Institute. My paper, presented there, was later re-worked into this article.

The concept of platforms has emerged in recent years as one of the most important concepts of the digital economy. In brief, my article concludes that digital platforms enact different types of governance, by recourse to three levels of observation: micro, meso, and macro.

  • In the minute, discrete interactions between platforms and users, micro-level forms of technocratic control are enabled.
  • On the level of platform interoperability (the meso level), a range of generative outcomes are supported.
  • In global aggregate, a macro-level mode of geopolitical domination is enabled.

Over at Oxford University’s Policy and Internet blog, you can read an interview with me about the article.

What’s the background to this article?

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.

Platforms enable a great number of new, seemingly rational and efficacious ways of organising society; but they are also based on an element of control, since users’ latitude is circumscribed by the computer code, and users are in many ways forced to adapt their behaviour to the interactions allowed for and prescribed by the platform owners.

A few platform-based corporations (Google, Facebook, Apple, Amazon, Microsoft) have gained massive global influence, since not only users but also a long list of other societal actors have become dependent on the services provided by these global companies, including many smaller, upcoming platform companies.

How does my concept of “platform logic” become useful?

If one chooses to look at the discrete, often highly technical inter-platform affordances and connections, one will see generativity and scope for innovation. This is what is often focused on in the business press, and similar outlets, despite the fact that many economists would argue that our present era of digital development is less innovative than past ones.

If one chooses, instead, to look at the emerging transnational, geopolitical formations under platform capitalism, one will make an entirely different set of observations. Theorists like Nick Srnicek and Frank Pasquale have argued that platform capitalism begets historically unprecedented forms of economic domination.

Lastly, if one chooses to observe the very minutiae of platform interaction — the ways in which individuals and organisations adapt to the technical imperatives that the platforms as infrastructures implement, one will see that there is a strong form of technocracy involved. Researchers like Robyn Caplan and danah boyd have recently shown how this takes place in institutions, as different organisations adapt their ways of doing things so that they become more compatible with the existing platforms, and in order to emulate the alleged efficacy and agility of tech companies. I, myself, have argued that the epistemological convictions that are at the root of behavioural data-gathering companies such as Facebook, and the technical prescription exerted by the resulting infrastructures, might be much more rigid than many would think, steering also the operatives inside the platform corporations to an extent that we should not underestimate.

The interplay between these different mechanics (each one observable by using the attendant optic) can be neatly summarized by my concept of “platform logic.”

I argue that platform logic is both conforming to and distinct from pre-existing capitalist structural logics (Taylorism perhaps being the one closest at hand, something that was recently seized upon by Evgeny Morozov in his long review of Shoshana Zuboff’s Surveillance Capitalism). Due to the digital nature of platforms, many tendencies already latent in capitalism (monopolism, colonialism, generativity) are exacerbated, while some altogether new tendencies can also be observed.

Platform power can be summarised as ‘the power to link facially separate markets and/or to constrain participation in markets by using technical protocols’ (Cohen 2016: 374). Data is generated, almost automatically, the very moment the infrastructure is used, enabling surveillance and various designs that utilize such data. This has primarily been discussed in relation to the distribution of ads and editorial content in the media sector, but has huge importance also for other industries. Further, digital platforms directly benefit from so-called network effects that make the platform exponentially more valuable as more people use it.

We already know that digital systems have the quality of being possible to scale, virtually endlessly. We also know that code is control, in the sense that events aboard platforms can be governed in absolute, binary ways; users and possibilities can be turned on or off. However, this hard logic of infrastructural control stands in tension with the softer, more generative potentials that are often observed as inherent to digitization; programmability, interoperability and so on. In other words, platforms are charged with a ‘paradoxical tension between the logic of generative and democratic innovations and the logic of infrastructural control’ (Eaton et al. 2015: 218). My concept of “platform logic” refers to this quite specific and, at times, paradoxical interplay that platform power results in.

