Big Data and The Smart New World as the Highest Stage of Positivism

Thomas Meyer

1. Introduction: The Mediation of Theory and Empiricism as a Concrete Totality

An individual never constitutes themselves directly, but is conditioned by the fetishistic process dynamics of capitalist society, mediated by the fetishistic whole. Immediacy of facts indicates that no critique of them is attempted, but a critique is evaded, for example, to make oneself comfortable in the scientific establishment. Empirical findings cannot be understood without theoretical concepts, and both concepts and empirical facts are in a dialectical relationship to each other. Adorno wrote in his critique of an empirically oriented sociology: “Theoretical reflections upon society as a whole cannot be completely realized by empirical findings […]. Each particular view of society as a whole necessarily transcends its scattered facts. The first condition for construction of the totality is a concept of the object [Sache], around which the disparate data are organized. From the living experience, and not from one already established according to the societally installed control mechanisms, from the memory of what has been conceived in the past, from the unswerving consequence of one’s own reflection, this construction must always bring the concept to bear on the material and reshape it in contact with the latter. But if theory is not to fall prey to the dogmatism over whose discovery skepticism—now elevated to a prohibition on thought—is always ready to rejoice, then theory may not rest here. It must transform the concepts which it brings, as it were, from outside into those which the object has of itself, into what the object, left to itself, seeks to be, and confront it with what it is. It must dissolve the rigidity of the temporally and spatially fixed object into a field of tension of the possible and the real: each one, in order to exist, is dependent upon the other.” (Adorno 1976)

Thus, empirical facts are to be applied to theoretical concepts, which themselves should be sharpened in confrontation with these facts. For every theory has its “time core” and concepts themselves have a history. Not taking note of empirical facts can result in an “anachronistic train of thought,” and theory building is then reduced to nostalgia and the exegesis of “holy writings.” At worst, one then ends up with an ahistorical and existentialist seeming “conceptualism.”[1] On the other hand, empiricism is not to be referenced with an immediacy such that every fact stands for itself as a positively given fact and its historical constitution and mediation with the social process dynamics is left out. For example, there are undoubtedly many studies that clearly describe the insanity of the capitalist mode of production (such as those on plastic production or industrial agriculture), but can only inadequately explain these empirical facts due to a lack of economic and social theoretical grounding; accordingly, the practical conclusions then often turn out to be helpless and abbreviated. If in such studies even the socio-critical impetus is still missing, one ends up “fact hoarding,” only wanting to acknowledge what can be expressed by graphs, statistics and numbers.

In contrast to the fact- and concept-mania, however, there must be an insistence on relating empirical facts to the fetishistic process-dynamics of capital, speaking to the totality; and at the same time the concepts, by which totality is to be expressed, must be related to empirical findings, so that the concepts grasp with sharpness that to which they are to refer, and make it possible to recognize the inner and historical connection of the empirical. The totality is thus to be thought of concretely (Scholz 2009). In this context, it must be noted that the empirical does not merge into the concepts, and in the context of the value-dissociation critique, it must be emphasized in particular that the various subject areas must also be accorded a quality of their own, which cannot be subsumed under a totality; rather, a fractured, historically dynamic totality must be assumed.

In the following, the aim is to outline facets of Big Data, social physics, and the Internet of Things, as well as the subsequent, rather left-wing criticism on a largely phenomenological or empirical level, which is also to be taken note of and not simply incidental. However, it should not stop with this critique; beyond this, the view of the overall social context of form and process should be unfolded.

2. Some Critical Thoughts on the Use of Mathematics in the (Social) Sciences

Mathematics is given the status of objectivity, stringency and freedom from personal values in (developed) modernity. This status is also given to those who express themselves through it. A statement that can be expressed by a number is regarded in our modern world as the epitome of truth. An argument has all the more power of statement and persuasion if it can refer to quantities, i.e. numbers and graphs (Ortlieb 2011). Thus, the sciences that are written mathematically, of which physics is a prototypical example, are considered “exact,” and those that are not are tainted with the stigma of non-exactness, of mere opinion, even of ideology.

Throughout the course of the 19th century and then at the latest in the 20th, various sciences have endeavored to orient themselves on the methodology of physics, on mathematical modeling and experiment, to thereby also attain the status of exactness and objectivity, with the goal of transferring the success of physics to their métier as well. The idea of being able to simply replicate the success of one subject by adopting its methodology to another is not without problems. This is because success (however it may be evaluated) has certain prerequisites that may not exist in another subject area. As a rule, there is no reflection on this either, because this would require dealing with the functional logic of the sciences and their “epistemic interests” (Habermas) or their “epistemic ideals” (K. M. Meyer-Abich). As we will see, an unreflective approach to mathematics is anything but stringent.[2]

A particularly clear case of this is the emergence of neoclassicism since the 1870s. Its goal was to overcome classical bourgeois economics and establish itself as an “exact” university discipline. It took its cue from physics, more specifically from classical mechanics. As the neoclassicist Irving Fisher (1867-1947) pointed out, the aim was to develop a formalism based on Hamiltonian mechanics[3] by establishing certain conceptual analogies (particle = individual, energy = utility, etc.) (Mirowski 1989, 222f.). However, this claim and its realization has already experienced some criticism (even more than 100 years ago, as described by Mirowski).

The impossibility of an experiment that could verify or falsify a mathematically formulated theory or even establish the situation in which the model assumes validity is a decisive argument for why this transfer cannot work in this way. It does not follow from this that mathematics cannot be used in economic theory in a meaningful and insightful way; however, it must be noted that mathematical models in economic theory generally cannot have the same explanatory power and scope as those in physics. However, a serious problem can already be observed at the level of model building itself: If one looks at common textbooks in economics, one sees that the assumptions of a given model are often not accounted for or verified when that model is applied to a new situation. Moreover, model assumptions are always made to fit the concept of market equilibrium: a rigid equilibrium scheme is thus imposed on all conceivable phenomena. The model assumptions are therefore chosen in such a way that we always get an intersection of two opposing tendencies, represented by the so-called Marshall cross[4] (if model assumptions were chosen a little more realistically, we might get no intersection, i.e. no equilibrium, cf. Ortlieb 2004a). Furthermore, these models and their assumptions convey an economic picture that has nothing to do with real capitalism, with industrial mass production, etc. They are little more than “market fairy tales” (Ortlieb 2004b). Therefore, neoclassical economic theory is rightly described as “mathematized charlatanry” (Ortlieb 2006). A possible reason to explain why a whole scientific discipline proceeds in such a methodologically questionable way was provided by Alan Freeman (Freeman 2006). According to him, neoclassicism is not so much a science that investigates and establishes facts of the external world, but rather a quasi-religious doctrine that has the dogma of the theory of harmony of the market equilibrium as its content, and therefore justifies capitalism. According to Freeman, this dogma is comparable to “heaven” in the Middle Ages. But this already indicates that if the aim is to criticize the sciences, it would be insufficient to limit oneself only to an immanent critique, to a critique of only methods and claims.

However, objectivity in the modern sense, as claimed by the natural sciences in particular, is not synonymous with truth, certainty, or fact-orientation. As Lorraine Daston and Peter Galison have noted, to be objective is to be “intent on knowledge that bears no marks of the knower” (Dasten; Galison 2007, 17). Objectivity, then, is a form of practice designed to eliminate subjectivity from the process of knowing. Objectivity understood in this way is thus an expression of social relations and the cognitive practice of the bourgeois subject form. The appearance of this objectivity consists precisely in the fact that scientific practice apparently has nothing to do with the cognizing subject.

Typically, objectivity and its historical or social genesis is not or is hardly reflected upon in the scientific community, and it is certainly not questioned.[5] The same goes for the term “exactness,” whose meaning is just as infrequently made clear.

According to Herbert Auinger, there is no reason why a non-mathematical language should not be exact, i.e. exact in the sense that the language hits what it refers to with clear words and conceptual sharpness. Ironically, philosophers such as Gottlob Frege (1848-1925) complain about the imperfection or lack of clarity of language with very clear words (Auinger 1995).

When talking about exactness of mathematical language, the focus is on the compactness of the mathematical expression and its convenient handling. A mathematical language is therefore precise and unambiguous and a non-mathematical one is not (necessarily).

However, it must be emphasized that this exactness can only be associated with those phenomena that are accessible to a mathematical description or quantitative approach (cf. the article “Math Delusion” by Claus Peter Ortlieb in this issue).

However, a switch to mathematics and the handling of social science or economic issues through mathematics, even if it is done in a methodologically clean way, is not to be confused with a profound examination of those issues that are to be given a mathematical form: According to Auinger, various social scientists who aspired to mathematization, or tried to justify it, complained that there are too many different theories in the social sciences, a complaint that says nothing against them in terms of content in the first place. Mathematization is thus seen as a way to put a stop to this confusing diversity; mathematics and formal logic then vouch for the truth of the rest. A mathematization can therefore find its reason in the fact that one does not want to (or can no longer) deal with the content of these different theories and their problems. Calculation can therefore possibly also be seen as a substitute for thinking (or thinking is limited to what can be quantified or is to be quantified). Certainly, the application of mathematics is useful in certain areas and appropriate to that corresponding subject area. But the number faith of our time can also lead to overestimating mathematics and its application, labelling everything else that might not be calculated as subjective and dismissing it as mere “speculation.”

