The Politics of Systems

Continuing in the direction of exploring statistics as an instrument of power more characteristic of contemporary society than means of surveillance centered on individuals, I found a quite beautiful citation by French sociologist Gabriel Tarde in his Les Lois de l’imitation (1890/2001, p.192f):

Si la statistique continue à faire des progrès qu’elle a faits depuis plusieurs années, si les informations qu’elle nous fournit vont se perfectionnant, s’accélérant, se régularisant, se multipliant toujours, il pourra venir un moment où, de chaque fait social en train de s’accomplir, il s’échappera pour ainsi dire automatiquement un chiffre, lequel ira immédiatement prendre son rang sur les registres de la statistique continuellement communiquée au public et répandue en dessins par la presse quotidienne.

And here’s my translation (that’s service, folks):

If statistics continues to make the progress it has made for several years now, if the information it provides us with continues to become more perfect, faster, more regular, steadily multiplying, there might come the moment where from every social fact taking place springs – so to speak – automatically a number that would immediately take its place in the registers of the statistics continuously communicated to the public and distributed in graphic form by the daily press.

When Tarde wrote this in 1890, he saw the progress of statistics as a boon that would allow a more rational governance and give society the means to discuss itself in a more informed, empirical fashion. Nowadays, online, a number springs from every social fact indeed but the resulting statistics are rarely a public good that enters public debate. User data on social networks will probably prove to be the very foundation of any business that is to be made with these platforms and will therefore stay jealously guarded. The digital town squares are quite private after all…

When talking about the politics of the social Web and particularly online networking, the first issue coming up is invariably the question of privacy and its counterpart, surveillance – big brother, corporations bent on world dominance, and so on. My gut reaction has always been “yeah, but there’s a lot more to it than that” and on this blog (and hopefully a book in a not so far future) I’ve been trying to sort out some of the political issues that do not pertain to surveillance. For me, social networking platforms are more relevant to politics as marketing rather than surveillance. Not that these tools cannot function quite formidably to spy on people, but it is my impression that contemporary governance relies on other principles more than the gathering of intelligence about individual citizens (although it does, too). But I’ve never been very pleased with most of the conceptualizations of “post-disciplinarian” mechanisms of power, even Deleuze’s Post-scriptum sur les sociétés de contrôle, although full of remarkable leads, does not provide a fleshed-out theoretical tool – and it does not fit well with recent developments in the Internet domain.

But then, a couple of days ago I finally started to read the lectures Foucault gave at the Collège de France between 1971 and 1984. In the 1977-1978 term the topic of that class was “Sécurité, Territoire, Population” (STP, Gallimard, 2004) and it holds, in my view, the key to a quite different perspective on how social networking platforms can be thought of as tools of governance involved in specific mechanisms of power.
STP can be seen as both an extension and reevaluation of Foucault’s earlier work on the transition from punishment to discipline as central form in the exercise of power, around the end of the 18th century. The establishing of “good practice” is central to the notion of discipline and disciplinary settings such as schools, prisons or hospitals serve most of all as means for instilling these “good practices” into their subjects. Jeremy Bentham’s Panopticon – a prison architecture that allows a single guard to observe a large population of inmates from a central control point – has in a sense become the metaphor for a technology of power that, in Foucault’s view, is part of a much more complex arrangement of how sovereignty can be performed. Many a blogpost has been dedicated to applying the concept on social networking online.

Curiously though, in STP, Foucault calls the Panopticon both modern and archaic, and he goes as far as dismissing it as the defining element of the modern mechanics of power; in fact, the whole course is organized around the introduction of a third logic of governance besides (and historically following) “punishment” and “discipline”, which he calls “security”. This third regime is no longer focusing on the individual as subject that has to be punished or disciplined but on a new entity, a statistical representation of all individuals, namely the population. The logic of security, in a sense, gives up on the idea of producing a perfect status quo by reforming individuals and begins to focus on the management on averages, acceptable margins, and homeostasis. With the development of the social sciences, society is perceived as a “natural” phenomenon in the sense that it has its own rules and mechanisms that cannot be so easily bent into shape by disciplinary reform of the individual. Contemporary mechanisms of power are, then, not so much based on the formatting of individuals according to good practices but rather on the management of the many subsystems (economy, technology, public health, etc.) that affect a population so that this population will refrain from starting a revolution. Foucault actually comes pretty close to what Ulrich Beck’s will call, eight years later, the Risk Society. The sovereign (Foucault speaks increasingly of “government”) assures its political survival no longer primarily through punishment and discipline but by managing risk by means of scientific arrangements of security. This not only means external risk, but also risk produced by imbalance in the corps social itself.

