It is precisely this ambivalence that dooms to failure any kind of *socioscope* or policy wind tunnel. It is here that the frictions arise, causing the Large Knowledge Collider to implode. For, in contrast to that meme-rich concern about the creation of a black hole by CERN (Rössler 2008), the black hole of this social supercollider seems to only yawn in its conceptual center.

## **Frictions in the Black Hole**

The effort to present *FutureICT* as an integrative, distributive, and participatory architecture is evidently an effort to refute any accusations of technocracy from the outset. Despite bold slogans, those involved in the project can by no means be accused of conceptual under-reflection. Due to the transdisciplinary disposition of the project, a multitude of critical objections against the proposed practices of data mining had already been extensively formulated in the white papers and in comment sections of special journal issues that prepared the field for *FuturICT* (Allen 2011; Thurner 2011). It seems that a media and cultural studies critique was internally implemented, seeking to anticipate any reservation. Beyond the display of self-criticism, it would therefore be more appropriate to ask what value these statements actually had for the *FutureICT* project. After all, the white papers cited here not only offer an extensive collection of material on social simulations, but also clever rhetoric around

funding applications. Accordingly, the impression arises that the **79** implementation of self-criticism leads to a number of loose ends.

First, the application does not emphasize the narrow scope for this type of project in view of the existing but inadequate instruments of "socio-economic management." Neither is there an open reference to the critique of progress. Conversely, existing problems, like the "mining" and processing of relevant data, are simply transferred to the development of the project as promises of future solutions. However, the constant allusion to the new possibilities of digitally networked societies refers only to one of the sides pointed out by Chun—i.e., the emancipatory potential of decentralized networks. This is especially relevant since *FuturICT*  also intended to gain control over the protocols that were supposed to make these media democratic (Galloway 2004). We should keep in mind, nonetheless, that *FuturICT* was formulated before acronyms like PRISM1 or GCHQ2 became part of the public discussion, and before the idea emerged that communication networks might not automatically generate connecting capacities, but also socially disintegrating ones. Put differently, a *Planetary Nervous System* can suffer from strong nervous convulsions, as the last decade of regression has shown (Pörksen 2018; Reckwitz 2019; Appadurai et al. 2017).

Second, although Helbing and others in the team expose the inadequacies of classical economic models, they do this only by focusing themselves on the limitations of the *homo economicus* model, which they contrast with the figure of a *homo socialis*—the latter acting cooperatively rather than selfishly. Similar to Robert Axelrod's (1984) studies on the evolution of cooperation, this approach is based on simulation programs with physics-based parameterizations. In the context of his original

**80** field of expertise—evacuation and panic research—Helbing had investigated the behavior of crowds in the context of catastrophes. Then, he described the "freezing-by-heating effect" (Helbing, Farkas, and Vicsek 2000) and the "slower-is-faster paradox" (Helbing and Mazloumian 2009)—both phenomena in which faster individual movements in crowds lead to macroscopic stalling effects, while cooperative behavior produces much better results. Here, however, the *homo socialis* is problematized through *frictions* between individuals which are primarily thought of in terms of physical frictions, without having semantic levels in mind.

Thirdly, this connects to a systemic incoherence concerning the decision-making process. On one hand, models based mainly on rational actors, such as *homo economicus*, were taken as an opportunity to alternatively design more complex, *data-based*, and heterogeneous models. However, in dealing with the data generated by *FuturICT*, the next step would be precisely to appeal to such rationalistically understood *decision-makers*, who would be able to implement *better, more intelligent,* or *more adequate*  decisions. The fact that this translation of expert knowledge into political action could become problematic is deliberately concealed in the white papers.

Fourth, defying the break with cybernetic approaches described above, a universalist ideal pervades the distributive network plans of *FuturICT*. Perhaps the greatest fallacy of both earlier cybernetic designs and complexity science, these social supercolliders—announcing an overarching conceptual setting of cybernetic feedback systems, social physics, and capture-all data—claim ubiquitous validity for all aspects and domains. At *FuturICT*, the get-the-right-data problem of previous decades morphed into the familiar Big Data mantra "*get the data right*." Thus, the conviction remains that an overarching communication and control system can and should be implemented. Therefore, regardless of all rhetorical anticipation of technocratic accusations, old qualms also endure: as with *Cybersyn*,

universalist systems run the permanent risk of becoming exactly **81** the opposite of what they were intended to be.

Fifth, this may be connected to the lack of reflection on the relationship between science and politics. The structural incompatibility of such a bond was summed up by none other than Hannah Arendt in her essay "*Truth and Politics"* (1967). Accordingly, the insistence on computationally expanding the horizons for decision-making and data-driven knowledge processes falls short when data become facts. After all, a common characteristic of political action is not to do what would be rationally opportune in the long or medium term. Reformulated in a rather Luhmannian (1994) manner: because of their functional difference, science, society, and politics will each treat *data* very differently, so that in each area quite different *facts* will be derived from the same data. This, however, is only recognized by those who do not equate *data* with *facts* (Rosenberg 2013), and decision preparations—i.e., science—with actual decisions—i.e., politics (Luhmann 2000). The experience from recent years—e.g., in the area of pandemic simulation—has shown that data-based decision-making, while offering immense advantages, often blurs the lines of conflict in decision-making processes: what amount of the epidemiologically-quantified index for distancing measures do I sacrifice in relation to the economically-quantified index for maintaining production processes? It does make a difference to how complex social systems are understood and modeled, as well as how this knowledge is communicated to the society, and thus effectively implemented (Priesemann et al. 2021). If one includes the unpredictability of daily global politics in this picture, it may become apparent that beneath this "Large Knowledge Collider" the aforementioned black hole lurks—under whose gravity all possible futures are stretched beyond recognition.

A sixth objection refers to the Agent-Based Simulation paradigm. What works very well for traffic or pedestrian systems, reaches its limits in the context of more complex social systems. As David O'Sullivan and Mordechai Haklay (2000) pointed out, the

**82** individual-based approach of these models only considers partial aspects—a bias that neglects the role of institutions and other social organizations as part of a mid-level between individuals and global structures. Hence, these models show an inadequacy similar to that pointed out by Herbert Simon regarding marketradical positions. Only having transactions in mind, they would not have planned structures thoroughly, leaving firms and other organizations adrift (Simon 1983). This could be extended to the vision of distributed, grassroots co-decision-making in peace rooms. Certainly, *FuturICT* was a contemporary of the German Pirate Party and initiatives such as Liquid Democracy (Ramos 2015). Political opinion, however, or even culture, are not just functions of interactions based on a few rules. Long-running discussions suggest how complex the topic of participation is in the context of digital technologies (Denecke et al. 2016; Center for Digital Participation n.d.)—and that it will not be enough to adopt a technology-driven approach, like the so-called *peace rooms*.

Seventh, computer simulations raise a fundamental epistemological problem, which, according to Wendy Chun, refers to programs and trust:

That is, "trusting" a program does not mean letting it decide the future or even framing its future predictions as simply true, but instead acknowledging the impossibility of knowing its truth in advance while nonetheless responding to it. This is perhaps made most clear through the example of global climate models, which attempt to convince people that something they can't yet experience, something simulated, is true. (Chun 2011, 106–07)

This resonates with *FuturICT* and the irresolvable circular argument that social systems react differently than climate to the predictions of their behavior, thus making them immediately invalid again. In the words of economist Alex Tabarrok: "The problem of perfectly organizing an economy does not become easier with greater computing power precisely because greater

computing power also makes the economy more complex" **83** (Tabarrok 2018). It could be argued that the most striking pitfall of *FuturICT* lies in its focus on providing solutions for complex societal problems and developing the necessary infrastructures at once. Put differently, despite its legacy of complexity studies, there still seems to be a residual *systems dynamics* mindset there.

Helbing's grim complaint after the Flagship's decision against *FuturICT* may put this in perspective:

While the project was doing impressively well, to everyone's surprise it was finally not funded, even though we proposed an approach aiming at ethical information and communication technologies, with a focus on privacy and citizen participation. This possibly meant that governments had decided against *FuturICT*'s open, transparent, participatory, and privacy-respecting approach, and that they might invest in secret projects instead. (Helbing 2015, 3)

Indeed, the Snowden revelations may have somehow reinforced this claim. However, the critical aspects discussed above offer more realistic reasons for the project failing to receive funding.

#### **Beware the Borg**

In late 2019, *The Economist* devoted an extensive article to possible futures and the viability of various models of data capitalism. Under the original title "*Beware the Borg*," it thoroughly reflected on the historical genealogies of the current developments, taking operations rooms, and *Project Cybersyn* in particular, as the starting point for a wide-ranging discussion on the antagonisms between market-based and planned economics since the 1920s—discussions that would have led to new hybrid forms such as AI-thoritarianism and infrastructures saturated by machine learning (The Economist 2019). As a discarded project that did not emphasize AI aspects, *FuturICT* did not play a role in the article. Nevertheless, almost a decade after the start of

**84** this project, the article once again framed questions from that time within a bigger picture. China's social credit systems are discussed alongside social media infowars, and the erosion of democratic societies in a Western surveillance-based economy (The Economist 2019). Similarly to Zuboff (2019), in these cases "information-machine-like" cultures of control, predictability, and automation of processes propagate from the private sphere to the societal level. The focus is thus on the "dark side of the digital," and the question about viable alternative models is raised. Consequently, the central point of the article is turning away from the "thoughtlessness" of media-technical automation and algorithmization, towards a "thoughtfulness" in multi-stage decision-making processes:

> If planners—or regulators, for that matter—want to intervene in something, it is with the platform that they are best advised to start. It is the place where code becomes law, where the mechanisms by which a market works are specified …

… This way of thinking of things allows a new insight into the calculation debate. In treating both the planning system and the market as what might now be called computer programs it made them comparable. Take the next step of seeing the type of program … as a platform, though, and they become very different …