The objection that mathematics and the mathematical sciences, quantitative thinking, are not to be overestimated, has been raised before. This was expressed by Hegel[6] himself in his Encyclopedia of the Philosophical Sciences: “This is followed by the further consideration that, since quantity, without being mediated by thinking, is taken up directly from the imagination, it easily happens that it is overestimated with respect to the extent of its validity, and even increased to an absolute category. This is indeed the case if only those sciences whose objects can be subjected to mathematical calculation are recognized as exact sciences. […] It would indeed be bad for our cognition, if of such objects as freedom, right, morality, even God himself, because they cannot be measured and calculated or expressed in a mathematical formula, we would have to content ourselves with renunciation of an exact cognition, in general merely with an indeterminate idea, and then, as far as the closer or particulars of the same are concerned, it would be left to the discretion of each individual to make of it what he wills.” (HW 8, 210f., here quoted after Auinger 1995, 16)

After Hegel, too, there were critical comments on the overestimation of the quantitative way of thinking, for example, by Friedrich Nietzsche, who wrote in “The Gay Science”: “So, too it is with the faith with so many materialistic natural scientists rest content: the faith in a world that is supposed to have its equivalent and measure in human thought, in human valuations – a ‘world of truth’ that can be grasped entirely with the help of our four-cornered little human reason – What? Do we really want to demote existence in this way to an exercise in arithmetic and an indoor diversion for mathematicians? Above all, one shouldn’t want to strip it of its ambiguous character: that, gentlemen, is what good taste demands – above all, the taste of reverence for everything that lies beyond your horizon! That the only rightful interpretation of the world should be one to which you have a right […], one that permits counting, calculating, weighing, seeing, grasping, and nothing else – that is a crudity and naiveté, assuming it is not a mental illness, an idiocy. […] Suppose one judged the value of a piece of music according to how much it could be counted, calculated, and expressed in formulas – how absurd such a ’scientific’ evaluation of music would be! What would one have comprehended, understood, recognized? Northing, really nothing of what is ‘music’ in it! (Nietzsche 2001, 238f.)

Hegel and Nietzsche hereby collect points that are mentioned in a critique of an overestimation of mathematical science.[7] However, they argue purely epistemologically, and do not relate to the level of society as a whole, and thus remain on the surface. It is important not only to criticize the unreflective and possibly methodologically impure application of mathematics or quantitative thinking, but also to criticize the social context in which this application takes place.

Claus Peter Ortlieb formulated a critique of the mathematical natural sciences on a socio-theoretical level in his essay “Unconscious Objectivity” (Ortlieb 1998). There it is argued, among other things, with reference to Evelyn Fox Keller, “that for some reason we have forgotten to bring our own survival into the objectives of scientific knowledge.” The basic problem, then, lies not so much in a merely unreflective approach to mathematics and the “hard sciences,” but in a socially produced objectivity, i.e., the fetishistic dynamics of capital, which is indifferent to the vital interests of human beings and nature and sees all the world only as a substrate for its valorizing movement.

A specific form of technological development is associated with the mathematical sciences, and the progress in knowledge that follows from them, which as a rule consists in the application of those structures, principles, or laws of nature that are discovered and investigated by the corresponding sciences. However, this technical development itself stands in a specific social context: This consists, among other things, in the fact that the fetishistic dynamics of capital favors technical developments which lead to a saving of abstract labor, so that their corresponding application results in a cheapening of the products and/or an opening up of new markets (not to be forgotten are the military: war research, etc.).[8] Technical development, together with the associated basic research, takes place in such a way that, for the most part, developments correspond to the valorization imperative of capital, or at least meet it. This also includes the establishment of the dissociated sphere, which forms the mute prerequisite of valorization; Fordism, for example, would hardly have been possible without the corresponding enforcement of a petty-bourgeois family structure.

Thus, with a quite understandable critique of technology, it must be insisted that the causal issue here is not “technology” per se, as alluded to, for example, in the works of Günther Anders (especially in Antiquity of Man I/II), but rather the fetishistic dynamics underlying it. For instance, a rejection of individual transportation does not necessarily mean that the internal combustion engine as such would be abolished. And the fact that the whole world is being filled up with microelectronics does not necessarily follow from the invention of the transistor; rather, the cause and justification lies in the commodity-producing patriarchy itself and its indifference to the material content, the inherent logics of nature and its boundlessness, which finds expression in Marx’s formula M-C-M’ etc. (Cunha 2016, Heintz 1992). This “technological totalitarianism,” as it is called in places in the bourgeois feuilleton, is therefore itself an expression and consequence of the totalitarianism of the value-dissociation relation. This does not mean, however, that technology would only have to be “liberated” from the fetish of capital without undergoing significant changes itself, since its development and realization are already shaped by the valorization requirements of capital. This can be seen in the sometimes-nonsensical business implementation of a so-called utility value: Thus, to increase sales, emphasis is placed on planned wear and tear, or planned obsolescence. For example, tear-resistant pantyhose or long-life light bulbs were withdrawn from circulation when it became clear that the market would otherwise be saturated much too quickly (Reuß & Dannoritzer 2013).

Through the fetishistic dynamics of the value-dissociation relation, a specific purpose is baked into technology, which of course will change or even become obsolete when the social relations and the corresponding subject form of people in capitalism are overcome. For some use values or technologies it may seem difficult to imagine or even absurd that they could find use in a liberated society, be it individual transport or nuclear weapons. For others, however, from our current perspective, it is not necessarily clear. This means that while technologies and their implementation are form poisoned, their potentialities do not necessarily merge in the social form into which they are squeezed. The issue is also complex because the precursor to technology is a socially mediated relationship of engagement with inanimate and/or animate nature that finds expression in contemporary natural sciences and their forms of thought and practice; it is a relationship to an external substrate of nature, but one that must be accorded an autonomy, a non-identicalness that cannot be reduced to discourse, human interpretation, and purpose. Otherwise, there would be claimed a total availability of nature, which, however, expresses nothing else than that nature is to be handed over to the capitalist imperative of valorization. A critique of technology is thus linked to a critique of the natural sciences, and both are to be related to the social context in which they take place. An acknowledgement of an autonomy of nature (which, however, is not to be confused with a “romanticism of nature”), together with a critique of the social form that negates it, leads to a kind of “dialectical realism” (Roswitha Scholz); in contrast to a “new materialism” or a “new realism” that, although it distances itself from poststructuralism and its fixation on discourse, does not take note of the social totality and therefore does not arrive at a critique of the value-dissociation relation (cf. Roswitha Scholz’s article in this issue).

Just as mathematical economic theory has already been criticized, the following will do the same regarding a recent trend in the scientific landscape: Big Data and the social physics based on it. To this end, the claim and the justification of this discipline will first be examined and then subjected to a critique.

3. The Social Physics of Alex Pentland

Alex Pentland is probably one of the best-known and most influential computer scientists currently working on Big Data. Big Data is the collection and analysis of data to an extent that has never been available before in history and is therefore no longer manageable with traditional statistics. In his book “Social Physics – How Social Networks Can Make Us Smarter”, Alex Pentland explains in a generally understandable way all the wonderful things that Big Data can do and what can be researched with it.

The use of Big Data aims to understand the social; and the corresponding scientific discipline is called “social physics.” However, as Pentland notes, because it abstracts from the human interior, its statements are fundamentally only probabilistic (Pentland 2015, 16). Nonetheless, the goal is “to build quantitative, predictive models of human behavior in complex, everyday situations” (Pentland 2015, 12).

But how exactly does this work and what promises are made?

It is initially quite simple: Vast amounts of data are gathered “by collecting digital bread crumbs from the sensors of cell phones, postings on social media, purchases with credit cards, and more” (Pentland 2015, 9). To this end, as Pentland repeatedly points out, special programs which record all sorts of things are installed on the “smartphones” of the subjects of the studies conducted. In this way, subjects can be observed in real time over an extended period, producing countless gigabytes of data in the process. This data is then used to help understand how an idea circulates between people and how this flow of ideas (idea flow), along with information, causes human behavior to change (or how it can be changed). To do this, a device was built to bring together the many sources of information: the “socioscope.” According to Pentland, this is expected to revolutionize the study of human behavior in the same way that, say, the microscope revolutionized biology (Pentland 2015, 10).

The crucial difference to conventional statistical sociology is that here, in principle, millions of people can be observed in real time over a longer period.

Furthermore, social physics should make one understand “how this flow of ideas ends up shaping norms, productivity, and creative output of our companies, cities, and societies. It enables us to predict the productivity of small groups, of departments within companies, and even of entire cities. It also helps us tune communication networks so that we can reliably make better decisions and become more productive” (Pentland 2015, 4).

In social physics based on Big Data, the aim is to filter out correlations from the data and then model them mathematically. In this way, human behavior (or traffic), among other things, can be predicted and optimized. This is accomplished by looking at the data of many individuals and their respective “peer group,” i.e., the immediate social environment, cliques, etc.

Pentland shows unbounded optimism about the expected results of social physics: “For the first time, we will have the data required to really know ourselves and understand how our society evolves. By better understanding ourselves, we can potentially build a world without war or financial crashes (!), in which infectious disease is quickly detected and stopped, in which energy, water, and other resources are no longer wasted, and in which government are part of the solution rather than part of the problem” (Pentland 2015, 18f.).

We will also owe “[a] much better government” to social physics (Pentland 2015, 138), and in doing so, if I understand Pentland correctly, we can dispense with the traditional means of a political discourse. Pentland’s point of view can therefore be seen as an indication that capitalism’s “ability to shape” through political discourse has historically reached its limits, and thus political discourse as such has become irrelevant, since it moves within capitalist real categories that today reach their absolute limit and can therefore mobilize “potential for shaping” only in their wildness. Robert Kurz thus consequently spoke of an “end of politics” (Kurz 1994).

By an “idea,” already mentioned above, Pentland means the following: “An idea is a strategy (an action, outcome, and feature that identify when to apply the action) for instrumental behavior. Compatible, valuable ideas become ‘habits of action’ used in ‘quick thinking’ responses” (Pentland 2015, 20). There is no clearer way to express the instrumental nature of this whole charade. It is also not surprising, as stated in various places in the book, that incentives are meant to get people to change or optimize their behavior. Critics see this as an intentional manipulation of behavior. The intentional manipulation can be seen in the fact that data collection and the study of the dynamics in social networks make it possible to intervene “to change the social network” (Pentland 2015, 5).