Andersson Schwarz, J. (2017). Platform Logic: An Interdisciplinary Approach to the Platform-Based Economy. Policy & Internet, 9(4): 374–394. DOI: 10.1002/poi3.159

Paywalled. Contact me for access

🇬🇧 Umwelt and individuation: Digital signals and technical being

This chapter, which forms part of a deep and existentially far-reaching anthology on Digital Existence, is essentially a plea for a more responsive, cooperative information infrastructure. I address this by taking Facebook as an example.

Today’s digital landscape is quite literally premised on a theory of information that was in fact intended for machines – Claude Shannon’s theorem from 1948. Thus, the digital imaginary of our time is unfortunately of a very rigid, mute, non-vitalist kind – essentially inhuman.

My chapter is an attempt at reaching towards a more integrated, dynamic, vitalistic, and inclusive theory of digital information, by adopting the theory of Gilbert Simondon, a French 1950s thinker of technology.

Simondon affirms technology as a symbiotic process, enabling a utopian future where humans and digital infrastructures can be allowed to truly co-habit this planet – in contrast with today’s mainstream paradigm, which rather seems to stipulate an alienated relationship to technology, humans in one ringside and machines in the other. In Simondon’s theory, the individual is not a being but an act, and individuality is always an aspect of generation, ever-evolving, an ongoing genesis.

This stands in stark contrast to prevailing technocratic “solutions” (apps, platforms, databases) that are essentially systems of control, where users are deprived of genuine participation and are at best offered limited forms of co-creation that are always conditional on the proprietors or owners in question. At worst, the participation allowed for users is only illusory. The very act of trying to encapsulate human being into predefined, finite and locked-down boxes – trying to “pin down” individuals and groups by recourse to palimpsests, intended to “freeze” system states as if these were reliable and objective snapshots of human behaviour – is reductive and regressive at its core.

Believe it or not: These rather outlandish epistemological convictions actually lay at the root of today’s tech companies that base their business models on behavioural data, leading the operatives inside of these companies to pretend that the signals gathered are truthful and representative renditions of human behaviour.

What is more, once these operatives implement new applications based on the data that they are constantly gathering and feeding into algorithmic systems of behavioural manipulation and control, these systems actually begin to actively shape the real world that they are interacting with.

Soon, sinister feedback loops emerge: By observing the behaviours that these algorithmic systems prescribe, indeed dictate, users are taught to behave in specific ways in order to navigate the interface in the expected ways. By doing so, they become enticed to make further interactions which will, in turn, be farmed into new, interesting content for other users to interact with: Think of how Facebook users are compelled to publish and share content that is expected to be desirable among their peers.

More importantly, any move that a user would make is monitored and recorded so as to enable the corporation to interpret these signals in order to make selections of content and advertisements that they believe that the user him- or herself would find interesting, based on what they read these signals to indicate.

Moreover, users would arguably adapt also their own behaviours in order to suit the algorithmic infrastructure: In order to maintain peer visibility, users are compelled to design their posts in accordance with what the algorithmic interface tends to value as popular or recognizable to a large audience (Gillespie, 2014: 183). This precipitates a kind of built-in conformism; a popularity bias (Webster 2014).

Algorithms indirectly construct culture by way of feedback loops like this. Individuals seem to act based on what they observe that these semi-automated systems seem to value.

My argument, in brief

There is a funny thing though.

Do you see how the humans in the loop always have to second-guess what the system would prefer or predict? Essentially, the corporation makes educated guesses from all the vast amounts of user signals that they collect, and try to make target groups and so that they can increase the chances for advertisers to place ads that actually engage the users. Essentially, users themselves try to “game” the system so that they can reap as many benefits as they can from using it.

Researchers like Taina Bucher and John Cheney-Lippold have come to similar conclusions.

