The Moneticization of Everyday Life By Andreu Belsunces

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Monitoring / capitalizing behaviour / configuring habits'

“Why not consider the irreducibly constitutive role of machines, techniques, or technology in the problematic axiology of power?” Matthew Fuller and Andrew Goffey

“We have gone from being agents tending to the action of machines to becoming constituent parts of them.” Deleuze and Guattari

- Note: the numbers in brackets correspond to points in the Interface Manifesto


The user is one of the key figures in today’s cultural ecosystem. More than cables, satellites, and protocols, the internet is, above all, its users. The power of disruptive companies, the inspiration for cutting-edge innovation, and the content that feeds all types of platforms depends on them (on us). We are a (porous) bottomless pit. When the new century was born it brought along Web 2.0, and like children born with a silver spoon, it augured a future full of happy omens. Users became the fuel for the new paradigm based on participation and horizontality, and the engine was the companies that created spaces where it could take place. The important thing was the information, the “content”.

As “viewers” became “users”, it became clear that the strategies that made money in traditional media could also make money in online environments. Online platforms and portals began selling brands to its users, just as television had sold brands to audiences. And just as television had segmented audiences based on market research and audiometers, web companies used cookies, the profiles created by users when they sign up to use their services, and their data footprints in general. The digital environment started to convince users through performativity, just as television tried to convince viewers through seduction.

The Datified User

The characteristics users have changed in line with the changes in the corporate, technical, institutional, and social fields. We could say that two main trends have shaped what we know now generally refer to as the “user”. On one hand, in the age of Big Data everything around us has become a potential source of information, and many aspects that were left up to human judgement are now augmented or replaced by computerised systems. On the other hand, mobile communication offers myriad internet-connected devices that allow us to interact with each other and with the world. As Viktor Mayer-Scönberger and Kenneth Cukier argue, this has changed basic aspects of our lives and given them an unprecedented quantitative dimension. As a result a new layer of meaning was added to the idea of the participatory user that became widespread with Web 2.0.

Against this backdrop, graphic user interfaces, which form part of virtually all our devices, become – to paraphrase Lev Manovich – cultural objects that permeate all areas of contemporary societies, creating frameworks for monitoring, representation, simulation, analysis, decision-making, memory, vision, writing, and interaction. These interface-mediated processes are part of the so-called “algorithm society”, in which the idea of machine learning encourages constant monitoring (through geolocation, the use of apps that require access to contact details, the use of online services and networks, city sensorization, etc.), which is described as a collateral effect and a necessary step for reaching the next level of comfort and efficiency. This approach takes for granted that the more machines know about us, the better they will serve us.

Optimization + Operability

This process is what has turned our omnipresent interfaces into spaces for potential datified interaction (2)*. Algorithms, which are supposed to compile, classify, predict and manage information, passively monitor our use of interfaces. In the context of hyper-accelerated capitalism, algorithms – which respond to the interests of the system they form part of – attempt to optimize a system that tends towards simplicity and operability for users, and profitability for the companies behind them (7). To this end, digital environments, always in Beta, begin operating in a way akin to what Fuller and Goffey have called a Pavlovian experiment on large-scale, constantly adjusting to the way they are used according to the collected data.

An example is AppPulse Mobile, a web-native software for designers and developers that monitors the use of services in which it is implemented, monitoring their operation in real time – from the moment in which a user’s finger first glides on a screen to the moment he goes offline. This allows programmers to identify the problems that affect the users or functionality of an application, to discover what fails on a particular device, operating system, or app version, and to fix errors before they affect the “end user experience” (and before the company that has contracted their services finds out).

Going back to Fuller and Goffey, these testing techniques support, amplify, and confirm the production of the user as a behavioural unit and provider of quantifiable test data, placing him in an unwitting, unconscious situation of agency in regard to the interface and the services it enables (14).


As well as monitoring geared towards the performative optimization of the interface, user datification is also used to produce consumer profiles. Through algorithms, data collection and ongoing processing can reveal overall patterns in regard to the types of users interested in a particular product, so that companies can adapt the content or try to attract other types of user profiles. Similarly, the general characteristics of groups of users can be sold to polling and marketing surveys.

When data is aggregated, the features of individual users blur. This is why there are also other uses for interface surveillance at the individual level. Depending on privacy conditions, one of these other uses could be collecting information for mass surveillance by governments, as Edward Snowden’s leaks in June 2013 showed.

Another more obvious use of individually-generated data is custom advertising to match user profiles. And another, perhaps more important, use is the burgeoning personal assistant market. This particularly interesting case shows how algorithms try to learn and predict user behaviour.

For instance, Google Now, a personal assistant developed for mobile devices, collects information extracted from our use of different Google services (Gmail, Google+, Google Maps, Chrome, Google Calendar, etc.) and combines the different data to identify our patterns and preferences. Based on these patterns, it offers personalised recommendations of events, products, and routes, and even lets us know what time we should leave home to catch a flight or go to work, without us asking it to.

This case illustrates the extent to which users feed data systems through the interfaces they use, providing detailed information about their everyday lives.

Interface as Infrastructure

Interfaces are data collection points that involve the interests of several actors. But the means by which this takes place are not clear. By mediating and simplifying technical operations, interfaces produce black boxes and their expedient opacity hides behind an illusion of transparency and user-friendly design (9)(10)(12).