It is already easy to see here that social physics, due to the rather narrow horizon of its concepts and methods, will never (be able to) think about emancipation; and even less about a fetishism-critical analysis of society, which would be necessary for an adequate and critical understanding of this society. Only the allegedly objectively directly present individual is considered, who is thereby only seen as an information and stimulus processing system. The approach through which the individual is claimed to be understood is thus a reified one, one that has a tendency toward the totalitarian. It is also assumed that humans, as mere stimulus-processing machines, can be passively manipulated or steered in a desired direction (both by social physics and by some of its critics). But this would mean assuming that domination is only external to the subject, and has nothing to do with an active intrinsic part of himself. By this elision of the socio-psychological level and capering on the individual and his data, the social totality, which for people like Pentland is surely nothing but metaphysical nonsense, is completely lost from view. It is also consistent, as mentioned above, to abstract from the human interior, since this could hardly be modeled or formalized mathematically. It is similar to the behaviorism of earlier days, in which the human being was also regarded only as a collection of flesh to be steered and controlled. It is not by chance that Pentland advocates for conducting corresponding larger field experiments: “We need to construct living laboratories – communities willing to try a new way of doing things or, to put it bluntly, to be guinea pigs (!) – in order to test and prove our ideas” (Pentland 2015, 186). This hubris is not too surprising for a technocratic worldview wherein people are bluntly and openly referred to as guinea pigs! This  is hardly to be understood as a colorful metaphor, but rather much more as a threat. To call humans guinea pigs, to dehumanize them, however, means nothing other than that one claims to also treat them as such. This phenomenon is also known from medical studies in which people who participated in experiments were collectively referred to as “material,” and usually treated accordingly (Pappworth 1967, XI). In particular clarity, this dehumanization of human beings supported by science was evident in psychiatry, where people were (or are[9]) effectively reduced to a vegetable.

Pentland’s social physics, as already indicated, is primarily concerned with productivity and how this can be optimized. Studies have shown that the more people communicate or interact with each other, the better the flow of ideas, which has a positive effect on the productivity of a company (Pentland 2015, 93f.). Who would have thought that? The book also stands out for other groundbreaking findings: For example, a family is more mobile and interacts with a greater variety of people when it has more money (Pentland 2015, 164). These exceedingly profound research findings already seem somewhat ridiculous and trivial in light of the élan and pretension with which Pentland promotes Big Data social physics. This phenomenon is nevertheless striking and in need of explanation, that sciences, when they claim with élan to finally be able to understand humans and society with their technical and mathematical instruments, often end up with rather trivial results, if they do not even produce more or less “mythology,” as it has been noted for instance in the case of neuroscience (Hasler 2012). This was also already noticed by Stanislaw Andreski (1919-2007), who at the time wrote a polemic against the social sciences of the time, specifically against Skinner’s behaviorism, which, in my opinion, could also be used against Pentland’s digital behaviorism: “The problem of how to control the behavior of humans and animals by punishments and rewards has been treated in innumerable treatises on penology, legislation, education, management and animal training, starting from the works of Aristotle and Confucius, not to mention the countless proverbs and wisdoms of the vernacular. It is always possible to say something important and new about this subject, but it is also very difficult. But a bit of pseudoscientific terminology can confuse and intimidate people into thinking a highly simplified and therefore less valid version of ancient folk wisdom is a significant development” (Andreski 1977, 72).

One reason why a high standard ends up in rather trivial results may be that a technocratic and mathematically oriented approach does not do justice to its subject matter. Pentland refuses to look at structural social contexts. He rejects categories such as “market” and “class” because they are too simplistic for him. Of course, the point here is not to demand that categories like class or market be made strong again; at best, that would only result in a social analysis and critique of traditional Marxist provenance. But it is nevertheless important to note that parts of the bourgeois intelligentsia are in the process of saying goodbye to social conceptualizations for good. We thus see that there is a clearly pronounced methodological individualism in Pentland. Through this, the ability to consider social relations as having become historical is reduced, and it becomes impossible to analyze and question social relations and, a fortiori, the fetishistic constitution of them. Consequently, the understanding that  social physics gives access to is a technocratic and domination-affirmative one, since it makes, above all, any historical thinking impossible. Social physics does not allow us to see the historical development of “social facts,” which would be a basic prerequisite for their critique and thus also the possibility of overcoming them in an emancipatory way.

This also strikes some representatives of the bourgeois intelligentsia. The journalist and Internet critic Nicholas Carr, for example, writes about this approach that “[a] statistical model of society that ignores issues of class, that takes pattern of influence as givens rather than as historical contingencies, will tend to perpetuate existing social structures and dynamics. It will encourage us to optimize the status quo rather than challenge it” (Carr 2014).

The left also criticizes the fact that social physics would make “relations of domination invisible” (Wagner 2016, 149).

However, a concept of domination, as it is used by many leftists in particular, which is often understood as an external or personal one, must be rejected. This is also echoed in various left critiques, such as Wagner’s, against Big Data, and so on. However, relations of domination ought to be understood as fetish relations. Thus, in the text “Subjectless Domination,” Robert Kurz writes: “The ‘domination of man by man’ must not, therefore, be understood in the crude external and subjective sense, but as the all-embracing constitution of a compulsive form of human consciousness itself. […]The concept of domination must therefore not be merely rejected so as to raise the concept of the constitution of the fetish in its place, which would reduce the subject and his declarations to a simple marionette. Rather, the concept of domination and its mediating concept “power” must be deduced as concepts from the universal phenomenal form of the constitutions of the fetish, which in turn are manifested both practically and sensibly as the spectrum of repression or self-repression in diverse forms and on various planes. The in-itself unconscious form manifests itself to consciousness as domination on all planes. In the figure of domination, the subject as a being constituted by the fetish makes real contact with himself and with others. The objectivized categories of the constitution thus form the (respective) pattern or matrix of domination. (Kurz 2004, 206f.).

Criticism of domination, whether in the abbreviated sense or as criticism of the fetish constitution, is of no interest to Pentland and other social physicists. However, Pentland at least (!) sees that the data sets could also be abused and used against the people. This also applies to anonymized data, as they can usually be deanonymized relatively easily (Pentland 2015, 228, 204). That is why he, in all seriousness, proposes a “New Deal on Data” (Pentland 2015, 180f.). In other words, a series of measures to ensure that individuals remain sovereign over their data, i.e. that each individual decides what is to be done with their own data. However, he does not mention the possibility of questioning this exorbitant data collection in principle and at least making it conceivable to possibly end it (just as questioning individual transportation makes its abolition conceivable). Instead, one gets the impression that technical and scientific developments are to be accepted as an inevitable fact of nature that could at best be regulated by the state.

In principle, the protection measures outlined by Pentland make sense and a commitment to them should be acknowledged. However, his plea for a defense of privacy (which is eroding anyway due to technological and social developments) is not very credible when one looks at some of the possible applications: In principle, everything can be monitored. These techniques are virtually predestined for such things, and an important motivation for their development is precisely this type of monitoring. In an interview with “Spiegel-Online,” he answers the question of whether he would intervene if, in a family being monitored, the father was drinking too much: “No, never. But we might in the future. The more science is moving forward and the better we understand human behavior, the more you get the obligation to act” (Pentland 2014). This suggests what might be called “digitized paternalism,” a mindset that also plays a large role in so-called “nudging.” I’ll come back to this later.

One thing that could be done with Big Data, which is probably actually meaningful (or rather negatively meaningful), would be to follow the existing material paths of industrial production. Not, however, with the aim of “optimizing” them in a capitalistic way, but rather to determine and denounce their utter madness: The absurd material distribution chains capitalism manages due to its processual dynamics, for example in the cultivation of apples, or the production of yogurt, has already been investigated in some places, such as in a study by Stefanie Böge (Böge 1992, 2001).

As is well known, the goal of the capitalist mode of production is the successful valorization of capital. An individual capital achieves this by trying to attract to itself as large a share as possible of the mass of value produced by society as a whole through competition. The consequence is, as Marx already described it, a growing concentration of capital. He put in a nutshell with “one capitalist always strikes down many others” (Marx 2005, 929). Today, this phenomenon must be seen specifically in the context of the globalization of the past few decades, i.e. unlike in Marx’s time, capital concentrations and mergers are not to be understood as an expression of an expanding total capital, but as a rationalization investment due to a contraction of total capital, as a mode of its crisis course (cf. Kurz 2005, 288f.).

However, it also follows from this merging dynamic that the “winner” takes over the market share of the dead beat, which means that the victorious apple producer then supplies the whole world with apples that could just as easily be grown “locally.” This leads to ever greater transport distances, and the corresponding consumption of resources, which are fatalistically accepted with a shrug of the shoulders. This madness exists in material terms, not in economic terms: In terms of the logic of valorization, this absurdity is not absurd at all; it has its origin in economic “reason,” and in accordance with it, this world is being productively disfigured.

In a critique of the material results of capitalism, it is therefore necessary to insist that it is not the material level per se that leads to environmental destruction, waste of resources, etc., but the social form in which the “use values” must move, whereby the material content is adapted to the form. The growing concentration of capital and even more the “contradiction between matter and form” (Ortlieb 2009) do not come into view if only the data scrap of many individuals is analyzed and the whole world has only “optimization” in mind.