Platforms are already a source of huge and increasing power, commercial and otherwise. Politics needs to catch up with this, not just in terms of regulating commerce—where the issue is already a hot one—but also by opening up discussion of the values that platforms embody and encourage. (The Economist 2019)

However, the merging of different participatory platforms is precisely what must be avoided. Instead, a platform world that is as pluralistic as possible should be embraced:

Some basic platforms, such as digital identity and digital **85** currency, perhaps, should probably be owned by governments, or at the very least open to policing by them. Other platforms need to allow oversight by their users and civil society to ensure an absence of bias … and privacy infringements. (The Economist 2019)

Such proposals do not seem far removed from the approach formulated by *FuturICT*. In their emphasis on variety however, these proposals do not claim to bring together all disparities for the purpose of a more efficient planning, or for the development of concrete technologies. Moreover, they are not the brainchild of an academic funding structure whose authority for redefining political conditions must always be contestable. Conversely, approaches like Francesca Bria's "Big Democracy" resonate here (Monge et al. 2022; Morozov and Bria 2018). Alongside fellow campaigners such as urban planner Carlos Moreno, Bria—a former digital expert for the city of Barcelona—takes traditional ideas of smart cities as a starting point to redefine livable cities in the age of ubiquitous digital technologies (Monge et al. 2022; Moreno 2020). With attention to concrete places and human experiences, broader notions for digital futures are sketched out; where Big Democracy becomes the European answer to Big Tech from the US, and China's Big State. In contrast to *FuturICT* however, here politics does not degenerate into a mere function of digital infrastructures, but is rather a prerequisite for them. To return to Wendy Chun:

What can emerge positively from the linking of crisis to networks—what must emerge from it if we are not to exhaust ourselves and our resources—are constant ethical encounters between self and other. These moments can call forth a new future, a way to exhaust exhaustion, even as they complicate the deconstructive promise of responsibility (Chun 2011, 107).

**86** This "*new future"* may well emerge from multiple initiatives, rather than from a unifying academic research proposal; it might be rooted in concrete locations like cities, with connections to tangible living environments, rather than being the product of abstract network approaches. After all, the larger part of social super-collisions still happens on the streets.

#### **References**

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Destroy Democracy?" *The Economist*, December 18, 2019.

https://www.economist.com/christmas-specials/2019/12/18/

can-technology-plan-economies-and-destroy-democracy.

Epstein, Joshua M. 2006. *Generative Social Science: Studies in Agent-Based Computational Modeling*. Princeton: Princeton University Press.

Forrester, Jay Wright. 1961. *Industrial Dynamics.* Cambridge: MIT Press.

———. 1969. *Urban Dynamics*. Cambridge: MIT Press.

Hacking, Ian. 1990. *The Taming of Chance*. Cambridge: Cambridge University Press.

	- Krajewski, Markus, ed. 2004. *Projektemacher: Zur Produktion von Wissen in der Vorform des Scheiterns*. Berlin: Kadmos.
	- Lovelock, James E., and Lynn Margulis. 1974. "Atmospheric Homeostasis by and for the Biosphere: The Gaia Hypothesis." *Tellus* 26 (1-2): 2–10. https://doi.org/10.3402/ tellusa.v26i1-2.9731.

Luhmann, Niklas. 1994. *Soziale Systeme: Grundriß einer allgemeinen Theorie*. Frankfurt: Suhrkamp.

———. 2000. "Die Paradoxie des Entscheidens." In *Organisation und Entscheidung*, 123–51. Wiesbaden: VS Verlag für Sozialwissenschaften.

Mahr, Bernd. 2003. "Modellieren: Beobachtungen und Gedanken zur Geschichte des Modellbegriffs." In *Bild—Schrift—Zahl*, edited by Horst Bredekamp and Sybille Krämer, 59–85. München: Fink.

McLoughlin, J. Brian, and Judith N. Webster. 1970. "Cybernetic and General-System Approaches to Urban and Regional Research: A Review of the Literature." *Environment and Planning* 2 (4): 369–408. https://doi.org/10.1068/a020369.

Meadows, Donella H., Dennis L. Meadows, Jørgen Randers, and William W. Behrens III, eds. 1972. *The Limits to Growth: A Report for the Club of Rome's Project on the Predicament of Mankind*. New York: Universe Books.

Medina, Eden. 2011. *Cybernetic Revolutionaries: Technology and Politics in Allende's Chile*. Cambridge: MIT Press.

Meyers, Robert A., ed. 2009. *Encyclopedia of Complexity and Systems Science*. New York: Springer.

Monchaux, Nicolas de. 2016. *Local Code: 3659 Proposals About Data, Design and the Nature of Cities*. New York: Princeton Architectural Press.

Monge, Fernando, Sarah Barns, Rainer Kattel, and Francesca Bria. 2022. "A New Data Deal: The Case of Barcelona." *UCL Institute for Innovation and Public Purpose, Working Paper Series* 2022 (2): 1–26. https://www.ucl.ac.uk/bartlett/ public-purpose/wp2022-02.

Moreno, Carlos. n.d. "Beyond the Smart City." *PCA Stream*. Accessed December 12, 2022. https://www.pca-stream.com/en/articles/ carlos-moreno-beyond-the-smart-city-114.

Morgan, Gareth. 2010. "Earth Project Aims to 'Simulate Everything'." *BBC News*, December 28, 2010. http://www.bbc.co.uk/news/technology-12012082.

O'Sullivan, David, and Mordechai Haklay. 2000. "Agent-Based Models and Individualism: Is the World Agent-Based?" *Environmental Planning A: Economy and Space* 32 (8): 1409–25. https://doi.org/10.1068/a32140.

# **CYBERNETICS**

# **TELEPRINTER**

 **DATA**

 **NETWORKS**

 **CHILE**

# **[4] Encoding from/to the Real: On Cybersyn's Symbolic Politics of Transmission**

**Diego Gómez-Venegas**

**This chapter traces the techno-epistemological relevance of Project Cybersyn's processes of production quantification at factories, the transmission of that data, and the road towards their computation. By unfolding a mediaarchaeological analysis, these pages discuss archival documents showing that from the depths of Project Cybersyn's technologies of transmission and computation, new correlations of forces and strategies of organization emerge. In sum, this text provides concrete evidence on how a media archaeology of Project Cybersyn unravels the media-genealogical scope of this case.**

A media-archaeological analysis of Project Cybersyn—the telecommunications and processing system developed by Stafford Beer and his team in the early 1970s to manage Chile's economy can be deployed, these pages argue, under three interconnected commands; namely, "*Encode, Forget*, and *Govern."* This chapter, however, is devoted to the first command only; that is, "*Encode*." Accordingly, a study of the project's modeling of industrial production, of its telecommunications infrastructure, as well as of the configuration and transmission of data, will be developed. The aim of this study is to identify and discuss the *frictions* that may have arisen between the attempts to implement these modeling techniques and the cybernetic thinking supporting them, and on the other hand, *the real* operations at the factories and in the network that they were connected to.

Hence, this chapter will first cover Project Cybersyn's early stages of encoding, in which a group of Chilean engineers visited and modeled the production operations of the factories the project sought to connect. Secondly, the telecommunications infrastructure used for the process of networking will be discussed—here, special attention will be paid to the protocols of encoding, and their potential relation to Chile's early history of telecommunications. Third, a media-theoretical analysis on the previous two aspects will be developed. In the wake of Foucault's archaeological approach, a techno-historical and techno-epistemological problematization will be attempted. Using the notion of "*exchanging"* as a probe, this analysis will traverse the project's operational modeling techniques, its technological infrastructure, and protocols, to finally propose a conceptual device called *tele[economy]cations*.

## **<sup>93</sup> Prolegomenon**

The events discussed in this chapter begin with two pieces of machine-typed paper written in English (fig. 1 and 2). On July 13, 1971, a 28-year-old engineer named Fernando Flores—who Salvador Allende's government had recently appointed as the technical general manager of Chile's Agency of Development (CORFO), as well as the board president of the country's Institute of Technological Research (INTEC)—sent a letter to the cybernetician Stafford Beer. In this letter, Flores not only introduced the British scientist-consultant to the socialist changes happening in Chile's industrial and financial sectors, but also acknowledged the role that his book *Decision and Control* and the operational research methods Beer had developed at the consultancy company SIGMA had played in his own career. More substantially, Flores emphasized the relevance of implementing "scientific views on management and organization" in Chile's socialist process, and how "cybernetic thinking [had become] a necessity" (Flores 1971) for such an implementation. Finally, the Chilean engineer closed his letter asking Beer for advice, as well as for his more recent writings on the topic, and he expressed his hope that Beer could one day visit Chile.

The exchange continued, following quite similar protocols. On July 29, Stafford Beer sent a machine-typed letter in response to Flores, in which—reinforcing the British spelling of Flores's missive, whereby the CORFO engineers Raul Espejo and Juan Bulnes had, in effect, contributed to the writing process in order to secure the proper use of that syntax (Raul Espejo, in discussion with the author, January 29, 2019)—Beer referred to his two upcoming books, *Brain of the Firm* and *Platform for Change*, explaining how they would connect to the problems Chile was facing (Beer 1971a). Asking if Chile's Embassy in London could operate as a proper channel, he added that he would attempt to send Flores a final copy of the former book, and a manuscript of the latter. That is to say, Beer replied with a confirmation

**94**

[Fig. 1] Letter from Fernando Flores to Stafford Beer, July 13, 1971. Page 1. (Source: Flores 1971, 1). Courtesy of the Stafford Beer Archive, Liverpool John Moores University, Special Collections & Archives.

message to Flores's request, corroborating the availability of the information sought, while including a request to secure an adequate sending channel. More important, however, was Beer's rhetorical query at the end of the letter. He wondered how he "could [actually] play a part" in this enterprise, since he had "the most extraordinary feelings about this situation" (Beer 1971a).