I would argue that this opens another way of thinking about social networking platforms in political terms. First, we would look at something like Facebook in terms of population not in terms of the individual. I would argue that governmental structures and commercial companies are only in rare cases interested in the doings of individuals – their business is with statistical representations of populations because this is the level contemporary mechanisms of power (governance as opinion management, market intelligence, cultural industries, etc.) preferably operate on. And second – and this really is a very nasty challenge indeed – we would probably have to give up on locating power in specific subsystems (say, information and communication systems) and trace the interplay between the many different layers that compose contemporary society.

Mashable.com has a piece on Google’s expanding media empire and there is one observation that is actually quite obvious but which I’ve never really thought about:

It becomes pretty clear how Google is going about launching new products or acquiring others: analyzing the most popular topics within its search engine.

People are searching a lot for second life? All right, let’s launch our own 3D virtual world then. Google Trends already exploits search statistics for really simple trend / market analysis but in a dynamic marketplace like the Web the vast amount of search queries Google registers can really be a much more formidable tool for taking society’s pulse. There is no doubt that Google uses this data internally for some heavy market research and I could imagine that the company might license these tools or data to third parties in the future. Nielsen would get some serious competition.

The point I find really interesting about this matter is that Google is mostly criticized for commercially biases search results, their monopoly on online search and the gathering of data that might be used to spy on citizens – I have yet to read something that reflects data collection on users’ search behavior not only as potentially dangerous to individual rights but as a unique tool for corporate strategy. Mining their all knowing logfile might give Google a competitive advantage that other companies simply cannot emulate. Spotting shifts in cultural trends early could give their business planning an asset that money (currently) cannot buy. It would be prudent to convert to Googlism while they still accept new members.

The concept of self-organization has recently made quite a comeback and I find myself making a habit of criticizing it. Quite generally I use this blog to sort things out in my head by writing about them and this is an itch that needs scratching. Fortunately, political scientist Steven Weber, in his really remarkable book The Success of Open Source, has already done all the work. On page 132 he writes:

Self-organization is used too often as a placeholder for an unspecified mechanism. The term becomes a euphemism for “I don’t really understand the mechanism that holds the system together.” That is the political equivalent of cosmological dark matter.

This seems really right on target: self-organization is really quite often just a means to negate organizing principles in the absence of an easily identifiable organizing institution. By speaking of self-organization we can skip closer examination and avoid the slow and difficult process of understanding complex phenomena. Webers second point is perhaps even more important in the current debate about Web 2.0:

Self-organization often evokes an optimistically tinged “state of nature” narrative, a story about the good way things would evolve if the “meddling” hands of corporations and lawyers and governments and bureaucracies would just stay away.

I would go even further and argue that especially the digerati philosophy pushed by Wired Magazine equates self-organization with freedom and democracy. Much of the current thinking about Web 2.0 seems to be quite strongly infused by this mindset. But I believe that there is a double fallacy:

1. Much of what is happening on the Social Web is not self-organization in the sense that governance is the result of pure micro-negotiations between agents; technological platforms lay the ground for and shape social and cultural processes that are most certainly less evident than the organizational structures of the classic firm but nonetheless mechanisms that can be described and explained.
2. Democracy as a form of governance is really quite dependent on strong organizational principles and the more participative a system becomes, the more complicated it gets. Organizational principles do not need to be institutional in the sense of the different bodies of government; they can be embedded in procedures, protocols or even tacit norms. A code repository like SourceForge.net is quite a complicated system and much of the organizational labor in Open Source is delegated to this and other platforms – coordinating the work effort between that many people would be impossible without it.

My guess is that the concept of self-organization as “state of nature” narrative (nature = good) is much too often used to justify modes of organization that would imply a shift power from traditional institutions of governance to the technological elite (the readers and editors of Wired Magazine). Researchers should therefore be weary of the term and whenever it comes up take an even closer look at the actual mechanisms at work. Self-organization is an explanandum (something that needs to be explainend) and not an explanans (an explanation). This is why I find network science really very interesting. Growth mecanism like preferential attachment allow us to give an analytical content to the placeholder that is “self-organization” and examine, albeit on a very abstract level, the ways in which dynamic systems organize (and distribute power) without central control.