As we will see in the following, the function of Big Data and its applications is obviously a socially repressive one (on the part of the state and on the part of individual capital), as Pentland has already openly and bluntly indicated. Big Data has accordingly been used as an instrument of repression for a long time, as the mathematician Cathy O’Neil shows phenomenologically in her book “Weapons of Math Destruction.”[10]

4. Applied Mathematics as A Means of Repression

In our digital brave new world, all kinds of data are collected and stored in huge databases. The data are then evaluated by certain algorithms or mathematical models. In this way, a person’s credit-worthiness, a job applicant’s fitness for hiring, the probability of a criminal recidivating (!) (and court decisions are made accordingly), or the likelihood of crimes occurring in a certain neighborhood (!) can be calculated. Algorithms are also used to make evaluations that determine whether a person will continue to be employed as a teacher. O’Neil brings up all sorts of examples in her book. The perfidious thing about algorithms is that what they do and how they do it usually remains a trade secret. So the algorithm’s judgment is absolute, and no contradiction is possible. This typically remains the case because these algorithms rarely have “error feedback” (O’Neil 2016, 133) (or they just positively feedback on themselves, a “pernicious loop feedback”) that could cross-check whether an algorithm was actually correct. Thus it is clear that these algorithms have extremely repressive consequences for many people, which is why O’Neil calls them “weapons of math destruction” (WMD). These “weapons” are “by design, inscrutable black boxes; they define their own reality and use it to justify their results. This type of model is self-perpetuating, highly destructive – and very common” (O’Neil 2016, 29, 7).

One problem here is that (applied) mathematics is not accessible to many people and they are therefore often helpless in the face of the judgments of such a model. This helplessness is also the result of the contemporary belief in numbers and the uncritical perceptions of the “objective sciences.” But models of this kind are anything but objective: “A model’s blind spots reflect the judgements and priorities of its creators. […] Models are opinions embedded in mathematics. […] these models are constructed not just from data but from the choices we make about which data to pay attention to – and which to leave out” (O’Neil 2016, 21, 218, emphasis TM).

O’Neil writes: “Nevertheless, many of these models encoded human prejudice, misunderstanding […] Like gods, these mathematical models are opaque, their workings invisible to all but the highest priests in their domain: mathematicians and computer scientists. Their verdicts, even when wrong or harmful, are beyond dispute or appeal” (O’Neil 2016, 3).

Moreover, the actual predictive power of some of these models is extremely poor. For example, Andreas von Westphalen points out that: “An elaborate study by ProPublica […] proves that at least one frequently used algorithm discriminates on the basis of skin color. The study also shows that accuracy of the risk calculation leaves much to be desired: Only 20 percent of people predicted to commit a violent crime actually committed a violent crime in the next two years. ProPublica ironically judges that-even if all felonies and misdemeanors were included – the prediction is only marginally more accurate than a coin flip” (von Westphalen 2016, 63f.).[11]

The crucial problem of such algorithms or models is that they are often self-referential. This is the case, for example, in the preventive fight against crime. The databases show that a high number of crimes, especially so-called “drug crimes,” have been detected in black “problem neighborhoods.” The algorithm predicts a high probability of crime in these neighborhoods. The police react with appropriate presence – and lo and behold – numerous crimes are detected and the algorithm is deemed a “success.” So the algorithm creates an interpretation of the world that always confirms itself. It is clear that there is a positive feedback loop here which will lead to even more police presence. In this way, those affected are punished for their very existence, their poverty is criminalized: “In this system, the poor and nonwhite are punished more for being who they are and living where they live. […] The result is that we criminalize poverty, believing all the while that our tools are not only scientific but fair” (O’Neil 2016, 97, 91).

Racist structures and social relations are therefore reproduced and cemented by Big Data and algorithms, although these algorithms claim to be  “objective” or even “fair,” as is strived for above all in the judiciary; an algorithm cannot possibly, for example, “judge” in a racist way. However, what is forgotten here is that it is humans, who may well be racist, that develop them; and even if they are not explicitly so, a racist and socially repressive reality is mathematically modeled through them, and with certain assumptions made, is thereby reproduced (O’Neil 2016, et al. 24-27). For example, risk assessment algorithms calculate the likelihood of a delinquent recidivating using methods such as  questionnaires. However, these questionnaires are constructed in such a way that someone who grew up in a “problem neighborhood” is inevitably calculated to be at higher risk. It may be argued that racist results do not necessarily follow from this methodology; but – and this is crucial – whatever assumptions and questionnaires are used, the goal of these methods is to model a racist reality, with the aim of more efficient and less costly law enforcement.

Thus, I think Big Data and its applications are probably only of secondary importance at this point; for high police presence in black “problem neighborhoods,” a “war on drugs,” mass incarceration of the poor (cf. Wacquant 2013, Meyer 2017), etc., existed before the times of Big Data. O’Neil’s focus is not on a clear analysis of the social causes of racism and crime; she does complain that Big Data and its applications, or some of them, i.e., the “weapons of math destruction,” would endanger democracy; but she does not question whether democracy is itself already a system of domination and to what extent applied algorithms are only the technical means by which a struggling capitalism deals with its delinquents, poor, and fallen out.

The extremely conservative character that data collection assigns to people because of their social behavior is similar. As a result of all their data being collected, people become fixed to their past: “Big Data processes codify the past. They do not invent the future. Doing that requires moral imagination, and that’s something only humans can provide” (O’Neil 2016, 204). This is due to the fact that “mathematical models, by their nature, are based on the past, and on the assumption that patterns will repeat” (O’Neil 2016, 38).

For example, someone could not get a job just because he had a stay in a psychiatric hospital a few years ago. A corresponding algorithm would filter out such candidates. However, it should be noted that such practices were just as common in earlier times and so an algorithm cannot be the primary problem here. Today this may be even more blatant, since much more data from much more people is available much faster. However, according to the logic of valorization, it is quite understandable why people with (formerly) severe emotional problems are rejected as applicants, since they are indeed dysfunctional for the company, or could be. Every single capital has to compete, but this also means that personnel costs, like all others, should be kept as low as possible. The problem, then, is not an algorithm in the causal sense (no matter how accurately it may “judge”), but the requirement to exist as a labor container and to be filtered out or put away (even with “well-meaning” pedagogical and re-socializing goals) if this requirement cannot be met.

This practice of filtering applicants with the use of algorithms is now common: “Such tests now are used on 60 to 70 percent of prospective workers in the United States, up from 30 to 40 percent about five years ago […]” (O’Neil 2016, 108).

Interestingly, however, it is often not at all a matter of finding the best candidate by sorting them out, but of quickly and cheaply getting rid of as many as possible (O’Neil 2016, 109).

The reduction of costs is the driving force behind the application of these algorithms: “For most companies, those WMD’s are designed to cut administrative costs and to reduce the risk of bad hires […]. The objective of the filters, in short, is to save money. […] Replacing a worker earning $50,000 a year costs a company about $10,000, or 20 percent of that worker’s yearly pay, according to the Center for American Progress. Replacing a high-level employee can cost multiples of that – as much as two years of salary” (O’Neil 2016, 118).

However, O’Neil remains at this phenomenological level and does not attempt to explain why job mobilization demands ever-increasing up-front costs, or why a seemingly excessive number of job applications flood companies and prove disruptive.

As explained, O’Neil points out the socially repressive character of Big Data and subsequently writes that Big Data threatens to go the same way as phrenology did a few centuries ago (O’Neil 2016, 121f.), i.e. to develop further into a repressive machine (or, to be more precise: to digitally upgrade the previous repression machine). This is not only because the whole procedure is opaque (trade secrets[12]), but also because many algorithms or models include questionable assumptions or prejudices that ultimately have socially repressive consequences. Big Data can therefore rightly be described, at least in part, as “mathematized charlatanry” (Ortlieb 2006).

Although O’Neil criticizes the questionable applications of Big Data, denounces its repressive consequences, makes the claimed “objectivity” of mathematical modeling highly questionable through her remarks (“Models are opinions embedded in mathematics.”), and suggests the inappropriateness of these models for describing human behavior, she nevertheless does not arrive at a principled questioning of the positivist way of thinking.

Let’s assume that algorithms and models are developed that are actually correct and accurately reflect the behavior of people: What would be gained by this with regard to the critique of social repression? At this point, at the latest, it should be obvious that an immanent critique of science, for all its necessity, has its limits and must be extended by a critique that goes beyond it. This must include a critique of the social subject-object dialectic, which one will look for in vain in such immanent critiques. For example, in a critique of the model of homo economicus, critics argue that people cannot be reduced to this conception of man, and that it is therefore not realistic; on the other hand, it is countered that many people actually behave in many situations exactly as if they acted according to this model (otherwise they would have to accept economic disadvantages) (Baumbach 2015, 297f.). Now how is this “fact” to be understood? The positivist scientific establishment would only feel confirmed, the model assumptions would be true and this external fact would thus be as certain as the former existence of the dinosaurs or the spherical shape of the earth. However, it is a fact, although people are not absorbed in this, which was produced only by the social action of the people themselves, and influences them as a compulsion, i.e. an act-thing which confronts them as objectivity.

However, if one restricts oneself to an immanent critique and concludes from this only that naively or incorrectly applied methods should simply be corrected with better or more stringently applied ones, then this almost inevitably leads to a continued affirmation of existing conditions. Thus, it is known that various critics of neoclassicism ultimately ended up in “post-autistic” or “heterodox” economics, which, according to their claim, want to develop more realistic modeling, but just like neoclassicism do not question the bourgeois forms of circulation, labor, etc., and the usual scientific forms of thought.

The danger of increasing social control emanating from Big Data is also increasingly being discussed in other places. Some time ago, several scientists published the “Digital Manifesto.”[13] This manifesto aims to draw attention to the totalitarian development paths made possible by Big Data. It looks admonishingly at China and Singapore, which give us an idea of where the journey of digitalization could lead: “The concept of a Citizen Score, which is now being implemented in China, gives us an idea of this: By measuring citizens on a one-dimensional ranking scale, the plan is not only comprehensive surveillance. Since the score on the one hand depends on clicks on the Internet and political good behavior, but on the other hand determines credit conditions, possible jobs and travel visas, it is also about the patronization and social control of the population” (Digital Manifesto 17).