Beer traveled to Santiago de Chile on November 1, 1971, put together a team, and thus began Project Cybersyn. The plan entailed connecting all the state-owned industrial companies – many of which had been nationalized through methods some considered controversial (Beer [1981] 1994, 246–47)—to collect

[Fig. 2] Letter from Fernando Flores to Stafford Beer, July 13, 1971. Page 2. (Source: Flores 1971, 2). Courtesy of the Stafford Beer Archive, Liverpool John Moores University, Special Collections & Archives.

daily production data. That data would then be computed in order to obtain its current and potential fluctuations, with the aim to improve the management of the industrial economy both at a local and national scale. This led to the structuring of a plan comprised of four sub-projects: a) a network of telecommunications which would transmit the data, transforming the factories into nodes—this network would later be called *Cybernet*; b) a central computational unit which would receive and analyze the data to forecast behaviors through statistical models – this unit and the software suite it ran would be named *Cyberstride*; c) an additional computational simulation model of the economy which would allow the government to test future scenarios—called *CHECO*, the

**96** acronym for Chilean Economy; and finally d) an operations and decisions room, where the processed data would be presented as graphs and diagrams in displays controlled by small keyboard interfaces located at the armrests of seven chairs—the so-called *Opsroom*.

Although Project Cybersyn has largely become known for its *Opsroom*—or, more precisely, because of the appealing images of this room that have circulated throughout the Internet for 15 years or so—this chapter proposes a rather different approach. The reason for that, it is argued here, is that an endeavor aiming to trace the techno-epistemological and cybernetic scope of a project like Cybersyn must first study its *operational core*, and, as it were, only then go up. In other words, an undertaking that emerges from the technologies that made the project's media processes possible; an inquiry that starting with the hardware and software that transmitted, computed, and stored the information the project used, can prompt us to ask about the position, role, and exchanges that humans and machines held in this context. That is, an investigation on the "set of strategies of the relations of forces supporting, and supported by, certain types of knowledge" (Foucault 1980, 196). These pages contend that therein lie the questions that will reveal the true archaeological fibers of Project Cybersyn, and, to anticipate already, its genealogical threads too.

Therefore, this chapter is focused on *Cybernet*—the telecommunications network—and *Cyberstride*—the computational processing unit. Or, paraphrasing Stafford Beer, on the nerves and the brain of a way of governing (Beer 1974, 43). More particularly, the aim here is to tackle the discursive and technological exchanges that configured *Cybernet*—the nerves by emphasizing the role played by this sub-project's technique of encoding; which will help us trace "the strategies of relations" (Foucault 1980, 196) that in turn set the groundwork for the emergence of a *symbolic* politics of transmission within the overall project.

## **<sup>97</sup> Protocols**

*Cybernet*'s earliest phase required quantitative modeling of the internal operations of the project's factories. This was essential in order to achieve Cybersyn's general goal; that is, "to install a preliminary system of information for the industrial economy that will demonstrate the main features of cybernetic management and begin to help in the task of actual decision making by 1st March 1972" (Beer [1981] 1994, 251–52). Already in his first visit to Santiago, Beer outlined an information system that would be based on data flows, for which the operations at the factories had to be encoded into quantifiable means. For such a task, Beer requested the formation of a team that should include what he then called an "OR Man," and whose professional profile should fit the following description: "Not USA archetype. 'Decision and Control' supporter! Versed in philosophy of science. Biological background ideal" (Beer 1971b, 6). Although these prerequisites were not matched entirely; they were indeed matched in general—a topic for which a small digression is necessary.

The teaching and practice of operational research (OR) was already well established in Chile by the early 1970s. In fact, the first courses in this field began to be taught at schools of engineering around 1957. One of the pioneers of this discipline was Raul Espinosa Wellmann, an engineer and professor at the Catholic University of Chile. After a random discovery at a local bookstore, followed by a more targeted book selection while visiting the USA during the 1950s, Espinosa Wellmann taught himself this discipline, and then introduced the first courses on operational research for students of the Department of Industrial Engineering at the aforementioned university—not much later renamed the Department of Industrial and *Systems* Engineering (Espinosa Wellmann, in discussion with the author, December 2, 2019). Espinosa Wellmann is mentioned by Stafford Beer in one of his early reports from January 1972, where, while discussing the necessity of having a "Chilean Systems Centre" that could act as a

**98** supporting institution for the development of Project Cybersyn, and suggesting that this could be achieved by founding a local chapter of the Society of General Systems Research, Beer points out that "to [his] astonishment," he had discovered that such a group already existed, and that it had a regular "programme of meetings in Santiago," which counted Espinosa Wellmann among its members (Beer 1972, 15).

The introduction and development of OR had already influenced Cybersyn's local team, particularly the engineers at CORFO. Many of them had studied at the School of Engineering of the Catholic University of Chile during the 1960s and had been trained in operational research by Espinosa Wellmann and others. Such is the case of Fernando Flores, who, as a young engineer in the OR team at the State Railways Company—years before Cybersyn—worked with the British consultants sent to Chile by Beer's company SIGMA (Flores 1971). Coincidentally, also while traveling in the USA, Flores made a random discovery by which he purchased Beer's book *Decision and Control*, which he later introduced to his peers in Chile (Raul Espejo, in discussion with the author, January 29, 2019). Put differently, these events are connected by a series of information exchanges where university teaching, engineering practices at technical enterprises, as well as random findings at bookstores—as to recall Friedrich Kittler's theories (1981; [1985] 1990; [1986] 1999)—play a significant role.

Coming back to *Cybernet*'s modeling at the factories—which the Cybersyn team used to call "indexes lifting" (Raul Espejo, in discussion with the author, May 19, 2019), somehow suggesting that they would be literally picked up from "*the real"*—it seems important to note how the techniques used for such a process emerged, were implemented, and then were deployed in the context of the project. An initial trace of this can be found in the notes Beer made during his first visit to Santiago. There, in a set of 10 loose pages taken from a sketchbook, one can find a series of quickly-drawn diagrams with comments. In one of them it is possible to read "quantified flowcharts," right next to a drawing

with the caption "identify the size of chambers flow … identify **99** bottlenecks" (Beer 1971c). This technique of *quantified flowcharting* was central to the project's initial stages; first, in regard to the methodological cohesion among the modeling engineers, and second, in the actual fieldwork at the factories. A later document, a thorough report developed by one of the team's engineers, allows us to assess the extent of such a technique.

Officially published by CORFO, signed by Humberto Gabella, and shared with the team in March 1973, the 102-page booklet titled *A Quantified Flowcharting Technique for Real-Time Control* constituted a detailed methodological tool for modeling production activity at the factories. Accordingly, the report stated that its goal was to support the implementation of "management techniques that have been developed … to be transformed into effective governing tools at the service of all levels of decision within the industrial apparatus" (Gabella 1973, 1).1 After an introduction to general flowcharting—which defined key concepts, explained its arithmetic, and gave examples of companies already modeled by the team—it followed an account of the scope of the notion of quantification in the context of this technique. By acknowledging that flowcharting consisted of detecting the flows that connect the "elements" that dynamically form "any productive system," and considering that "for the implementation of this technique [such elements] must be considered 'black-boxes'" (Gabella 1973, 2), the use of quantification entailed, first, to detect the variables conditioning the flows, to then measure the ratio between their *real* level at a given time, and their *actual* capacity. Such a ratio was then graphically expressed in a diagram in order to effectively communicate the intensity of that index.

Three questions must be considered at this point. First, by understanding all productive "elements" of a system as black boxes, the technique embraced two key notions from Beer's management cybernetics: *recursion* and *variety* (fig. 3). The former notion

1 Document retrieved from Raul Espejo's personal archive.

**100** implies that the elements of a system are closed sub-systems containing other closed sub-systems, and that each of these contain others—and so on. It follows that every sub-system in the recursion must be supervised, and internally known, only by the team in charge of that sub-system—all sub-systems and teams are thus ruled by a general principle of autonomy. Consequently, the technique allows those in charge of the general system, as well as those in charge of sub-systems, to pay attention to the interactions between the elements within the supervised sub-system only—what happens in neighboring sub-systems is, as it were, another team's business. Therefore, from the point of view of Beer's management cybernetics, this constituted an initial step towards the filtering of *variety*—i.e., the complexity of the system—and increasing autonomy, thus assuring the viability of that system. Second, the quantitative modeling of the relations between *flows* and *elements* would allow the detection of *bottlenecks* in the system, to thus select the key, conditioning variables of the workflow. This is particularly relevant because Project Cybersyn, as a whole, operated by modeling a wide range of variables, while however only processing a sample of them—which marks a key difference with contemporary data processing. Third, in the background of these considerations, on one hand Beer had already argued, in *Decision and Control*, that the collection and parsing of too many variables in the process of modeling a company was an actual problem for the manager aiming to control a productive system (Beer [1966] 1994, 96–98), and that therefore management cybernetics should provide ways to attenuate such a *variety* (Beer [1966] 1994, 289–98). On the other hand, however, an even more concrete matter emerged when the Cybersyn team faced *the real* fact that they had very limited access to infrastructure, equipment, and computational capacity to implement the project. Therefore, in contrast to the scientific ideal that demanded that the manager analyze the whole scope of variables detected in a system (Beer [1966] 1994, 97), Beer and his team had to rely on this quantified flowcharting technique and the nuances it proposed.

[Fig. 3] Stafford Beer's notion of recursion applied to his Viable System Model. Redrawn by the author from Raul Espejo's report "Proyecto Synco: Conceptos y práctica del control" (Source: Espejo 1973, 14).