This is not a substantial post just a pointer to this interview with Digg lead scientist Anton Kast on Digg’s upcoming recommendation engine (which is really just collaborative filtering but as Kast says the engineering challenge is to make it work in real time – which is quite fascinating given the volume of users and content on the site). Around 2:50 Kast explains why Digg will list the “compatibility coefficient” (algorithmic proximity anyone?) with other users and give an indication why stories are recommended to you (because these users dug them): Digg users hate getting stuff imposed and just showing recommendations without a trail “looks editorial”. Wow, “editorial” is becoming a swearword. Who would have thought…

This morning Jonah Bossewitch pointed me to an article over at Wired, authored by Chris Anderson which announces “The End of Theory”. The article’s main argument in itself is not very interesting for anybody with a knack for epistemology – Anderson has apparently never heard of the induction / deduction discussion and a limited idea about what statistics does – but there is a very interesting question lurking somewhere behind all the Californian Ideology and the following citation points right to it:

We can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.

One could point to the fact that the natural sciences had their experimental side for quite a while (Roger Bacon advocated his scientia experimentalis in the 13th century) and that a laboratory is in a sense a pattern-finding machine where induction continuously plays an important role. What interests me more though is Anderson’s insinuation that statistical algorithms are not models. Let’s just look at one of the examples he uses:

Google’s founding philosophy is that we don’t know why this page is better than that one: If the statistics of incoming links say it is, that’s good enough. No semantic or causal analysis is required.

This is a very limited understanding of what constitutes a model. I would argue that PageRank does in fact rely very explicitly on a model which combines several layers of justification. In their seminal paper on Google, Brin and Page write the following:

PageRank can be thought of as a model of user behavior. We assume there is a “random surfer” who is given a web page at random and keeps clicking on links, never hitting “back” but eventually gets bored and starts on another random page. The probability that the random surfer visits a page is its PageRank.

The assumption behind this graph oriented justification is that people do not randomly place links but they do so with purpose. Linking implies attribution of importance: we don’t link to documents that we’re indifferent about. The statistical exploration of the huge graph that is the Web is indeed oriented by this basic assumption and adds the quite contestable ruling according to which shall be most visible what is thought important by the greatest number of linkers. I would, then, argue that there is no experimental method that is purely inductive, not even neural networks. Sure, on the mathematical side we can explore data without limitations concerning their dimensionality, i.e. the number of characteristics that can be taken into account; the method of gathering data is however always a process of selection that is influenced by some idea or intuition that at least implicitly has the characteristic of a model. There is a deductive side to even the most inductive approach. Data is made not given and every projection of that data is oriented. To quote Fernando Pereira:

[W]ithout well-chosen constraints — from scientific theories — all that number crunching will just memorize the experimental data.

As Jonah points out, Anderson’s article is probably a straw man argument whose sole purpose is to attract attention but it points to something that is really important: too many people think that mathematical methods for knowledge discovery (datamining that is) are neutral and objective tools that will find what’s really there and show the world as it is without the stain of human intentionality; these algorithms are therefore not seen as objects of political inquiry. In this view statistics is all about counting facts and only higher layers of abstraction (models, theories,…) can have a political dimension. But it matters what we count and how we count.

In the end, Anderson’s piece is little more than the habitual prostration before the altar of emergence and self-organization. Just exchange the invisible hand for the invisible brain and you’ll get pop epistemology for hive minds…

A couple of weeks ago, Google released App Engine a Web hosting platform that makes the company’s extensive knowledge in datacenter technology available to the general public. The service is free for the moment (including 500MB in data storage and a quite generous contingent in CPU cycles) but there is a commercial service in preparation. Apps use Google Passport Google’s account system for user identification and are currently limited to (lovely) Python as programming language. I don’t want to write about the usual Google über alles matter but kind of restate an idea I proposed in a paper in 2005. When criticizing search engine companies, authors generally demand more inclusive search algorithms, less commercial results, transparent ranking algorithms or non-commercial alternatives to the dominant service(s). This is all very important but I fear that a) there cannot be search without bias, b) transparency would not reduce the commercial coloring of search results, and c) open source efforts would have difficulties mustering the support on the hardware and datacenter front to provide services to billions of users and effectively take on the big players. In 2005 I suggested the following:

Instead of trying to mechanize equality, we should obligate search engine companies to perform a much less ambiguous public service by demanding that they grant access to their indexes and server farms. If users have no choice but to place confidence in search engines, why not ask these corporations to return the trust by allowing users to create their own search mechanisms? This would give the public the possibility to develop search algorithms that do not focus on commercial interest: search techniques that build on criteria that render commercial hijacking very difficult. Lately we have seen some action to promote more user participation and control, but the measures undertaken are not going very far. From a technical point of view, it would be easy for the big players to propose programming frameworks that allow writing safe code for execution in their server environment; the conceptual layers already are modules and replacing one search (or representation) module with another should not be a problem. The open source movement as part of the civil society has already proven it’s capabilities in various fields and where control is impossible, choice might be the only answer. To counter complete fragmentation and provide orientation, we could imagine that respected civic organizations like the FSF endorse specific proposals from the chaotic field of search algorithms that would emerge. In France, television networks have to invest a percentage of their revenue in cinema, why not make search engine companies dedicate a percentage of their computer power to algorithms written by the public? This would provide the necessary processing capabilities to civil society without endangering the business model of those companies; they could still place advertising and even keep their own search algorithms a secret. But there would be alternatives – alternative (noncommercial) viewpoints and hierarchies – to choose from.

I believe that the Google App Engine could be the technical basis for what could be called the Google Search Sandbox, a hosting platform equipped with either an API to the company’s vast indexes or even something as simple as a means to change weights for parameters in the existing set of algorithms. A simple JSON input like {”shop”:”-1″, “checkout”:”-1″,”price”:”-1″,”cart”:”-1″,”bestseller”:”-1″} could be enough to e.g. eliminate amazon pages from the result list. SEOing for these scripts would be difficult because there would be many different varieties (one of the first would be bernosworld.google.com – we aim to displease! no useful results guaranteed!). It is of course not in Google’s best interest to implement something like this because many scripts might direct users away from commercial pages using AdSense, the foundation of the company’s revenue stream. But this is why we have governments. Hoping for or even legislating more transparency and “inclusive” search might be less effective than people wish. I demand access to the index!

There are many things to be said about Clay Shirky’s recent book “Here Comes Everybody: The Power of Organizing without Organizations” and a lot has already been said. The book is part of an every growing pile of Web 2.0 literature that could be qualified as “popular science” – easily digestible titles, generally written by scholars or science journalists, which are generally declaring the advent of a new age where old concepts no longer apply and everything is profoundly transformed (knowledge, education, the economy, thinking, wisdom, organization, culture, journalism, etc.). The genre has been pioneered by people like Alvin Toffler and Jeremy Rifkin and it does now dominate much of the debate on the social, cultural and political “effects” of recent developments in ICT. There is of course merit to a larger debate on technology and the sensationalist baseline is perhaps needed to create the audience for such a debate. At the same time, I cannot help feeling a little bit unsettled by the scope the phenomenon has taken and the grip these books seem to have on academic discourse. Here are a couple of reasons why:

1. There are actually very few thoughts and arguments in the whole “Web 2.0 literature” that have not already been phrased in Tim O’Reilly’s original essay. Granted, the piece was quite seminal but shouldn’t academia be able to come up with a stronger conceptual viewpoint?
2. The books in question are really lightweight when it comes to anchoring their thoughts in previous scholarly effort. A lot of room is given to metaphorical coupling with the natural sciences (some keywords: swarms, ecologies, auto-organization, percolation, critical thresholds, chaos, etc.) but although most of these books talk about the future of work (prosumers performing collective wisdom, in short), there is very little interaction with the sociology of labor or economic theory. Sure, a deeper examination of these topics would be difficult, but without some grounding in established work, the whole purpose of scholarship as a collective endeavor is meaningless – which is especially ironic given the celebration of cooperation one can find in Web 2.0 literature
3. As I’ve already written in another post, I find the idea that “participation” and “leveling of hierarchies” equates democracy deeply troubling. Richard Sennett’s argument that stable social organization and work relations are necessary prerequisites for true political discourse – politics that go beyond the flash mob activism often presented as prove for the new, more democratic age that is upon us – is ringing louder than ever.
4. Much of the Web 2.0 literature is basically antithetical to the purpose of this blog. Shirky’s idea that the new social tools allow for “organizing without organizations” is largely ignoring the political power that is transferred to the 21^st century tool maker and the companies that he or she works for. I’m not advocating paranoia here, but the fact that many of the tools that power mass sociability online are produced and controlled by firms that are accountable to their shareholders only (or the people that got them venture capital) is at least worth mentioning. But the problem really goes beyond that: the tools we currently have incite people to gather around common interests, creating and activating issue publics than can indeed take influence on political matters. But politics is much more than the totality of policy decisions. The rise of issue publics has coincided with the demise of popular parties and while this may look like a good thing to many people, parties have historically been the laboratories for the development of politics beyond policy. Europe’s social market economies are unthinkable without the various socialist parties that worked over decades to make societies more just. One does not have to be a left winger to recognize that the loss of the stable and accountable forum that is the political party would be at least ambiguous.
5. While Web 2.0 literature is light on politics and serious political theory it is not stingy with morals. The identification of “good” and “bad” effects that 2.0 ICT will have on society often seems really at the core of many of the texts published over the last few years. But as point 4 might have shown, the idea of “good” and “bad” is really meaningless outside of a particular political (or religious) ontology. What actually happens is the understatement of a vague political consensus that takes a position antithetical to the premises of critical sociology, i.e. that conflict is constitutive to society.
6. An essay stretched over 250 pages does not make a book. (I know, that’s a little mean – but also a little true, no?)