Today’s interfaces, which are becoming increasingly ubiquitous in our lives, are designed to reduce user friction. In a quest to achieve this, the field of user experience design prioritises interface design that seeks efficiency of gesture and thought. And this requires monitoring geared towards optimization. But paradoxically, this contradicts a phenomenon noted by Olia Liana: the gradual disappearance of the term “user” in the discourse of designers and developers. By calling users “persons” they are naturalized (and neutralized) and the computational component is eliminated. But at the same time, they are subjected to surveillance that is programmed into the algorithms. This is one factor that contributes to reducing the conscious agency of interface users. The irrefutable tendency to make all graphic interfaces as usable, engaging, simple, and social as possible is an expression of the values inherent to the discourse of Silicon Valley and global technoculture elites.

Interfaces as infrastructure incorporate these narratives and exert enormous power in their apparent neutrality. Because of their necessary, ubiquitous mediation, interfaces go unnoticed, as if they were an ambient factor. But the truth is that as users we delegate many different tasks to them, and through this delegating we give them a great deal of control when it comes to making all kinds of decisions.

As Pierre Lévy argues, intelligence technologies – including computing and its interfaces – affect the way we think and behave, and our habits. This is where interfaces – not just as systems of representation, but also as matter – exercise agency on users, in many different forms.

Metrification as (and of) Performativity (15)

In their graphic form, algorithms invite those who interact with them to adopt their own logic, and this often leads to standardization based on their own pre-defined objectives (11). This can be seen in the growing quantification of online life, and in how the importance of metrics as standards of measurements is introducing the world of business management into the private realm.

Artist and composer Ben Grosser talks about how social networks, particularly Facebook, enable certain conditions of performativity that stimulate what he calls the “business ontology” and “audit culture”. In this way users, focusing particularly on the amount of “likes”, friends, or comments on their own pages and those of others create a “graphopticon”, an audit practiced on themselves, where many users monitor the activity metrics of many others.

This quantifying dynamic is fuelled by and becomes integrated in the habits of users, at least partially, through gamification strategies. As Daphne Dragona shows, every move on social media is measured and every post awaits response, creating a particular field of action in which content constantly competes with other content for attention. These points systems, she says, depend on algorithms on one hand, and on promptness and virtuosity on the other.

Expanding these dynamics to the world of interface design, we see how game dynamics configure performativities geared towards creating a situation of soft conflict in users, who must negotiate it with their prowess (13). Rewards based on quantification (or micro-satisfaction) fuel participation, opening up the opportunity for playful interaction, but also for more possibilities of exploitation and control. (6)

This is how business ontology seeps into social life through interfaces, leading - as Grosser puts it – to the audit culture or an increase in the use of observational measurement – way beyond its original use in financial administration – into the previously self-managed public sector.

As Dragona writes, it is no coincidence that gamification has reached users in the age of data-oriented culture and economy, when there is a desire to calculate and quantify everything not just by governments, companies and institutions, but also by users and citizens themselves.

This dynamic should be considered within a scenario that is very well illustrated by Mayer-Scönberger and Cukier, in which data become an important corporate asset, a vital economic factor, and the basis for new economic models. Which is why the more measurable our living habits become, the easier it will be to monetize them.

Taking all of this into account, Fuller and Goffey say that we are not aware of the extent to which behaviour has been transformed into economics. In the age of datification, the interface acts as an infrastructure that prescribes habits, a key position in the crystallisation and reproduction of an emergent state of affairs, where corporate interests materialize in hardware and software that make it possible to exist, think, and interact within a specific range of possibilities, but not others. This is where interfaces not only configure and normalise particular ways of being a user, but also of being itself, in the ontological sense.

  • Numbers between parenthesis relates ideas to Manifesto points


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Dragona, D. (2013). “Counter-gamification Emerging forms of resistance in social networking platforms”. Comunicación en Rethinking Gamification Gamification Lab at Centre for Digital Cultures 15-17 Mayo 2013 .

Carr, N. (2014). Atrapados. Cómo las máquinas se apoderan de nuestras vidas. Madrid, Taurus.

Fuller, M., & Goffey, A. (2012). Evil media (p. 232). Cambridge, MA: MIT Press.

Gil Claros, M. G. (2012). “Subjetividades contemporáneas, Un acercamiento estético y politico a Félix Guattari”. Revista de filosofia on line A parte Rei. 75. Mayo 2011. Consulta [10/01/2015]

Grosser, B, (2014) “What Do metrics want? How quantifiaction prescribes social interaction on Facebook”. Computational Culture. Noviembre 2014. Consulta [08/01/2015]

Lévy, P (1994). “Las tecnologías de la inteligencia. El futuro del pensamiento en la era informática”. Consulta [5/05/2015]

Liliana, O. (2012) "Turing Complete User". Contemporary Home Computing. Consulta [10/04/2014]

Manovich, L. (2001). The language of new media. MIT press. Mayer-Schönberger, V., & Cukier, K. (2013). Big data: La revolución de los datos masivos. Turner. Madrid

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VV. AA. (2013). BWPWAP. Transmediale. Berlin.