This implied that the modeling of the factories would almost be a tailor-made process, where each case would go through a particular process of analysis, and thus through a specific quantified flowcharting. In other words, the OR team recognized that each factory was a system or rather a sub-system in its own right, even if it was part of an industrial branch—e.g., the timber industry—and that it would then have a particular set of variables. This time-consuming process was by no means an automated one—it was always developed by OR men. Only equipped with their training in operational research and the aforementioned technique, these men visited the factories and studied their operations. In a way—and this was part of the

**102** "noise" the Cybersyn team had to accept—this process included a fair degree of subjectivity (Beer [1966] 1994, 99). Let's consider for example the case of the textile industrial branch, which was then an important part of Chile's industrial economy. The modeling of such a branch was the responsibility of Tomás Kohn; a 28-year-old engineer who had studied at a technical university in the Chilean city of Valparaiso. It was there that Kohn first became acquainted with operational research, in his case through programming. Kohn attended Fortran courses taught by Wolfgang Riesenkönig—a German programmer who had moved to Chile to install the first Lorenz ER-56 digital computer in 1962 (Álvarez and Gutiérrez 2012a, 5). Later, supported by a Fulbright scholarship, Kohn studied in the USA, receiving his master's degree from Louisiana State University, where he delved into OR, statistics, and automatic control. As Kohn recalls, the process of modeling involved visiting the factories, and using the technique of quantified flowcharting, as well as several long meetings at INTEC to discuss the theoretical aspects that would help the team to better interpret Beer's work, the technique in question, and its results—a process certainly driven by technical skills, but, as Kohn states, also arrogance (Tomás Kohn, in discussion with the author, December 9, 2019).

An additional distinction becomes necessary here. It has been claimed, particularly by the US historian of informatics Eden Medina (2011, 101), but also by Beer himself in later interviews and writings (Beer 1974, 47)—perhaps as an attempt to match Cybersyn's politics of technology to Allende's socialist program—that factory workers had participated in, or that the project's original design considered them taking part in, Cybersyn's processes of modeling and the subsequent decision-making. However, concerning the modeling of production and its indexes, the findings of the research behind these pages suggest something different. When it comes to Cybersyn's politics of transmission—that is, the exchange of scientific discourses, techniques, technologies, data, and information—it seems

clearer every day that what took place at *Cybernet* is interwoven **103** with the old protocols of university teaching, academic papers, scientific and technical treatises, and operational reports—and whose carriers were, after all and mostly (although *not always*), highly skilled engineers.

### **Infrastructure**

Nonetheless, new protocols were also part of *Cybernet*; they came from the fields of telecommunications and computing, and their configuration was determined to a great extent by the infrastructure and equipment available in the country. Beer was well aware, years before Cybersyn, of the role that computation should play in operational research, and, all the more, in the development of management cybernetics—because, as he stated in 1966, "this [was] the age of 'automatic data processing'" (Beer [1966] 1994, 70). For Beer, the main goal of his cybernetic approach to management and control was, literally, a matter of time:

Even the most advanced countries in the world suffer from a vast lag in the receipt of economic data, and they suffer too from the bureaucratic time it takes to process these data towards any kind of conclusion. (Beer [1981] 1994, 248)

Beer argued that developed nations still had a lack of awareness regarding what "the current state of telecommunications and the computing art" (Beer [1981] 1994, 248) was, and what it could do to reduce the time of analysis of economic data, whose results used to arrive with an "average delay of nine months" (Beer [1981] 1994, 248). Therefore, he insisted that moving towards real-time processing was the only way to reach an effective level of data analysis, and thus of economic management. However, Beer and his team in Chile faced a difficult scenario, where the available technology was, in the cybernetician's own words, "antiquated" (Beer [1981] 1994, 248). Additionally, the chances to invest in new equipment were almost zero, in large part due to the political

**104** constraints affecting Allende's government regarding the international exchange of goods. Thus, despite the fact that the ideal design required interconnecting all the factories taking part in the project through a distributed network of *teleprocessing*—where each plant would have an in-house computer to process all the data that were "vital" for its operations (Beer [1981] 1994, 252) *the real* circumstances demanded something different. By 1971, Chile had only 57 computers; most of them being mainframes heavily used by either universities or administrative institutions (Álvarez and Gutiérrez 2012b, 28; Medina 2011, 60). On the other hand, being that Chile was then a poor country under strong political and economic pressure, buying new machines was not a viable option—consider here that the project aimed to connect over 100 companies, and that the price of a mainframe computer ranged between US\$1 and US\$2 million (Álvarez and Gutiérrez 2014, 131–35). Therefore, the team was forced—knowing that the project still required a reliance on the old Greek *tèle* (τῆλε)—to replace the word *processing* with the powers of transmission granted by *communications*. Thus, they looked at a reliable technology that by the 1970s had a robust infrastructure in the country; namely, *telex* networks.

Nonetheless, an important distinction has to be made here. One that acknowledges a key aspect of Eden Medina's unpublished PhD thesis (2005), and which—even if she decided not to emphasize it in *Cybernetic Revolutionaries*—is fundamental to assessing the scope of what follows. Despite the antiquatedness of Chile's technology as pointed out by Beer, the country had, not long before Cybersyn began, gone through what can be understood as a major technological transformation. In the government that preceded Allende's—the one led by the Christian Democrat, Eduardo Frei Montalva from 1964 to 1970—key developments unfolded: in 1964, the National Enterprise of Telecommunications (ENTEL) was put together, seeking to enhance and control the development of telecommunications in the country; in 1967, the National Commission on Computation was created with the

specific goal of advising the government on the use of computing; **105** in 1968, a National Enterprise of Computation (EMCO, later ECOM) was founded by and within the government, aiming to provide computing services to all the divisions of the state; and then, the same year, the aforementioned Institute of Technological Research (INTEC) was established. All these, alongside other efforts in the same direction, were benefited by, and in some way possible thanks to, foreign financial aid such as that coming from the USA's Alliance for Progress program (Medina 2005, 108–65; Álvarez 2014, 18–26).

Accordingly, ECOM acquired first an IBM 360/40 mainframe computer, and in 1970 another of this model as well as an IBM 360/50 (Álvarez 2014, 26)—machines that had been released on the market in August 1965, and were sold by IBM until 1977 (IBM n.d.). On the other hand, ENTEL inherited the technical management of part of a telex network inaugurated in 1959, but which had been heavily extended and technologically updated in 1967—a network originally developed by Chile's State Post and Telegraph Company on top of its own, old telegraph network (Diehl 1970, 21–37). This network's main station was in Santiago, with major line connections to the city of Valparaiso on the central Pacific coast, Concepcion in the south, and La Serena in the north (fig. 4). From the latter two, connections to smaller cities were established, and from Santiago, radio HF links activated nodes in the further north and south of the country (Diehl 1970, 35)—consider here that Chile is over 4,000 kilometers long, and that the far north and south offer particularly rugged geographical conditions. Moreover, the network also included a station of satellite links for international communications, which, 100 kilometers away from Santiago, was inaugurated in 1968 as the first of its kind on the continent (ENTEL-Chile ca. 1971).

Regarding the equipment used by this network, in 1965 the government granted concessions to two foreign companies as part of an expansion plan. Consequently, the machinery and technical support to build and maintain the central routing

[Fig. 4] Telex Network in Chile by 1970. Redrawn by the author from Lothar Diehl's *La Telegrafía en Chile*. (Source: Diehl 1970, 35).

stations was provided by Sweden's LM Ericsson (Diehl 1970, 27), which installed switching systems of the type ARB-111 and ARM-201 in the country (Ruiz Zúñiga 1976, 9–11).

Concerning smaller equipment, a brief digression is necessary. Medina and others have claimed that while working on the telex network, and facing a lack of machinery to complete this work, Project Cybersyn's team was fortunate enough to find hundreds of unused teleprinters in an ENTEL storage facility (Medina 2011, 72; Becket 2003). These claims, which have no formal reference, do not provide many details about the finding, nor about the type of equipment it consisted of. Hence, although the facts surrounding that discovery are still a missing link for the research sustaining these pages, it is now possible to offer some clarifications. When, in 1965, Chile's Ministry of Interior granted

[Fig. 5] The Siemens T-100 Teleprinter. Views from Service Manual. (Source: Siemens & Halske Aktiengesellschaft 1963, VI.3). Courtesy of Siemens Historical Institute.

the concession to provide teleprinting and harmonic telegraphy equipment for the country's public telex network, the recipient was the German company Siemens (Diehl 1970, 27). Moreover, when it comes to teleprinters in particular, the model acquired by Chile was the T-100 (fig. 5), and it is possible to state here that by April 1973 ENTEL had 265 units—215 in use, and 50 in stock—while the State Post and Telegraph Company had 1,063, of which only 182 were in stock (CORFO 1973, 43). Therefore, if the discovery of the unused teleprinters did indeed take place, this would have referred to a storage facility of the latter company. More simply, it was never about 400 or 500 units, but a rather smaller amount consider again that Project Cybersyn aimed to connect some 100 factories (Medina 2011, 86).

In a word, it was under these circumstances that the Cybersyn team would have found the equipment, and thus arranged and configured *Cybernet*. It is also true that some private telecommunications companies with a presence in Chile, such as the International Telephone & Telegraph Company (ITT)—secret exchanges with the CIA notwithstanding (Secretaría General de Gobierno 1972; Committee on Foreign Relations United States Senate 1973)—could have used British Creed teleprinters, and it is also possible that local armed forces used the American Teletype Corporation Model 33 ASR for their own closed telex networks (Ministerio de Defensa de Chile 1974). Nonetheless, as the widespread use in the public sector shows—e.g., the State Railways Company, which had its own network too (Orlando Contreras,

**108** in discussion with the author, December 19, 2019)—the Siemens T-100 teleprinter was by far the standard in the country.