Don’t get me wrong, many of the books I’m referring to have actually been quite interesting to read. What worries me is the lack of more scholarly and conceptually demanding works but perhaps I’m just impatient. In a sense, “Digital Formations” by Robert Latham and Saskia Sassen already shows how sophisticated Internet Research could be if we switch off that prophet gene.

This is a very general question and there is no way to answer it in a rigorous way. But after reading many of the books and articles on “participatory culture” I cannot shake the feeling that the idea of non-organized organization will very soon be confronted with a series of limits and problems inherent to auto-organized social aggregation – inequality, intercultural strife, visibility of minority opinion, etc. – that will be difficult to ignore.

But there is a more practical reason why I ask myself this very question. Pierre Lévy actually used to work at my department and my laboratory has recently stuck up a cooperation with his research unit in Ottawa. We’ve been organizing a little seminar here in Paris where Lévy will be giving a talk later this month. When Lévy wrote “L’intelligence collective” in 1994, many people saw his proposals as sheer blue-eyed utopia and dismissed it rather quickly. The American reading of that text has since then become something like the bible of research on participatory culture, user-generated content movements, and so on. Interestingly, Lévy himself has been pretty silent on all of this, leaving the exegesis of his thoughts to Henry Jenkins and others. Why? Because Lévy probably never imagined collective intelligence as photo-sharing on Flikr or Harry Potter fanfiction. What he envisioned is in fact exemplified by his work over the last couple of years, which was centered on the development of IEML – Information Economy Meta Language:

IEML (Information Economy Meta Language) is an artificial language designed to be simultaneously: a) optimally manipulable by computers; and b) capable of expressing the semantic and pragmatic nuances of natural languages. The design of IEML responds to three interdependent problems: the semantic addressing of cyberspace data; the coordination of research in the humanities and social sciences; and the distributed governance of collective intelligence in the service of human development.

IEML is not another syntax proposal for a semantic web like RDF or OWL. It is a philosopher’s creation of a new language that allows mainly two things: facilitate the processing of data tagged with IEML sentences and help cross-language and intercultural reasoning. This page gives a short overview. Against the usual understanding of collective intelligence, IEML is really a top-down endeavor. Lévy came up with the basic syntax and vocabulary and the proposal explicitly states the need for experts in helping with formalization and translation. I must admit that I have been very skeptical of the whole thing, but after reading Clay Shirky’s “Here comes Everybody” (which I found interesting but also seriously lacking – I’ll get to that in another post though) there is a feeling creeping up on me that Lévy might yet again be five years ahead of everybody else. In my view, the mindset of large parts of research on participation has adopted the ontology and ethics of American-brand Protestantism which, among other things, identifies liberty and democracy with community rather than with the state and which imagines social process as a matter of developing collective morals and practices much more than the outcome of power struggles mediated by political institutions. This view idealizes the “common man” and shuns expert culture as “elitist”. Equality is phrased less in socio-economic terms, as “equal opportunity” (the continental tradition), but in mostly in cultural terms, as “equal recognition”. (Footnote: this is, in my view, why political struggle in the US has been, for many decades now, mostly about the recognition of minority groups while on the European continent – especially in catholic countries – “class struggle” still is a common political vector) In this mindset, meritocracy is therefore necessarily seen as ambiguous.

I believe that the most interesting projects in the whole “amateur” sector are the ones that organize around meritocratic principles and consequently built hierarchy; open source software is the best example but Wikipedia works in a similar fashion. The trick is to keep meritocracy from turning into hegemony. But I digress.