Thereby it is noted that if similar things would also come about in the western democracies, it would be irrelevant whether it would come through the state or through private companies (like Google![14]). Unfortunately, these people seem to miss the fact that in the West the things indicated in the quote have been going on for a long time, which Cathy O’Neil was not the first to point out (von Becker 2017). Of course, it is also not taken into account that the so-called democracies have long been “post-democracies” (Colin Crouch), surveillance state-of-emergency regimes in which everyone tends to be given criminal status qua existence, a development that can be seen very clearly in all the manifold measures that have been tackled after 9/11 (cf. Kurz 2003b, Trojanow; Zeh 2010).

Two explosive and extremely clear examples from the wonderful world of democracy should be cited. Since 2009, the EU has been working and researching on a project called INDECT: “The computer-based surveillance system is to automatically detect ‘abnormal behavior’ and identify suspects by facial recognition and database matching. To do this, the Internet and primarily urban space will be seamlessly monitored. Information from social and private networks will be linked with other databases, such as police records, using automated facial recognition through camera surveillance, and biometric data from identity cards and passports, which will be available in digitalized form, and will also be used. […] INDECT is thus another form of artificial intelligence. The concrete networking and evaluation of the data happens – how could it be otherwise – behind closed doors. Those responsible for the project equate ‘abnormal behavior’ with ‘criminal behavior.’“

This consists not only of looking into the camera screaming “Allahu Akbar” shortly before pressing the button, but also, among other things, “walking too fast or too slow, screaming or swearing, moving in the wrong direction, ‘loitering,’ meeting with many people, staying too long in the direct vicinity of a certain object […]. Once a suspect – and who wouldn’t be a suspect given the behaviors labeled ‘abnormal’? – come into the sights of INDECT, the smallest remote-controlled surveillance drones with built-in high-performance cameras are to be used to identify and track the suspect. These drones are networked with each other and are supposed to cooperate with each other ‘intelligently and autonomously,’ thus forming drone swarms” (Jansen 2015, 109f.).

The next logical step would be to arm such drones and continue automated warfare, as is being waged in Afghanistan and elsewhere, in the Golden West itself.

The “world’s most populous democracy” – India – has come up with the following: “The world’s largest biometrics project by a single state is being carried out in India. An estimated 1.2 billion people, one-sixth of the world’s population, are being digitally enrolled on the Asian subcontinent. The project is called ‘Aadhaar’ […]. Specifically, the biometrics project envisions that every Indian, whether pariah or social elite, will have digital scans of their ten fingerprints and both irises, as well as a photo of their face, taken, processed and stored in a digital database. Each Indian is also to be given a twelve-digit ‘Unique Identification Number’. […] Not only biometric, but also demographic information, such as name, age, gender or even caste (!) is linked to the number. This only further cements the still racist separation of Indians into different castes […]” (Jansen 2015, 105f.).

The numerous surveillance possibilities of Big Data in combination with “artificial intelligence” are wonderfully suited for the permanent state of emergency, social control and (preventive) counterinsurgency. The difference between the EU and China, for example, is only a gradual one. However, it does not occur to the authors that digitalized capitalism is virtually predestined for the purposes described above and that a digital capitalism without them would probably not be possible – in view of the real existing social disruptions and the crisis-like conditions in which these technologies and their developments are situated. But none of this is taken into account. It is always the others who are totalitarian! (cf. Kurz 2001, 2002a)

However, the following should be emphasized here: Although these numerous surveillance technologies suggest the realization of a total state à la George Orwell’s 1984, this moment should not be overestimated either. First of all, these technologies are used primarily by private companies, thus also playing a major role at the level of individual capital, and second, state sovereignty itself is in the process of erosion and barbarization. This can be seen, on the one hand, in the fact that the state security apparatus is decaying by aligning itself with private terror gangs, as can be clearly seen, for example,  in the Third World.[15] On the other hand, the apparatus of force is also subject to funding constraints that can hardly leave its ability to function untouched: Thus, the expansion of camera surveillance coincides with constant talk of a lack of personnel, i.e., to some extent the techniques of surveillance, etc., can also be understood as rationalization measures. In the military, this is even clearer: In recent years, for example, “drone warfare” has been pushed because it is cheaper than regular intervention, since “world order wars” are apparently reaching the limits of their financial viability.

If the worst came to the worst, these technologies would be used to put down uprisings and maintain “security,” at least according to the intention; but whether it would really work out that way is more than questionable; after the uprising, the state of emergency would only continue, a civic normality of “law and order” would hardly come about, rather, a molecular civil war, a state of emergency dictatorship, or something similar is to be expected. The omnipotence of Big Brother ends in its inability to be financed.

Furthermore, the Digital Manifesto, like Pentland, criticizes the use or misuse of data against the interests of its owners, as is evident in personalized advertising, nudging and the phenomenon of the “filter bubble.” The latter is about search engines sending the “user” specifically what corresponds to their (supposed) preferences. The consequence is a self-referentiality, “a kind of digital thought prison” (Digital Manifest 15), which consists of someone only being fed the news, films, or books that a corresponding algorithm has determined from their media consumption past; there would then be no more surprises, no things to rub up against and argue about together with others (Simanowski 2014, 78f.); in this way, “personalized information can unintentionally destroy social cohesion” (Digital Manifesto 11).

It is clear, however, even if the authors do not say so, that these “filter bubbles” are very congenial to neoliberalism and its ideology, according to which there is no society anyway, but only individuals who move about consuming on markets. And this technology also offers the narcissistic social character some feel-good advantages; namely, not having to deal with the world outside of the parallel universe knitted together by oneself. It should be emphasized that here, too, technology should not be causally blamed for this effect, it reinforces and continues it; however, people are already narcissistic and incapable of conflict, and it is precisely this that enables them to exist in their virtual world, in their “echo chamber” as “users” without throwing up.[16]

Despite some criticism, the authors of the “Digital Manifesto” do not question digitization in principle (or capitalism); because, as a certain Professor Weikum says in an interview, “digitization itself […] is an evolutionary phenomenon that has been emerging for a long time.” Although others see and criticize totalitarian tendencies above all (!) and therefore advocate a debate for some “regulation,” Weikum speaks out against it: “Science must not be regulated; that would be like censorship in journalism or the prohibition of anatomical studies by the church in the Middle Ages” (Digital Manifesto 49f.).

Evolution and the Middle Ages are exactly the catchwords that are mobilized when the scientific establishment does not know how to justify itself otherwise. Of course, “regulation” is not the answer, but it is clear how quickly the limit of reasonable criticism is reached with some.

However, a fundamental questioning of digitization is not the same as a consistent rejection of digital technology altogether. There may be sensible applications, or they may be able to be developed, but to do so, the corresponding substantively determined criteria for meaning and purpose would first have to be established. But this is only possible in the context of a radical critique of capitalism; because the only standard or criterion that capitalism can think of and implement is the valorization of value and the maximum expansion of markets, etc.; and it is clear that this standard cannot be suitable for judging the meaning and purpose of a (possible) technology, since the material and social levels are fundamentally abstracted from. If they do appear, then they do so as a business cost or disruptive factor. There is no doubt that this is nothing new in principle: If rationalization threatens an older technology due to “moral wear and tear,” it has always been replaced by the more cost-effective and logically more efficient technology, and this has happened wherever a corresponding market has opened up. The resulting social and ecological catastrophes were then accepted and played down as alleged necessities of “progress.”

Thus, digitization de facto means the implementation of digital technology on all levels of society (subject to financial feasibility). This “technological totalitarianism” fueled by the fetishistic dynamics of capitalism must be fundamentally questioned and rejected!

5. The Internet of Things and The Idiocy of The Abstract Individual

Another field of activity for Big Data is the so-called “Internet of Things,” which includes all kinds of devices that are characterized by their “smartness.” Due to the enormous reduction in the cost of sensors, it is now possible to equip all conceivable devices in industry and private life with sensors (billions of them!). These sensors scout out the status of the device and its environment and record everything that can be detected by them (or by cameras). A corresponding connection to the Internet results in the “Internet of Things.”

This results in smart watches, smart trash cans and smart kettles, smart refrigerators, etc. Indeed, the development of such devices serves to make consumption as “sustainable” as possible, at least according to their manufacturers. For example, Evgeny Morozov writes about smart trash cans in his book Smart New World: “BinCam, a new project by British and German researchers, aims to modernize the way we deal with trash by making our trash cans smarter and – you guessed it – more socially conscious. Here’s how it works: A small smartphone is attached to the inside of a trash can lid that snaps a photo every time someone closes the lid – to document what was just thrown away, of course. A group of poorly paid people recruited through Amazon’s Mechanical Turk website then evaluates each photo. How many things are on it? How many of them can be recycled? How much food was thrown away? Along with this information, the photo is uploaded to the Facebook page of the person who owns the garbage can. There, other users can view it. The creators of BinCam hope that when there are smart trash cans in many households, with the help of Facebook, recycling could be turned into a fun competition. Weekly results are calculated, and when the amounts of food and recyclable material decrease, the owners receive (symbolic) leaves and gold bars. Whoever collects the most leaves and bars is the winner. Mission accomplished, planet saved!” (Morozov 2013, 20)

Not only is everyone’s every expression of life documented, but everyone is also required to optimize themselves and their own consumption in terms of sustainability (and health). Because that is not enough, an infantile little game is made of it. Morozov calls the latter phenomenon “gamification.” What should actually be the subject of critical discourse is translated into an infantile game, for example, by encouraging people to save electricity through a “’dialogue without words’ […] cast in technology. One of these is the Caterpillar – an extension cord (in the shape of a small caterpillar) designed to make its user think about how much energy is wasted by appliances in stand-by mode. The caterpillar has three modes of operation: When the plugged-in device […] is turned on, the caterpillar breathes slowly and steadily; when it is turned off, it does nothing; but when it is in stand-by mode, the caterpillar begins to writhe and twitch as if in pain. Will the owners meet the caterpillar’s needs as if it were a living being?” (Morozov 2013, 539)

Morozov brings up even more examples. Like smart kettles that light up red when they shouldn’t be used because the load on the power grid would otherwise be too great at that moment. So smart things help us save electricity and, on top of that, do something good for the environment! Thank goodness!