Furthermore, the telex network used by the Cybersyn team had an identification system for subscribers—i.e., connected teleprinters—consisting of a five-digit code. The first two digits represented the area where the subscriber was located: the first indicated the region—Chile's central region was number 4—and the second referred to a district within that region—Santiago had the number 0. Thus, when subscribers in a southern region wanted to connect with a subscriber in the district of Santiago, they began by dialing 4 and 0. The remaining three digits identified the actual subscriber (Diehl 1970, 32–34). Given the increasing direct exchanges between national and international subscribers, the Chilean authorities introduced a protocol which, following the recommendations of the UN's International Telegraph and Telephone Consultative Committee (CCITT), gave each telex node an international identifier formed by a series of 20 signals that every teleprinter sent at the beginning of a message (Diehl 1970, 34). The series was structured as follows:

Signal: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Combination: ↓ < = ↑ N N N N N → ↓ X X X X X → C L ↓

Where,

The structure above can be seen in a telex message found at **109** the Stafford Beer Archive in Liverpool (fig. 6). Starting with the header, it is possible to notice: first, a shift to letters (↓); and then a line break (<). In order to make a small code analysis, let's jump to the fourth line, skipping the two red lines in the middle. The message shifts then to numbers (↑), presenting a five-digit figure (NNNNN) where the first two are 4 and 0—i.e., the subscriber was from the Santiago district. There follows a space (→) and a shift to letters again (↓); it reads CORFO—the Chilean development agency. After that, there is another space (→) and the CL code. It perfectly matches the protocol shown above.

Regarding the first two letters of this telex—G and A—further research has yet to be completed. However, the mere fact that the code begins with letters tells us something interesting. According to a report found at the documentation center of the Chilean Ministry of Transport and Telecommunications—the one informing these paragraphs—"the machines used in Chile (Siemens T 100)" had a default feature that made them begin every exchange with a shift to letter signal (Diehl 1970, 34). On the other hand, the color coding in the text was designed to identify between outgoing messages, in red, and incoming ones, in black (Siemens & Halske Aktiengesellschaft 1963, V.3). Consequently, it is possible to notice that the message from the Stafford Beer Archive was in fact printed at ECOM, and that the black text was incoming data from the receiver subscriber; in this case, a teleprinter at CORFO—with both sender and receiver located in Santiago.

Another relevant aspect can be found in the footer of this message (fig. 7). The small cross indicates the "who are you" symbol, which gave information regarding the identities of the parties involved in an exchange. More interestingly, not all teleprinters printed that square, Prussian-style cross as the Siemens T-100 did (Siemens & Halske Aktiengesellschaft 1963, II.9–13)—models from other manufacturers printed either narrower, or thinner and color-filled crosses. In other words, it is possible to confirm

[Fig. 6] Telex Message between ECOM and CORFO, April 1973—Header. Stafford Beer Archive, Box 64. Courtesy of the Stafford Beer Archive, Liverpool John Moores University, Special Collections & Archives.

[Fig. 7] Telex Message between ECOM and CORFO, April 1973—Footer. Stafford Beer Archive, Box 64. Courtesy of the Stafford Beer Archive, Liverpool John Moores University, Special Collections & Archives.

that subscriber number 40506 from Chile's ECOM was a Siemens teleprinter.

Yet, it must be noted that *Cybernet* was configured to support a very specific goal: "To install a preliminary system of information and regulation for the industrial economy" (Beer [1981] 1994, 251). Put differently, beyond the technical specifications of the network and its equipment, the data sent from the factories to the processing center should also have their own protocols. Hence, given that the incoming data had to match the requirements of the software suite being developed by the *Cyberstride* team, these

**110**

protocols were designed in the offices of ECOM—where the local **111** *Cyberstride* team was based. This was done while paying special attention to the indexes the OR team obtained from the modeling process at the factories. Accordingly, the protocol consisted of a series of codes for each factory, which referred precisely to such indexes (Benadof 1972, 1–5).

For the textile industrial sector for example, a code looked like this: TEXSAIMPEXISTENPOLSTW (Benadof 1972, 2). The codes were formed by 22 letters, where the first three referred to the sector, and the following five indicated the name of the factory. After that, the next 12 letters showed the specific index, in this case "existence polyester," or the stock level of polyester. Similarly, ECOM had prepared a small form which the people at the factories had to fill in with the respective data (Benadof 1972, 2–3). Nonetheless, one question remains: who was seated in front of the teleprinter at the factories and typed out this data? Although the findings of this research on this matter are still not fully conclusive, some preliminary informed conjectures can be offered. Considering that the companies connected to the project used to have departments of industrial operations led by engineers trained in OR—that is the case, for example, for a textile company this research has investigated (Manuel Núñez, in discussion with the author, December 5, 2019)—it is probable that the values of the daily indexes had been collected by members of these departments. Moreover, because those unassuming forms were still simple sheets of paper with blank boxes where letters should be entered, it is also possible that they had been filled out with that old and traditional tool called the pen, before being as if Kittler's theories were again pushing for the conclusion of this section (Kittler [1986] 1999, 183–263)—transcribed, finally in real contact with the machine, by female secretaries (Isaquino Benadof, in discussion with the author, December 4, 2019; Manuel Núñez, in discussion with the author, December 5, 2019).

And since power after the print monopoly's collapse was diverted to cable and radio, to the recording of traces and **112** electrical engineering, outdated security protocols were dropped as well (Kittler [1986] 1999, 195).

#### **Tele[economy]cations**

Almost 100 years before Cybersyn, in January 1874, another exchange between the Chilean government and a British technology businessman took place (West Coast of America Telegraph Company Limited 1875, 10–11). Strictly ruled by the ceremoniously handwritten protocols of notaries, and of the UK's and Chile's 19th-century legislation (Horacio de Pinna 1898), this triggered a series of commercial transactions and concessions that eventually led to the laying of a submarine cable connecting the Peruvian seaport of El Callao, and its Chilean equivalents in Caldera and Coquimbo at that country's north, and in Valparaiso in the center (West Coast of America Telegraph Company Limited 1875, 10–12). Moreover, these developments brought about the arrival of the British West Coast of America Telegraph Company Limited in Chile, with the subsequent construction of a telecommunications network that—linked to the network built by Clark's Transandine Telegraph Company—connected the main ports and business centers of Chile with Europe, using cable technology that spanned Buenos Aires and Pernambuco, all before 1876 (Diehl 1970, 15–16). The reasons behind such a level of technological entrepreneurship in this remote corner of the world would be hard to explain in detail here. However, it is possible to state that they are strongly linked to the vast deposits of natural resources in the area—e.g., nitrates and copper in the north, as well as coal in the south—and the local governments' great interest in exploiting those resources with the help of foreign capital (Monteón 2003). In a word, the early arrival of telegraphy technology and infrastructure to Chile is inextricably attached to economic exchanges. Its purpose, consequently, was to serve as a platform of communication, supporting commercial transactions and the capital interests behind them.

Therefore, a media-archaeological analysis of Project Cybersyn, **113** and particularly of *Cybernet* and *Cyberstride*, cannot avoid a genealogical approach. If a problematization of Project Cybersyn as an apparatus, as a *dispositif*, is in effect possible, one is compelled to study, as pointed out earlier, the "set of strategies of the relations of forces supporting, and supported by, certain types of knowledge" (Foucault 1980, 196). Accordingly, when a secretary seated in front of a Siemens teleprinter types almost incomprehensible codes, followed by dates and decimal numbers with the goal of transmitting pure economic data, what emerges is *the symbolic* displacement of the centrality of human understanding: a techno-episteme which is invariably attached to a still ungraspable politic of transmission. Its genealogy, however, is undetachable from a longer history of scientific discourses, infrastructure, technology, and information exchanges. One is thus compelled to ask: whose agency would have emerged, then, in Chile's 1970s factories? All the more, is there a component of that agency that could account for the 100-year genealogical transformation in that corner of the world?

An attempt to answer such an inquiry leads to the question of value; its formation, and the place and time where all that is hosted. Then, with the archaeologist, it may be said:

It is thus no longer a question of knowing in accordance with what mechanism kinds of wealth can represent each other (and represent themselves by means of that universally representative wealth constituted by precious metal), but why objects of desire and need have to be represented, how one posits the value of a thing, and why one can affirm that it is worth this or that (Foucault 2005, 206).

Yet, in that distant and lonely room where the secretary types, who is *the one* that posits the value of a thing, when all that she has at her disposal is a frenetic clacking machine, its keyboard, and a series of puzzling codes? Literally, then, there seems to be *no one*. She fades away *in* the machine, and thus the possibility of

[Fig. 8] Printout of *Cyberstride*'s Permanent Suite. (Source: ECOM 1972, 3). Courtesy of the Stafford Beer Archive, Liverpool John Moores University, Special Collections & Archives.

finding *a single place* for the formation of value is left adrift. This is so because, starting from the teleprinters, throughout the telex network, to the processing center, every place has been replaced by sequences of symbols, and all formations by their constant erasability. Hence, that which this sort of archaeology can no longer tell us could then be pointed out by cybernetic thinking: "That is to say that cybernetics studies the flow of information round a system, and the way in which that information [data, in this case] is used by the system as a means of controlling itself" (Beer [1966] 1994, 254). Put differently, data for the system, and a system for that data. Does this interrelation indicate the moments and the processes through which a new sort of value began to be encoded? One that emerges from feedback, or self-regulation?

Again, if one is able to study Project Cybersyn as a *dispositif*, it must be considered, with Agamben, that starting from Foucault's *positivity* we can traverse the broad and complex notion of *dispositif*, to arrive to the old Greek term *oikonomia*: "the administration of the *oikos* (the home) and, more generally, management" (Agamben 2009, 8). Therefore, could we then

**114**

problematize Project Cybersyn as an economic system of trans- **115** mission, processing, and storage of data, and of its encoded value? A system whose ultimate aim is making *its own economic condition* viable? Would this signal a knot shaped by the archaeological and genealogical echoes of a stubborn cybernetic thinking? A knot that could help us unravel the way in which this technological project of management, this technological economy of *dispositions*, thus constitutes a project for governing the *oikos* too?