In order to understand all of this better, let us think of these media-technological systems as Umwelts for individuals to roam through. The concept of Umwelt was developed in the early 20th century by the Baltic German biologist Jakob von Uexküll, and refers to the cognized environment, the “self-centered world” which all organisms live in. All organisms experience life in terms of subjective reference frames: a bumblebee is at the center of its own world, much like the Facebook user is at the center of her own world, uniquely personalised for her, by Facebook the corporation™.

So, as users interact with environments-that-are-unique-to-them-and-only-them, they would at the same time give off signals as they keep interacting with this built environment. After all, this is an environment that is built on surveillance, all the way through. These signals are then instantly harvested by the platform proprietors and are read to be indicative of the assumed internal states of these individuals.

The really clever thing with this argument, though, is that we can think of also the platform infrastructure’s intelligence as a form of technical Umwelt unto itself!

Facebook doesn’t magically “know” you, as if we were dealing with some kind of sentient fairy-tale being, a Leviathan of some kind (although some critical scholars would definitely seem to want to frame it like that!) The platform operators and managers can actually only “see” that which takes place in the direct interactions, the actual “clicks” and measurable movements made. This is, quite literally, all that the automated systems have to go on. A system is a sum of inputs. It is by compiling signals, encoded in the form of “behavioural data,” that the engineers, behavioural scientists and marketing experts who build and maintain this infrastructure make their decisions.

Consequentially, we should not underestimate the degree to which the actual operatives inside the platform corporations are informed by estimations that risk being very reductive, if not even blind to a lot of aspects of human life.

A stunning addition!

After having finished this article in 2018, I was reminded of the concept of affordances, pioneered by cognitive psychologist J.J. Gibson in 1979. It is a bit embarrassing that his work hadn’t actually crossed my mind before. I’m schooled in a field somewhat indebted to continental philosophy and the Frankfurt school, so the work of an American mid-20th century psychologist hadn’t really cropped up on may radar.

But, conversely, Gibson himself had no reference to Umwelt either.

Andersson Schwarz, J. (2018). Umwelt and individuation: Digital signals and technical being. In: A. Lagerkvist (Ed.) Digital Existence. London & New York: Routledge. 61-80.

Paywalled / contact me for access

🇬🇧 Heuristics of the Algorithm

As the cultural and media industries have developed into 21st century forms, where large aggregates of personal information (behavioural data) is mined in order to find patterns of correlations so that individuals and target groups can be identified, me and my co-author Göran Bolin explore some of the foundational heuristics that businesses have to rely upon.

We begin by contrasting 20th century audience statistics with those of the 21st century. 20th century intelligence on mass media audiences was founded on representative statistical samples, analysed by statisticians at the market departments of media corporations.

In the 21st century, an age of pervasive and ubiquitous personal media (e.g. laptops, smartphones, credit cards/swipe cards and radio-frequency identification), techniques for aggregating user data build on large aggregates of information (Big Data) analysed by algorithms that transform data into commodities.

While the former technologies were built on socio-economic variables such as age, gender, ethnicity, education, media preferences (i.e. categories recognisable to media users and industry representatives alike), Big Data technologies register consumer choice, geographical position, web movement, and behavioural information in technologically complex ways that for most lay people are too abstract to appreciate the full consequences of.

The data mined for pattern recognition privileges relational rather than demographic qualities. We argue that the agency of interpretation at the bottom of market decisions within media companies nevertheless introduces a ‘heuristics of the algorithm’, where the data inevitably has to be translated into social categories.

In the paper we argue that although the promise of algorithmically generated data is often implemented in automated systems where human agency gets increasingly distanced from the data collected (it is our technological gadgets that are being surveyed, rather than us as social beings), one can observe a felt need among media users and among industry actors to ‘translate back’ the algorithmically produced relational statistics into ‘traditional’ social parameters. The tenacious social structures within the advertising industries work against the techno-economically driven tendencies within the Big Data economy.

Bolin, G. & J. Andersson Schwarz (2015). Heuristics of the Algorithm: Big Data, User Interpretation and Institutional Translation. Big Data & Society, 2(2): 1–12. DOI: 10.1177/2053951715608406

Link