Morozov called such a technology-reductionist and at the same time socially and historically ignorant view, as it shines through in what is mentioned here, “solutionism”: The narrow-mindedness of the solutionist makes itself clear by the fact that he only knows his hammer and sees only nails everywhere (Morozov 2013, 25f.).

Similarly, people optimize their consumption through “self-tracking,” i.e., recording personal data, life functions, such as sleep, etc., which should then allow us to monitor our personal “carbon footprint and minimize our own carbon dioxide emissions by buying more efficient products and using greener transportation” (Morozov 2013, 546).[17]

That consumption is not “optimal,” not necessarily healthy, is well known. However, it is no longer left up to the individual to decide what and how much to consume; there is a tendency, which has long since taken the form of political action or agitation, to “nudge” people in the supposedly “right direction” (for example, by making “unhealthy” candy bars difficult to reach on the shelves, as opposed to “healthy” lettuce, so that the former is presumably bought less) by “subtle manipulation” (nudging). Its supporters justify it by asserting that humans typically make the “wrong” decisions and because they are mere fools, who are meant to be guided in order to be protected from themselves! The justifications could be summarized so openly and bluntly at any rate. In this way, as critics complain, a new “gentle” or “libertarian” paternalism emerges, which “incapacitates” the citizen and imposes a neo-Protestant asceticism on them (with savings on health insurance, if it is proven by self-tracking that one lives healthily and walks at least 1000 steps every day). A paternalism which wants to make people reject everything that is allegedly or actually unhealthy (such as fatty currywurst or cigarettes). So-called “public health” is therefore only a matter of individual consumption, not of production and certainly not of the conditions and social relations in the world of work and reproduction!

This directly abstract-individual perspective, as it shines through in nudging, is not only found in social physics or in behavioral economics, but also in the critiques of nudging, which are often liberal. Thus, to summarize, they usually insist on the “maturity” of the individual, on the “freedom of choice”; instead of “manipulation” they call for “political discourse” and “enlightenment”: the individual would then be fully aware of what is best for him.[18] But even these positions usually suffer from the fact that consumption and its contents are broken down to the supposed freedom of choice of the individual, the “responsible consumer,” i.e. to the idiocy of the abstract individual. Unfortunately, what liberals do not see is that this wonderful bourgeois “maturity” also consists precisely in internalizing the coercive relations of capitalism and acting according to their imperatives, without the need for a state apparatus of force. The freedom of choice of the “responsible consumer” is ultimately the freedom of the enslaved.

This upheld bourgeois freedom is on the one hand arbitrary in content and at the same time profoundly one-dimensional: “The freedom of thinking, producing and consuming contains […] on the one hand an absolute arbitrariness […]. Once again, the content does not matter at all. In this respect, freedom, thinking, opinion and criticism are always already qualitatively empty; or their content is accidental, external and, in the truest sense of the word, unessential. On the other hand, however, the same abstract freedom contains a merciless limitation and exclusion. Its social form is in no way arbitrary, but completely one-dimensionally fixed; it defines all relations, for it is, as Marx just rightly said, at once the form of existence and the form of thought in this mode of production and life. Not even the slightest criticism of it is permitted. Whoever violates it is imprisoned; whoever questions it is declared insane. One is only allowed to do almost everything because one is not allowed to do precisely one thing, namely to break open this ‘cage of bondage’ (Max Weber), the iron form of being allowed. The arbitrariness of the content of commodity and money relations forms a coercive relationship without parallel. This is the secret of all democracy and freedom in modernity.” (Kurz 2017, 78)

The form and content of consumption, energy usage, transportation, etc. should indeed be the subject of critical discourse. With smart technology and the accompanying nudging, however, these problems are shifted to the level of the individual and individual consumption, thus removed from any critique; no other level comes into view for these highly unsmart people. A critique of consumption or, more precisely, a critique of the material results of capitalism can, however, only be meaningfully developed by including the level of society as a whole, in which the determination of form and the arrangement of content by the capital relation, by the valorization of value and by the gender dissociation, must be taken into account.

A critique of the consumption of the individual leads nowhere if one does not even look at how production actually takes place. For example, the technical progress in agriculture in the United States, more precisely in the corn industry, since the 1970’s, not only led to a cheapening of corn, but also resulted in “mountains of corn” which “had” to find a market somehow. So, from then on, a sugar concentrate was produced from corn and added to a vast amount of food. This is said to be responsible for the high level of obesity and diabetes in the US population. As Tomasz Konicz writes, “Productivity increases in capitalist agribusiness thus lead not to conservation of limited natural resources, but to efforts to create, by hook or by crook, new fields of demand to sustain the valorization process – even if this means using the human body as a fructose dump” (Konicz 2013, 19).

The southwestern United States has been suffering from water shortages for years. However, agriculture continues to grow the very crops (such as almonds) that require a lot of water. Instead of reducing the production of these crops due to the drought and switching to other, less water-intensive crops, they are still grown because they are the most profitable! (cf. Konicz 2014)

Therefore, it is obvious that it is completely pointless, in the pursuit of sustainability, health, etc., to look only at the consuming individual or the end product to be purchased, without including the societal level. An orientation towards the individual, the “consumer,” misses the point.

In her critique of the anthropology of the bourgeois individual, Franziska Baumbach, referring to Marx, writes the following: “To understand society as a stringing together of individuals overlooks the fact that social structure is determined precisely by the form of intercourse in which people deal with one another. In a society of free competition, in which the isolated private producers encounter one another socially through the exchange of their commodities, the person appears as a completely independent individual. This result of the capitalist mode of production, isolated individuals, leads to a worldview that, misjudging cause and effect, seeks to form a picture of the individual human being without taking social circumstances into account” (Baumbach 2015, 160, emphasis TM).

Beyond Baumbach’s remarks, Robert Kurz notes that: “If, however, this whole or the ‘total process’ as capital fetish or ‘automatic subject’ [is] the real precondition and thus forms the determination of the essence of their relations made is independent of its own actors and has slipped away from them, then the apparently ‘independent from each other’ private producers or individual capitals are in reality already socialized ‘behind their backs’ before they empirically enter into a relationship on the market. As the real actors, they can only accomplish afterwards through the market what exists objectively in advance, namely the all-round mediation, mutual dependence and deeply stratified division of the functions of social reproduction. It is a comprehensive concatenation of multiply structured, interlocking partial productions, supply relations and infrastructures, which has emerged through capital as an a priori total complex. […] For on the level of individual capital, it still seems to be a matter of an event that can be grasped in terms of action theory and is to some extent absorbed in subjective calculation, in which actors of interest directly confront each other. That which constitutes these actors themselves and which does not appear as a distinct object in their narrow-minded perception, namely the presupposed entity of the ‘total process,’ disappears in an immediate factual world. […] What transcends the acting subjects and constitutes the real valorizing movement, however, is the whole of the ‘automatic subject,’ the constitutive and transcendental a priori, which only appears in individual capital, but is not categorical” (Kurz 2012, 173, 177f.).

The sociality of the individual and its determination of form by the fetishistic whole must be insisted on, especially when every responsibility is given to the individual as an individual and the social totality is dropped under the table, as is so obvious in the debates about nudging, sustainability, etc.

The potential uses of smart products seem inexhaustible, Morozov goes on to write: “Nowadays, sensors alone, without a connection to social networks or data storage, can do quite a lot. For the elderly, for example, smart carpets and smart doorbells that detect and report when a person has fallen can be a great help” (Morozov 2013, 23).

This also indicates another area for the use of digital and smart technology: the care and reproductive sector. As Gisela Notz puts it: “Nursing robots developed by Japanese companies with strong arms and big googly eyes that can lift elderly people out of bed and put them in wheelchairs are already in use. There are teddy bears with electronic cores that dementia patients can cuddle, humanoid dolls equipped with artificial intelligence and voice recognition technology, and stuffed animals that can sing, stroke and speak which, according to reports from interested parties, are loved by the elderly. If there are problems, the nursing robot can inform the nursing staff” (Cf. the article by Andreas Urban in this issue.). There is also talk of smart kitchens “for the cook(!).” However, this does not dismantle “stereotypical gender images […] but modernizes and fixes them anew” (Notz 2016, 31).

Of course, industry in particular is also interested in equipping as many devices as possible with sensors. Once again, the point is to cut costs, because real-time monitoring of equipment allows companies to “squeeze their assets harder. Secondly, there is […] the possibility to predict the future reliability of machines and components and thus better ensure their maintenance” (Woudhuysen; Birbeck 2016).

Morozov also notes that cutting costs is a primary motivation for the introduction of smart products: “A start-up company with the pretty name BigBelly Solar wants to revolutionize garbage disposal with trash cans that use solar energy and built-in sensors to inform disposal companies how full they are and when they need to be emptied. This will allow garbage trucks to optimize their routes, saving gasoline. The city of Philadelphia has been experimenting with such trash cans since 2009. It has since reduced the number of garbage pickups from 17 to 2.5 per week and the number of employees from 33 to just 17. In a single year, this yielded savings of $900,000” (Morozov 2013, 23f.).

However, it should not stop at such specific points. The vision is that we will all live in “smart cities” at some point (Alex Pentland also raves about “data-rich cities”). However, as Rainer Fischbach points out, it is very questionable whether a society equipped with smart devices would actually reduce energy consumption, because their production and the corresponding infrastructure would also have to be included in the calculation. Apart from that, a smart world would be vulnerable to attacks from hackers, and the corresponding protection, which does not yet exist, would be very costly (cf. Fischbach 2015).