The notion of *tele[economy]cations* aims to highlight these questions; to emphasize the ways in which they could activate an analysis and a discussion on the techniques, technologies, and scientific discourses that interconnect *Cybernet* and *Cyberstride*. This sort of approach requires, nonetheless, a materially grounded research strategy; one that can prove—against the claims suggesting that Project Cybersyn simply could not have worked—that after all, it did function. That the evidence confirms that, at least in the case of *Cybernet* and *Cyberstride*, they were indeed in operation (fig. 8), and that their features were applied to encode, transmit, and process data from about 20 factories (Isaquino Benadof, in discussion with the author, December 4, 2019) before, 50 years ago, on September 11, 1973, a coup d'état destroyed everything.

*The field and archival work behind this chapter was partially funded by Chile's National Agency of Research and Development through the doctoral grant no. 72200037.*

#### **References**

	- ———. 2014. "Empresa Nacional de Computación, Chile: Antecedentes, creación y primeros años." In *Proceedings of the XL Latin American Computing Conference*, edited by Pablo Ezzatti and Andrea Delgado, 128–36. Montevideo: Universidad de la República.
	- Beckett, Andy. 2003. "Santiago Dreaming." *The Guardian*, September 8, 2003. https:// www.theguardian.com/technology/2003/sep/08/sciencenews.chile.
	- Beer, Stafford. 1971a. Stafford Beer to Fernando Flores, July 29, 1971. Liverpool John Moores University, Stafford Beer Archive, Box 55.
	- ———. 1971b. "Project Cyberstride," Santiago, November 1971. Liverpool John Moores University, Stafford Beer Archive, Box 57.
	- ———. 1971c. Notes and Sketches from November 1971. Liverpool John Moores University, Stafford Beer Archive, Box 57.
	- ———. 1974. *Designing Freedom*. London: John Wiley & Sons.
	- ———. 1972. "Cyberstride: Preparations," January 1972. Liverpool John Moores University, Stafford Beer Archive, Box 57.
	- ———. (1981) 1994. *Brain of the Firm, 2nd Edition*. Chichester: John Wiley & Sons.
	- ———. (1966) 1994. *Decision and Control. The Meaning of Operational Research and Management Cybernetics*. Chichester: John Wiley & Sons.
	- Benadof, Isaquino. 1972. Empresa Nacional de Computación e Informática, Gerencia de Ingeniería, Departamento de Análisis de Sistemas, Manual de Perforación TS - 07, Sistema Cyberstride, Temporary Suite. Liverpool John Moores University, Stafford Beer Archive, Box 57.
	- Committee on Foreign Relations United States Senate, Subcommittee on Multinational Corporations. 1973. *The International Telephone and Telegraph Company and Chile, 1970–1971*. Washington DC: Congress of the United States of America.
	- Contreras, Orlando. 2019. (Former technician, Department of Signals, Chile's State Railway Company), in discussion with the author, December.
	- CORFO. 1973. *Armaduría de Teleimpresores ELECNA*. CORFO, Subgerencia de Industrial Liviana, Comité de Industrial Eléctricas y Electrónicas. Santiago: CORFO.
	- Diehl, Lothar. 1970. *La Telegrafía en Chile*. Santiago: Dirección Nacional de Correos y Telégrafos, Subdirección de Telecomunicaciones.
	- ECOM. 1972. Informe Algedónico Taxonómico, Permanent Suite. Liverpool John Moores University, Stafford Beer Archive, Box 57.
	- ENTEL-Chile. ca. 1971. Promotional flyer, "National Telecommunications Company— ENTEL-Chile." Liverpool John Moores University, Stafford Beer Archive, Box 64.
	- Espejo, Raul. 1973. *Proyecto Synco: Conceptos y práctica del control, una experiencia concreta: La dirección industrial de Chile*. Santiago: CORFO
	- ———. 2019. (Former director of operations, Project Cybersyn, CORFO), in discussion with the author. January.
	- ———. 2019. (Former director of operations, project Cybersyn, CORFO), in discussion with the author. May.
	- Espinosa Wellmann, Raul. 2019. (Former systems engineering professor, Pontifical Catholic University of Chile), in discussion with the author. December.
	- cussion with the author. December.

# **CYBERNETICS**

 **TECHNOLÓGOS**

 **MATTER**

 **DIAGRAMS**

# **[5] On the Notion of Cybernetic Frictions and its Role in Radical Media Archaeology**

**Wolfgang Ernst**

**This chapter asks to what extent the technical realizations of cybernetic projects still relate to their conceptual diagrams. This is assessed by discussing three types of endeavors: a) those from the early years of cybernetics showing asynchronous frictions between the unfolding of cybernetic thinking and the pace of technological deployment; b) the mid-century attempts to implement cybernetic models in culture and society, where infrastructure itself appears as the source of resistance; and c) the still recurrent efforts to develop diagrammatic and techno-material methods to study the feedback loops between the environment, natural resources, and their industrial**

# **<sup>120</sup> appropriation. Hence, it will be argued that the techno-logical frictions emerging from mate(real)izing cybernetic systems should not be seen simply as collateral damage, nor as noisy disturbances, but rather as an essential component of the techno***lógos* **of cybernetics.**

This book, as well as the *Applied Cybernetics* lecture series coorganized by the Institute of Musicology and Media Studies at the Humboldt University of Berlin and the Institute of History and Philosophy of Science, Technology, and Literature at the Technical University of Berlin,1 have not simply been an administrative matter of academic cooperation, but, almost by necessity, a programmatic act. It takes the combined effort of technical analysis—e.g., computer and engineering sciences—and fields in the humanities—e.g., media epistemology, media archaeology, techno-poietics, machine-oriented ontology—to address the temporal moments, and spatial sites where cybernetics as a conceptual frame—the symbolic order—confronts its material *real*—its literal mater(e)alization.

The core drama enacted on the landscape of the technological world stems from the entanglements of logical reasoning with the material real—the *mateReal* in a more Lacanian sense (Kittler 1999). Analog and digital technologies oscillate between *logified* matter and mechanized mind. Thus, *radical* media archaeology becomes an adequate method to investigate concrete scenarios *in*, and *as* the cybernetic media theater. The encounters of technical reason (*lógos*) with in-formable matter occur in two ways: one being method, the other actual realizations. Media science, with media archaeology as its method, radically *grounds* the investigation of technical objects in actual matter, aiming to discover its main sources of action (*archai*). How close can

#### such analytic *lógos* get to what is unfolded within the technical **121** *mateReal*?

According to the research hypothesis of radical media archaeology, it is in these frictions that the techno*lógos* of cybernetic thinking can be found. A *frictionless* functioning of technologyb(i)ased communication, or a "friction-free world" (Tapscott and Tapscott 2016, 265), is a fallacy which does not account for the *veto* of its material implementation. Friction is a term well known from mechanical physics, one that Carl von Clausewitz applied to his seminal theory of war to describe the differences— *Friktionen*—between the strategic diagram and the actual hindrances occurring in its practical implementation (von Clausewitz 1832). In the case of Chile's Project Cybersyn, there were two types of diagrams: the cybernetic design—Stafford Beer's Viable System Model—and the actual technical system—the teletype network. Likewise, the processing of the data sent from stateowned factories across the country was dependent on the only IBM mainframe computer available to the project in Santiago.

This case may be generalized when it comes to explaining the failures and applications from the *heroic* era of cybernetics: its limited computational capacities were just not yet ready for the implementation of *Big Data* processing in (almost) real-time e.g., for the simulation of neurological signal processing in the human brain, or what is today called *deep* machine learning, even if artificial intelligence was one of the core concepts developed during the classic cybernetic epoch. What nowadays are celebrated as artificial intelligence, machine learning, process simulations, and neuro-aesthetics, are to a large degree a reoccurrence of cybernetic reasoning, with the only difference being that microprocessors can now achieve the demands of cybernetics.

## **<sup>122</sup> Heroic Implementing Efforts**

As an example, the former Institute for Cybernetics in Paderborn, run by Helmar Frank, coined the notion of "programmed instruction" (*programmierte Instruktion*) for pedagogics in the 1960s to implement not only automated learning in schools, but to replace teachers themselves by an algorithm (Englert et al. 1966). At the very moment when, in the early 1970s, Frank's institute had finally developed a model computer (the MORE) in cooperation with the neighboring computer company Nixdorf as both learning assistant and didactic object for self-learning (Höltgen 2019; Frank and Meyer 1972)—this TTL-based computer had been surpassed by the first generation of INTEL microchipbased home computers, which were more effective as learning assistants, but conceptually not really conceived as a cybernetic device (Zuther 1996).

Another case is the seminal "tortoise" developed by neurologist William Grey Walter in 1951; an operative demonstration of the core thesis of cybernetics—McCulloch's "experimental epistemology" (McCulloch 1965)—stating that from a limited number of neurons in the brain, or their equivalent as electro-magnetic relays, complex behavioral patterns emerge. Multiple frictions become evident when trying to re-implement Walter's intent from his archived circuit diagrams.  When such frictions are read with different, media-archaeological eyes, they rather point to the limits of a brain-computer analogy in a more epistemological sense.<sup>2</sup>

A decisive parameter of these frictions—which occur not simply in the logical, but in the technical implementation of cybernetic diagrams—is their actual temporal behavior. "One important

2 As shown at Humboldt University's Media Theater in 2018 by Juliette Bal's *Tortoise* Juliette, with the local engineering assistance of Ingolf Haedicke.

fact about the computing machine as well as the brain is that **123** it operates in time" (Wiener 1948, 214)—that is, to be precise, in *different* times. While the human brain *calculates* in parallel mode, computing in the Von Neumann architecture operates strictly sequentially. "As long as we mean by 'parallel' only more simultaneous discrete operations, I do not think it is the basic problem" (Pattee 1974, 146). But it is in that "time of non-reality" (Pias 2003, 158; Pias 2009)3 that the unconscious flashes up as the *tempoReal*.