Lévy’s bet is that collective intelligence, if it wants to be more than pop culture, will need experts (and expert tools) for a series of semantic tasks ranging from cartography to translation. His vision is indeed much more ambitious than most of the things we have seen to this day. The idea is that with the proper (semantic) tools, we could tackle problems collectively that are currently very much out of reach; and this in a truly global fashion, without bringing everybody into the rather impoverished linguistic umbrella of globish. Also, in order to make search more pluralistic and less “all visibility to the mainstream” as it currently is, we will need to get closer to the semantic level. I don’t believe that IEML, in its current iteration at least, can really do all these things. But I believe that yet again, Lévy has the right intuition: if collective forms of “problem solving” are to go beyond what they currently do, they will have to find modes of organization that are more sophisticated than the platforms we currently have. These modes will also have to negociate a balance between “equal opportunity” and “equal representation” and make it’s peace with instituionalization.

The philosophical discipline of ethics is, in my view, the intellectually most daunting field in the humanities. The central problem has been identified by David Hume in his “Treatise of Human Nature”, published in 1738, and is resumed by this paragraph:

“In every system of morality, which I have hitherto met with, I have always remark’d, that the author proceeds for some time in the ordinary ways of reasoning, and establishes the being of a God, or makes observations concerning human affairs; when all of a sudden I am surpriz’d to find, that instead of the usual copulations of propositions, is, and is not, I meet with no proposition that is not connected with an ought, or an ought not. This change is imperceptible; but is however, of the last consequence. For as this ought, or ought not, expresses some new relation or affirmation, ’tis necessary that it shou’d be observ’d and explain’d; and at the same time that a reason should be given; for what seems altogether inconceivable, how this new relation can be a deduction from others, which are entirely different from it.”

Know as the “is-ought problem”, the change of register implied by going from a descriptive mode towards a prescriptive one, poses the question on what to found the latter. There is a necessary recourse to something non-descriptive, a system of values that cannot be stabilized by the scientific method and is therefore necessarily a terrain for permanent struggle. Value systems are, however, by no means random but deeply embedded in historic process and while the conflictual nature of the “ought” cannot be dissolved, the contents of ethical debate can be treated as just another “is”, i.e. a field of discourse that can be described and analyzed. While the specific answers we give to Kant’s question “what should we do?” may well be products of long and hard reasoning, they are nonetheless developed against the backdrop of long-standing “networks of significance” (Geertz), that is, culture.

Having grown up in a German-speaking country, living in France but also following and participating in the globalized English-language sphere of discourse, it is hard not to be amazed by the striking differences in how recent developments in technology and digital culture are framed and appreciated. I have recently attended the “Web 2.0 Politics” conference near London and in a sense the experience had the quality of an epiphany. From the perspective of a drifter like me, culture (defined in national or linguistic terms) can sometimes look like a vast assembly of automatisms and reflexes. Coming from the outside, we cannot help but see how little in culture is actually decided upon and how much seems to be simply received. This is especially true when it comes to intrinsically shifty areas like ethics and political reasoning. What struck me at this conference was how certain words seemed to pass through what one could call “automated moral preprocessing”, which would allow filing very complicated and ambiguous concepts very quickly into neatly labeled boxes, largely divided into “good” and “bad”. This is very effective because it speeds up the reasoning process and bridges the rift between “is” and “ought” without much effort. A concept like “participation” for example gets preprocessed into the “good” box and can then be used as a general-purpose moral qualifier for all kinds of technological and cultural phenomena. Online services that allow people to participate can suddenly be called “democratic” because “participation” and “democracy” are commonly filed together. This is the moment when my Germanic “me” comes to spoil the party and points to the fact that pogroms and lynch mobs are in fact quite participatory activities. The little Frenchman that has secretly taken up home somewhere in my wetware adds that “populisme” is a permanent danger to true democracy and that only strong institutions can guarantee freedom. Catholicism’s heritage is a profound mistrust in human nature. These are perhaps nothing more that worn clichés, but in my case the effect of multiculturalism is a permanent cacophony of competing automatisms that disables the “good” / “bad” preprocessing that so much of the current Web 2.0 discourse seems to fall victim to.

We seriously need to get back to understanding ethics – and as a consequence politics – as deeply troubling subjects. The usual suspects of French philosophy have become household names but their principal lesson has been washed away like the famous face in the sand: that critical thinking must look at the ground it is built on. That doesn’t mean that normative arguments should be excluded, quite on the contrary – a new Habermas is direly needed. It could mean though that Hume’s bafflement at how the “ought” suddenly seems to spring out of nowhere should trouble us, too.