However, parts of the infrastructure are already “smart,” as Morozov also points out: “Cars that no longer start when the driver is drunk; closed-off communities that do not tolerate intruders; bridges from which one cannot jump; exact fare systems in public buses, thanks to which the driver no longer needs change and is therefore less likely to be robbed […]” (Morozov 2013, 320f.). Or the full body barriers in the subway system of New York that deny access to anyone without a ticket; fare evasion thus becomes impossible (Morozov 2013, 319f.). Ultimately, the goal of smarting up cities lies primarily in “situational crime prevention.” Thanks to smart technology, crime and deviant behavior are supposed to be abolished once and for all, although of course nothing is supposed to change in the social conditions that may underlie them. From this, one can see with clarity that Big Data technologies arise in the context of a security discourse and its corresponding bludgeoning practice. The consequences of a smart infrastructure, as Morozov emphasizes with clarity, would simply be that deviant behavior and thus lawbreaking would become ever-more structurally impossible. This, according to Morozov, would severely limit the possibility for a human being to act morally (compare the following excursus on ethics or morality in social criticism). The possibility for lawbreaking and deviant behavior are, however, on the other hand, as Morozov points out, necessary, as they can stimulate discourse and political change, as history shows, many changes have been made possible by civil disobedience and resistance[19]: in a smart city, for example, there could not have been a Rosa Parks,[20] as Morozov notes (Morozov 2013, 342f.).

Of course, it is not enough to counter the smarting of the infrastructure and the accompanying restriction of human possibilities for action by referring to a morally free or autonomous subject, as Morozov suggests. The smarting of infrastructure, the Internet of Things, and the digitalization of politics are rather to be seen in terms of their functions in crisis-ridden capitalism. Smarting has a lot to do with cost savings and the famous “security.” Without digitalization, given the crisis, there would be nothing but police truncheons without acceleration sensors, which would hardly improve the overall situation.[21]

The situation is similar with the envisaged “automation of politics.” The fact that political decisions are to be passed on to Big Data and corresponding computer simulations has to do primarily with the fact that the political sphere as a capitalist regulatory entity has long since reached its limits in the crisis and has lost its effective impact. As already mentioned, we must therefore speak of an “end of politics” (Robert Kurz).

Big Data also seems to be associated with the hope that the “sciences” would provide politicians with recipes that may have been overlooked thus far, and/or test these recipes for effectiveness through computer simulations (whether anything useful comes out of this, however, is another matter). This approach is also somewhat reminiscent of the ideology of transhumanists, who, in order to solve the world’s problems, are calling for the development of artificial intelligence to surpass humans and seriously replace them as a species at some point (cf. Meyer 2016).

A critique of the delegation of “social responsibility” to Big Data, as formulated by Westphalen (von Westphalen 2016), is understandable, but will lead nowhere if in the end only an old-fashioned (left-wing) Keynesianism is demanded. The Keynesianism is then expected to have a certain “ability to shape policy.” Apart from the fact that Keynesianism, too, only served to regulate and maintain the capitalist machinery, this perspective has long been obsolete and has nothing to do with meaningful social responsibility and planning. This is shown especially well by the absurd economic policy in China, which wanted to deal with the crisis in “political responsibility” by an investment policy in infrastructure which consumed more concrete in a few years than did the USA in the whole 20th century! (cf. Konicz 2015)

Ultimately, however, such a development as we can observe is only consistent for a fetishistic society that is all too blind to itself and that does not know how to justify and substantiate itself (and no longer even tries). The smart new world is, in the final analysis, nothing more than a digitalized state of emergency, a smart emergency order that wants to deal with every problem or pseudo-problem[22] with even more security, surveillance and digital technology. Digitization is little more than the reproduction of capitalist madness on a higher rung of the ladder.

6 Excursus: On the Problem of Ethics or Morality in Social Criticism

Even if the problem of morality during the smarting of infrastructure resonates with Morozov, he can nevertheless hardly be said to have a moralizing point of view, since he is quite aware of the complexity of social problems in his confrontation with “solutionism” (even if not in the sense of a radical questioning of capitalism in general).

Nevertheless, on this basis, we can also point to a fundamentally problematic mode of argumentation, namely the appeal to ethics or morality.

This appeal can be seen, for example, in the debates about “business ethics”, can be found again in all kinds of “ethics committees” (cf. von Bosse 2010) and culminates in absurd plans to program morality into an “artificial intelligence.”[23]

Ethics debates should always be treated with skepticism. In these debates, “responsibility” is transferred to the individual or an institution and ethically correct actions are suggested, while the constraints and comprehensive impositions of capitalism are completely dropped under the table. Ethics thus functions, as it were, as an “indispensable lubricant” (Scholz 2013, 30) for the preservation of commodified patriarchy and has the consequence of concealing or repressing relations of domination and their fetishistic constitution: For ethics, in the sense of propagating moral maxims of action, scandalizes the badness of certain human actions or certain technical developments or applications of the same, without, however, speaking out about the social relations on which these are based. However, this does not necessarily exclude that ethical discourses and what they intend to aim at in terms of content could show moments of correctness.

Ethics committees, however, usually assess the results of technical development and propose regulations or restrictions, provided they do not have a legitimizing, if not trivializing function from the outset. This confirms and reinforces the idea that research and development should first be regarded as neutral, that ethical concerns are only external to them and that they have no place there.

The situation is similar with debates or discourses that deal with justice or the lack of its implementation. There, too, a critique of capitalism and its real basic categories is left out, and a critique is usually limited to lamenting the lack of participation of certain social strata, neither taking note of the crisis of the labor society nor questioning in principle and content that which the disadvantaged intend to participate in.

Robert Kurz formulates the following in his critique of such a “democratic ethics”: “The call for justice derives in its very name from the concept of a functioning legal subjectivity. A ‘right’ to life, food, housing, etc., however, is absurd in itself; it only makes sense in a social frame of reference which, according to its tendency, does not take all these elementary foundations of human reproduction for granted, but, on the contrary, constantly and objectively calls them into question. The legal form and the rights of the democratic subject are only the complementary other side of the ‘wolfish’ economic subject with its interest in money, which is barred from every other human movement. To the same extent, however, as more and more people cease to be economic subjects of this system with the totalization of the commodity form and its simultaneously manifesting functional reproductive incapacity, they also cease to be legal subjects and thus to be people at all qua system definition. It is true that in the relative winner economies the appearance of legal states may still be maintained for a while; but this appearance is bound to the functioning of social redistribution networks and thus to the ‘successful’ competing down of other world market economies. Substantively, every person who can no longer constitute a market economic subject in the long run is just a dead man on leave. Conditions in loser and collapsing economies confirm this barbaric logic on a daily basis and in ever more brutal forms” (Kurz 2013, 18).

Ethical or moral debates, discourses on justice, etc., can thus be understood as helpless attempts to come to terms with barbarities that have not been conceptualized and are thus not understood precisely because such debates displace the social causes of those barbarities.

The schizoid character of ethical debates occasionally becomes very clear: On the one hand, neoliberal self-entrepreneurship is always propagated, the work on the project “I,” the permanent self-optimization in order to perhaps be able to prove oneself better in competition, and on the other hand, there is moral criticism that people are extremely self-centered, narcissistic and always completely indifferent to the other. In this society, the other person is not a fellow human being, not a friend whom one does not yet know, but just another competitor on the journey to Jerusalem. But hardly anyone dares to say this: everyone is supposed to always be “nice” to each other.

However, a “pre-theoretical apriori” (Robert Kurz) precedes the theoretical understanding and radical questioning of capitalism.[24] This apriori consists of a disagreement with the conditions, with the suffering and the comprehensive impositions that capitalism brings with it. However, the development of a radical critique does not necessarily follow from this disagreement. It is to be criticized, for example, if this disagreement itself takes the form of an ethical or moral claim. If, however, an ethical claim were to be formulated, then in my opinion the sting of critique, while not necessarily completely withdrawn, would be quite blunted; an ethical claim would capriciously focus on the individual and his or her actions (or on institutions and their members), thus considerably narrowing the horizon of critique; ultimately, one would arrive at, among other things, “ethically correct nutrition,” “politically correct language,” local communes and contexts, “lifestyle anarchism,”[25] etc., in which supposed alternatives are allegedly “lived free of domination.”

To sharpen the thought: Even to ethically underpin a disagreement with Auschwitz is nothing other than a perversion. It is true that a certain practice follows from Auschwitz, as Adorno explained, i.e. to arrange thinking and acting in such a way that Auschwitz or something similar does not repeat itself, but this is not an ethical claim (Adorno 2014, 358). Ethical claims are typically addressed to people as individuals, presupposing the social forms of intercourse and relations by which they are compelled to move within according to their form; the failure to come to terms with these, however, demands their radical critique and practical overcoming. Adorno’s “categorical imperative” should be understood in this way.

As Marx already formulated, all relations in which man is a subjugated and humiliated being are to be overturned. For in radical critique, it is not the individual or an institution that is the main concern, ignoring all social relations, but rather the current actions of people, i.e. their practice, is seen in the context of a destructive social objectivity, which is (re)produced precisely by this practice, and it is the claim of this critique that precisely this objectivity, i.e. the fetishistic dynamics of capitalism together with the subject form on which it is based, must be abolished. Only then could the idea of a “peaceful coexistence” of man and nature be realized.

7. Big Data and the “End of Theory”

With “Big Data,” some have already proclaimed the “end of theory,” and thus the highest and last stage of positivism has presumably dawned: Due to the incredible amounts of data made possible by Big Data and the smart new world, correlations will be sufficient; in the future, the numbers could speak for themselves; theory and model building could thus be disposed of. This is the viewpoint of Chris Anderson, the former editor-in-chief of Wired magazine (cf. Anderson 2013). Of course, there was opposition from the scientific establishment: As in physics, it makes no sense to just “go ahead and measure”; there must already be some theoretical thinking that determines what should be measured and with what goal (cf. e.g. Mazzocchi 2015, Boyd; Crawford 2012). In addition, Gerhard Lauer (a representative of the “Digital Humanities”) also argues that the more data are available, the more theory is needed (Lauer 2013).