In 1948, at the outbreak of the Cold War between East and West, Norbert Wiener defined a transubstantiation in communication engineering: "Information is information, not matter or energy. No materialism which does not admit this can survive at the present day" (Wiener [1948] 1961, 132). Socialist countries collapsed because their economy, for ideological reasons, anachronistically insisted on the priority of matter and energy (Ernst 2013). Still, *applied* cybernetics cannot be reduced to its logical or mathematical diagram, but it can operatively come into being only as techno-mathematics, or techno-logics, which makes all the difference when it comes to frictions. That is why cybernetic systems cannot be reduced to pure semiotics—that is, symbolical analysis. The proof of cybernetic reasoning (the pudding) is in its material implementation (in its eating). The techno-practical *computing* being, as an instantiation of orders in the form of algorithmic programs, is the effective criterion of *computational* abstraction.

Many processes in nature must be such that we cannot understand them in terms of a computer program and at the same time put our understanding to the test by running the program on a machine. (Conrad 1995, 279)

3 Wiener revealed his techno-poetic notion of a computational "time of nonreality" at the 1949 Macy Conference, and this was later problematized by Pias.

**124** Against the cybernetic idealism of a seamless modeling of human processes by computing machines, J. C. R. Licklider's seminal text on the human-machine "symbiosis" (Licklider 1960) explicitly points to the differences that arise in the communication between human and non-human agencies. Such frictions do not simply irritate the human-machine *dialogue*, but actually reveal that the dialogic approach is wrong from the beginning. It is from the differences between human reasoning and techno*lógos* that a productive, informative interaction derives.

One of the variables of the frictions which occur when the symbolic order encounters the real is the fully technological machinemachine coupling; a central configuration of cybernetic systems. The media-theoretical techno*lógos* hypothesis states that "the apparently always noisy attempts for bringing such cybernetic systems into full and successful application" (Humboldt-Universität n.d.) is not accidental, but intrinsic to the techno-logical reasoning at work behind its ideal design. This technological reality can be analytically delineated. A central thread of the *Applied Cybernetics* lecture series was "to discuss if, considering the human-machine coupling as the core and hinge of any cybernetic system, the factors that may have truncated the historical deployment of cybernetics remain intrinsic to such core, are external to it, or respond to the articulating quality of such hinge" (Humboldt-Universität n.d.).

In the implementation of cybernetic reasoning, to what extent do the symbolic diagram (or code) and technical matter actually matter? Concerning Chile's Project Cybersyn, in his letter to Stafford Beer from July 13, 1971, Fernando Flores pointed out the *kairotic* (time-critical) moment at which cybernetic thinking may become operative reality, and the opportunity to implement it on a national scale.4 Beer's first visit to Chile, in November 1971, resulted in flowcharts, notes, and sketches. But against a metaphysical body-mind dichotomy—so familiar to Western

ontology—radical media archaeology insists that any sym- **125** bolic operation is already *rooted* in activatable matter—be it the human brain, or electronics. To *en/code* already involves a material medium in the sense of *implementation*—a concept that always includes the options of its realization. It is only by its physical implementation that an abstract algorithm becomes actual software.

Institutionally, cybernetics always oscillated between the rather goal-oriented engineering approach, and a more abstract mathematical system modeling. That is the moment when the specific cultural and social contexts surrounding the application attempt of a particular case must be examined; the moment when either of these approaches were chosen. While the tracing of the discursive, aesthetic, historical and/or political contexts bringing frictions into cybernetic systems is the concern of science and technology studies (Medina 2011), radical media archaeology analyzes the (techno-)epistemological momentum in the actual mate(real)izations, which account for the scope, success, and failures of cybernetics.

One critical aspect in the implementation of the symbolic cybernetic order (feedback-enabled systems) that makes all the difference when transforming the abstract diagram into an operative one (electric circuitry) is the *tempoReal*. This has been expressed in Beer's time-critical approach to economic operations management—in fact inherited from the previous *war theater*. The "vast lag in the receipt of economic data" and the "bureaucratic time it takes to process these data" (Beer [1981] 1994, 248) required, in cybernetic reasoning, to be literally updated in favor of real-time data processing.

Another critical aspect of the encounters of the symbolic order with the *mateReal* is the difference between code (the algorithm) and electronic hardware, which runs parallel to the difference between the Turing Machine's abstract computation, and actual computing. Operational diagrams require a material

**126** technological infrastructure, such as a telegraph network, in order to become dynamic cybernetic systems, and acquire negative feedback options in data teleprocessing for the system to control itself—that is, to let its techno*lógos* articulate.

## **The Cybernetization of Architecture**

The architectural design for Ruhr University Bochum in 1960s West Germany was the product of cybernetic systems thinking. The concept failed, to a large degree, precisely due to its material implementation; architecture cannot become cybernetic as long as its building materiality remains unsuitable for recurrent, feedback-based modifications. Only when a symbolic diagram is embedded in concrete matter does it become an actual, operative circuitry. A rejected architectural proposal for Ruhr University by Eckhard Schulze-Fielitz—the Lattice Grid City (*Raumgitterstadt*)—came close to an architectural cybernetics (Bauwelt 1963, 541). "Based on adaptable tubular structures it would form a flexible architecture, that would enable the university to adapt to demand, climate and terrain … a true form of cybernetic architecture as it would have been able to react based on feedback" (van Treeck 2019). This echoes Negroponte's "architecture machine" (1973).

In the planning of Ruhr University's architecture, its underlying diagram aimed "to prioritize informational flows" (van Treeck 2019) by updating the notion of the German university: it sought to open the doors between previously strictly separate academic disciplines, as if they were logical gates in the computer engineering sense. However, frictions between the *lógos* and *techné* of architecture—its actual embodiment—soon took place. Administrative processes may be symbolically expressed in flowcharts, and can thereby be formulated as an algorithm. But actual computing, such as in the *Von Neumann architecture*, differs from macro-spatial building architecture indeed. Concrete architecture cannot itself incorporate the cybernetic techno-logics, since its

crucial agency is missing. Feedback is the techno-epistemic core **127** of cybernetic (self)-governance, where output signals regulate the whole process by re-entering the still-running system, either as information in positive (amplifying) or negative (self-regulating) ways. "Maybe architecture when it manifests itself in brick mortar and masses of concrete is not the right medium to incorporate feedback. At best it can facilitate it among the elements that make up the procedural flows it canalizes: people" (van Treeck 2019).

### **H. T. Odum's Applied Systems Thinking**

After World War II—going beyond its military applications such as anti-aircraft prediction—cybernetic systems theory was extended to ecological questions by conceptualizing the feedback loops occurring between the environment and natural resources on the one hand, and in its industrial appropriation on the other (Taylor 1988). The operators of this modeling were theorems, mathematical analysis, and diagrams; its mathematical and material computational episteme was analog computing. Such diagrams became operative technical circuitry in the 1950s and 1960s when H. T. Odum developed "simple electrical networks composed of batteries, wires, resistors and capacitors as models for ecological systems" (Kangas 2004, 101). Circuit diagrams "called passive analogs to differentiate them from operational analog computer circuits, which simulated systems in a different manner" (Kangas 2004, 101). Odum designed a symbolic language to simulate and model ecological and social systems with electronic units such as resistors for delaying, or capacitors for shortterm storage. "The language consists of a dozen basic modules, each having a mathematical definition" (Odum 1972, 141). In the sense of operative diagrammatics, "the simulation procedure for the energy circuit follows in simple automatic manner from the energy circuit diagram; the thinking on the behavior and structure of the system is done in the diagramming" (Odum 1972, 210). Odum applied this cybernetic reasoning to a practical

**128** teaching program in a signal laboratory: "Students with a yen for the soldering iron can be utilized in combining physical and biological science to make a gadget, which mimics in some ways the flow of materials in the ecosystem" (Odum 1960, 77). But anyone who has ever translated a circuit diagram into real circuitry has experienced the frictions which arise. Actual soldering is, in fact, the most concrete event where the encounter of the symbolic order and *mateReality* take place—a media theory of soldering is still missing (Schulze 2022). What comes close is the symbolic coding of a field-programmable gate array (FPGA) for computer microchips by means of the Very High Speed Integrated Circuit Hardware Description Language (VHDL).

Odum's electrical models became early examples of a technically applied systems ecology, somewhat in parallel to Alban B. Phillips's hydraulic MONIAC (Monetary National Income Analogue Computer) from 1949, preserved in the London Science Museum. The techno*lógos* of such an approach, in the most media-archaeological sense, respects the material embodiment of any kind of symbolic thinking:

Whereas operational analog methodology involves the writing of differential equations first, passive analog methodology bypasses the equations except to verify the similar behavior of the particular hardware pieces used. The energy network language and the electrical model are forms of mathematics *in themselves*, but forms that naturally resemble the normal ways of thinking in biology, ecology, and the social sciences. (Odum 1971, 261)5

To sum up, the question arises: to what extent does a technical realization still relate to its cybernetic conceptualization? The techno-logical frictions that occurred, and still occur, in the efforts of mate(real)izing cybernetic systems, frequently resulting in their failure, are not simply collateral damage, or

noisy disturbances of an otherwise intact reasonable concept. **129** The material and energetic frictions that take place in *applied* cybernetics—that is, materially implemented cybernetic system thinking—have frequently been considered a troublesome side-effect. Against such an idealistic (techno-)logocentrism, a different hypothesis has been proposed here: these frictions are essentially inherent to the techno*lógos* of cybernetics itself. They deserve to be conceptually included in a techno-materialist second-order cybernetics. Accordingly, radical media archaeology pays less attention to the specific cultural and social contexts that may explain their surrounding conflicts, to focus itself on unraveling their essential role from within technologies themselves.