As commendable as such objections against the alleged end of theory may be, generally speaking, methodological individualism, modern objectivity, alleged neutrality and freedom from ideology remain unquestioned. To be sure, there are niches, individuals, and small groups that do this to some extent, but it certainly does not happen in large-scale scientific projects. For example, billions are invested in neuroscience to research mental disorders that are supposedly only caused by the brain of the individual and have nothing to do with structural conditions in society (Schleim 2016). It would therefore not be surprising if, in the course of the digitalization of thinking, the science enterprise or the entrepreneurial university (and, of course, all private companies that research and develop) were to fall prey to a bottomless ignorance and thus say goodbye once and for all to any critical reflection, or even the mere possibility of it. However, critical reflection has never been hegemonic in the scientific landscape anyway.

Critical objections, which do exist against Big Data and its applications (see the Digital Manifesto), are consequently easily concealed when the prospect of how many oh-so-great new jobs will become possible as a result is held out (e.g., Helbing; Pournaras 2015). Critical reflection and a fundamental questioning of social relations are unfortunately not self-evident and do not automatically result from methodologically clean applied mathematics or from formal, logically flawless manipulations of strings. That theoretical (immanent) reflection is disappearing at all suggests the suspicion, as Robert Kurz once wrote, “that theoretical reflection falls silent because the social dynamics underlying it disappear” (Kurz 2002b).[26] This would make it understandable why the various prophets of science and technology evangelism have abandoned the possibility of a discourse on the meaning and content of technology and think that everything can be dealt with by technology and a quantitative way of thinking alone.

The proclamation of the end of theory is fatally reminiscent of the end of history proclaimed by Francis Fukuyama. After postmodernism, late bourgeois society seems to have entered a new stage of organized stultification with Big Data. However, in my opinion, this is not surprising: For in postmodernism, the possibility of critical reflection had already evaporated to such an extent that it was largely limited to the linguistic level, and “grand theories” were refused because of alleged totalitarianism. Postmodern arbitrary thinking, the switch to culturalist modes of argumentation, the hypostasizing of differences, etc. were little more than the expression of intellectual capitulation to the misunderstood social conditions.

The basic problem with the forced digitalization of science, the presumed “end of theory,” is therefore not so much a naïve belief in mathematics, technology and the abundance of data that can supposedly solve all problems, but rather the fact that critical reflection is in bad shape anyway due to the crisis-ridden conditions. Even in places where socially critical Marxist theory has become fashionable again, because of the precarious conditions that have long since prevailed, the university refrains from a radical questioning of social conditions in accordance with the flowery saying “publish or perish,” so as not to ruin a possible academic career. In this way, a science that has become thoroughly economized and devoid of reflection is also well qualified for digital foolishness: It is important, however, not to confuse cause and effect here, but rather, to emphasize it once again, to criticize Big Data, the smart new world, not only on a level intrinsic to science, but also, as was the case here, in relation to society as a whole. The critique would then point beyond the scientific community and its limitations.


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[1] Cf. Robert Kurz’s discussion of the anti-Germans: Kurz 2003.

[2] A reflective approach to mathematics would involve acknowledging its limitations and engaging with it epistemologically and in the history of philosophy, but usually these approaches are marginalized in contemporary scholarship, see, for example, Rießinger 2010; in detail, Bedürftig; Murawski 2015, and Heintz 2000.

[3] In Hamiltonian mechanics, named after William Rowan Hamilton (1805-1865), a mechanical system is defined by the Hamiltonian function, which in a sense represents the total energy of the system, expressed in generalized position and generalized momentum, cf. Penrose 2007, 471f.

[4] Named after the economist Alfred Marshall (1842-1924).

[5] This point could be elaborated further. For reasons of space and because it would become a separate text, it cannot be done here. To justify the elimination of the subjective factor, personal prejudice is usually brought up, but in fact it goes far beyond that: among other things, the externalization of ethical concerns; a (Cartesian) subject-object split, the dissociation of the “feminine” (feelings, body), and so on. Cf. Ortlieb 1998, as well as, for example: List 2008, Braun; Kremer 1987 and Pernkopf 2006.

[6] Cf. on Hegel: Späth 2013 and 2014.

[7] The Nietzsche quote is also used by Evgeny Morozov in his book “Smart New World”, which will be discussed in more detail later.

[8] There are other objectives that arise from the imperative of capital valorization but cannot simply be subsumed under the aspect of saving abstract labor, cf. Becker 2017.

[9] It may be that, due to reforms, the conditions in psychiatric wards are no longer as they were depicted in the film “One Flew Over the Cuckoo’s Nest” (1975). Nevertheless, psychiatry is still an instrument of repression today: for example, when psychiatric reports are drawn up against Hartz IV recipients who are not “employable,” see Allex 2015.

[10] It should be mentioned and criticized that O’Neil is (was) an activist of Occupy Wall Street. Nevertheless, I take note of her critical remarks on Big Data here.    

[11] See also the radio interview:

[12] Of course, the criticism is not about demanding that people should have free access to the programming code itself, which non-experts cannot comprehend anyway. However, O’Neil’s point is to criticize the fact that it is usually not clear according to which criteria and standards an algorithm sorts and judges in the first place.


[14] On the criticism of Google, see Edel 2016.

[15] Cf. Konicz 2016, esp. 51-80: “The Collapse of the Periphery,” and data in footnote 21.

[16] On narcissistic social character, see Wissen 2017.

[17] For more on self-tracking, life-logging, and the quantified self movement, see, for example: Selke 2014, Lupton 2016, and Schaupp 2016, all of which remain on a more empirical level, but Schaupp also analyzes the gendered connotations of self-tracking.

[18] Cf. various texts at: Cf. also the “12 Theses for the Responsible Consumer,”

[19] To prevent misunderstandings, it should be emphasized here explicitly once again: Morozov is not concerned here with illegal acts which aim at bringing about social change! It is about the fact that a smart or automated infrastructure restricts the human possibilities of action to the effect that certain “everyday sins” become impossible; or violations of the “racial order” or the like. Such violations could enable a discourse on whether certain laws could not be meaningfully changed after all. For example, poverty-related fare evasion could lead to tax subsidies for public transport or the like, or illegal alcohol or cannabis consumption led or could lead to a change in a prohibition policy.

That does not mean, however, that this is to be understood as a call to criminal behavior, although it was or would be quite reasonable to question or abolish the criminal nature of certain acts; as was (or is, depending on where) the case with homosexuality, for example; until 1994, as is well known, §175 StGB applied in this country.

Critical objections to the existing (criminal) law should, however, be linked with a fundamental critique of this society, especially if the aim is to counter a “populist criminology” (Cremer-Schäfer; Steinert 2014) on the one hand and, at the same time, the social conditions and the social identities ofcriminals on the other, with criticism. Criminal behavior (such as property crimes, fare evasion) are anything but “subversive,” but rather are nothing more than the continuation of competition by other means.

[20] Rosa Parks (1913-2005) was arrested on 12.1.1955, because she did not want to leave her seat, which was reserved for white people, in a bus. If the bus had been “smart” at that time, she might not have been able to sit down in a “white seat,” because such a thing would be technically impossible, e.g. by the seat recognizing the skin color of the person who intends to sit down with appropriate sensors. Direct violations of the “racial order” (and the infrastructure that was designed around it) were an important practical component of the civil rights movement.

[21] A tendency toward a state of emergency has already been established through the designation of a “danger area,” cf., cf. also Montseny 2016. As is well known, something like this also works without smart technology. Smart technology in the police sector should be seen as a technical rationalization measure to support, speed up and cheapen “law and order.” Without these techniques, however, the police state and the state of emergency would not disappear, because the “security problem” is an expression of the crisis of capital. This can be seen in the formation of gangs and rackets in problem neighborhoods of the socially superfluous, all the way to the “failed state,” etc., cf. Pohrt 1997, as well as Bedszent 2014.

[22] Morozov also gives examples of pseudo-problems, i.e. problems that exist only in the minds of the “solutionists.” For example, self-tracking, Big Data, etc. make it possible in principle to record almost every detail of a life. In this way, suddenly the possibility of forgetting at all (!) is seen as a problem that should be abolished! Here the authoritarian claim of a totalitarian and androcentric will of availability over everything becomes clear. It is therefore also no coincidence that the agitators of the “life-logging movement,” like Garry Wolf, Steve Mann or Gordon Bell, are men.

[23] Reification cannot be clearer than when human qualities are attributed to a machine. However, this also has to do with the fact that the scientific view of humans is in any case extremely reductionist, see Bächle 2014.

[24] Cf. the lecture by Robert Kurz and the discussion “The History of the Critique of Value – On the Historical Conditional Context of Theory Formation” (2010).

[25] However, this was sharply criticized by the wiser of the anarchists: Thus, by Murray Bookchin (1921-2006) in: Bookchin 1995. Bookchin also criticized, among other things, the hostility to theory of large parts of the anarchist scene, the kitschification of supposedly pristine and domination-free “primitive peoples,” and an ahistorical “critique of technology,” such as John Zerzan’s, which rejects technology as such andseriously wants to go back to the Neolithic Revolution (!).

[26] The fact that critical (immanent) reflection is disappearing, however, does not mean that the same is happening to ideology production: on the contrary, it can be observed that the scientific establishment itself is becoming increasingly ideologically neglected or wild. This assertion can be seen, for example, in the case of such people as Franz Hörmann, an economist who is now the financial policy spokesman for the “Deutsche Mitte” party (as of summer 2017). A party, by the way, with ethical claims (!).

Originally published in Exit! no. 15 on 04/01/2018

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