#### **References**

Bauwelt. 1963. "Wettbewerb Universität." *Bauwelt* 19/20: 541.

	- Medina, Eden. 2011. *Cybernetic Revolutionaries: Technology and Politics in Allende's Chile*. Cambridge: MIT Press.
	- McCulloch, Warren S. 1965. *Embodiments of Mind*. Cambridge: MIT Press.

Negroponte, Nicholas. 1973.  Cambridge: MIT Press.

# **TEACHING MACHINES**

 **MORE**

# **RECHNERKUNDE**

# **HELMAR FRANK**

 **B. F. SKINNER**

# **[6] Teaching Machines: Learning as Subjective Technique and Feedback Loop**

**Stefan Höltgen and Rolf F. Nohr**

**This chapter presents a short media history of teaching machines with a focus on their development at West Germany's Institute for Cybernetics during the 1960s and 1970s. Special media-archaeological attention is paid to the MORE computer and the** *Rechnerkunde* **approach devised by Helmar Frank and Ingeborg Meyer. Accordingly, this work argues that by tracing the frictions between the USA's perspective on teaching machines—embodied in B. F. Skinner's work—and West Germany's outlook on these systems, contemporary epistemological echoes of teaching machines can be discerned.**

*For every old blackboard there are now hundreds of new electronic computers. —Dwight D. Eisenhower (Norberg 2005, 267)*

We are currently experiencing a boom in the use of digital tools in the educational landscape; not only because of the challenges brought about by the coronavirus pandemic. Apart from their often-improvised use and the recurrent failure of these technoeducational methods—mostly due to the lack of infrastructure and equipment—one notable aspect of this *improvised field test* is the fact that it is not unprecedented. The history of education and media is full of undertakings that sought to produce learningassistant systems that sometimes aimed to expand and support educational environments. Others, however, simply intended to eliminate the *teaching subject* by automating the production of learning results while making them measurable. In light of the current, technologically-driven teaching scenarios, it seems appropriate to examine the history of automated education, especially considering the mechanisms of self-regulation and automated individual learning that have always been a promising aspect of this history. Therefore, paying attention to the development of teaching machines in the 1950s and 1960s, and to the work of German computer scientist Helmar Frank and his *Institute for Cybernetics* (IfC) in particular, we will argue that the connections between automated learning systems and specific *subject effects* have a deep, *genealogical* dimension. We think that, in order to understand and assess the current debates on educational software, remote teaching, blended learning, and flipped classrooms—especially in relation to results and performance—we need to consider the historical constellations that paved the way for the implementation of these techniques.

## **Teaching Machines**

Machine-aided learning systems first emerged in the USA in the mid-1950s, coinciding with the surge of cybernetics, computer-based data processing, mathematics model theory, **135** operations research, and system dynamics. Initially designed as mechanical devices—as opposed to electronic ones—these teaching machines briefly received a lot of attention. They were, at times quite enthusiastically, integrated into schools as well as into the field of science, and were perceived positively by the public. In 1961, *Popular Mechanics* published a report on teaching machines titled "*Will Robots Teach Your Children?"*—a title which could hardly have been further from the truth. The subheading promised "a revolution in mass education": a statement in line with the contemporary discussion on the topic (Bell 1961, 152–57). When they were first used in schools in the USA in the early 1960s, teaching machines were not seen as a means to organize education via an automated third party. Rather, they offered a method to pragmatically help in overcoming the crisis in schools and universities (Foltz 1965, 17)1 based on autonomous and selfmotivated learning approaches. The initial focus was therefore on the course syllabus itself—as opposed to the technology which was essentially mapped through multiple-choice tests with immediate feedback. Students were seated at a mechanical device (not yet a computer) and tackled the subject matter themselves in an intense question-and-answer process. The devices presented *subject matter segments* followed by a set of questions the student had to answer. If the answers were correct, the device proceeded to the next step; if they were wrong, the subject matter presentation was repeated in iterations of diverse complexity. Students made their way through the syllabus at

1 Although a lack of teachers and funding had repeatedly been brought up to justify the necessity of educational reforms, some sources offer a different reason: the West's perception that it lagged behind the achievements of the socialist bloc. In the times of the post-war economy and the looming Cold War, the Western world's need to remain dominant, both in the technological and epistemological spheres, was clear, especially in light of the Sputnik crisis. In Skinner's words: "Our schools, in particular our 'progressive' schools, are often held responsible for many current problems including juvenile delinquency and the threat of a more powerful foreign technology" (Skinner 1958, 976).

**136** their own pace, depending on their individual ability to "process knowledge." The iterations—which could potentially be executed endlessly—aimed to ensure the progress of learning. The very fact that teaching machines were both technology- and humanbased emphasized the individuality of the learning process, and that the progress of learning could be distinctly measured and processed. However, teaching machines also posit the potential redundancy of a human teaching instance. They embodied the promise of the algorithmization of the learning process, suggesting that traditional teaching formats, subjective teaching styles, as well as collaborative learning could all be suspended. The key notions here—or rather the epistemological discourses supporting the conviction that teaching machines worked—were the ability to condition the learning subject—i.e., behaviorism and the effectiveness of semi-automated feedback processes and loops during the learning process—i.e., cybernetics. Accordingly, teaching machines were developed for preschoolers and adults, were used in mathematics and language lessons, and were even used to train staff at nuclear missile silos.

## **Skinner's Machine**

The rise of teaching machines coincides with the advancement of modern education and one of its protagonists: Burrhus Frederic Skinner. A representative figure of behaviorism, a discipline to which he contributed substantially, Skinner and this field provided the foundations for programmed learning—which was not merely theoretical. In fact, Skinner worked on developing his own teaching machines. In a seminal essay from 1958, Skinner signals two central developments that, he believed, necessitated the establishment of automated learning: the increasing complexity of tasks in education due to a rising population (Skinner 1958, 969–77) and, on the other hand, the challenge of adapting the educational environment to the technical possibilities of the time—the development of audiovisual media was one of the reasons that made the introduction of teaching machines

[Fig. 1] B. F. Skinner's early Teaching Machine. Source: image by Silly Rabbit, CC BY 3.0. https://commons.wikimedia.org/w/index.php?curid=3806150.

possible. In his autobiography, Skinner describes the central "enlightening experience" that originally inspired him to take a closer look at teaching machines. He visited his daughter's math class, where he noticed that students did not receive immediate feedback on their performance (Skinner 1983, 64). The class took a test, which the students then handed in, after which it was corrected and given back to them several days later. This, said Skinner, was contrary to the behavioristic theory of learning; the fact that there is no immediate feedback between the test and its correction undermines learning results (Watters 2021, 19). Consequently, Skinner built the prototype of his first machine (fig. 1), which strictly adhered to Pavlov's notions of operant conditioning; when the student provided the correct answer for a question, a bell rang (Watters 2021, 20).

In later developments, Skinner referred to studies that psychologist Sidney L. Pressey had conducted in the late 1920s— Pressey proposed his own programmed learning system, but initially had no public success (Skinner 1958, 969; Benjamin 1988, 703). Starting from his theory of learning, and closely following

**138** Edward L. Thorndike's approaches on "instrumental conditioning" (Niemiec and Walberg 1989, 265), Pressey developed a simple test device that required students to answer questions by pressing buttons, providing immediate feedback on their inputs. In 1926, Pressey himself summarized the results of his work at Ohio State University: the immediacy of the feedback would fix the correct answer to the subject's memory, and the device could be adapted to give out candy or other forms of reward when the student reached a specific level. This confirmation of achievement would have "cemented the learning results" (Pressey 1960, 37; Watters 2021, 61–80).

In his interpretation of Pressey's work, Skinner understood that machines for programmed learning would both *test* and *evaluate*, and at the same time, they would trigger actual learning processes. These processes would also be characterized, to a considerable extent, by the individualization of the learning process,2 resulting in an "industrial revolution in education" (Skinner 1958, 969).3 However, Skinner goes beyond Pressey's work by redefining the learning process itself; that is, a modification of emitted changes in behavior, rather than a mere conveyance of knowledge. For Skinner, this made the machine a secondary actor compared to the actual "knowledge-changing program" (Niemiec and Walberg 1989, 266).

Beyond the apparent similarity with the Taylorian principle of increasing effectiveness, which was popular at the time (Niemiec and Walberg 1989, 264), the underlying notion of behavioristic

learning (Lumsdaine 1959, 164) is key to understanding the **139** teaching machines movement. In the discussion on teaching machines, the learning effect is usually understood as part of operant conditioning, characterized by an almost immediate, individualized feedback on learning results, or to be more precise, on the correctness of the answers (Foltz 1965, 41). This is the predominant way of thinking of behaviorism, where observable, empiric, and unambiguous human (and animal) reactions are traced back to environmental stimuli. The black box metaphor is a typical example of this: the interior structure of the studied object is initially of no interest; a demonstrable connection between input and output is key. In the concrete case of teaching machines, this input is specific teaching content combined with the size of the class, the age of the students, and the duration of the teaching session; the output is the measured success of the learning process (Zöller 1975, 99).

In the 1960s, this *operant* conceptualization of the learning process brought about two schools of thought on programmed learning processes based on instructional devices: the Skinner school and the Crowder school (Fry 1963, 17–34)—Norman A. Crowder was the vice president and technical director of the Educational Science Division of the US Industries. These two types of learning programming differed in how they conceived the role of repetition. Both emphasized the effectiveness of repeated messages and questions for the lessons to be learned. Skinner's *linear program*, however, focused itself on small details of the questions, on the answers phrased by the students, and on the progress of learning, advancing in tiny steps—all in the spirit of the operant conditioning approach to learning. In contrast, Crowder's *branching programming* emphasized the explicit effect of mistakes. They would lead the student into enhanced repetitive routines and would simultaneously—by a more strongly branching algorithm architecture—guarantee an "intrinsic" (Fry 1963, 5) adaptation of the student's individual level of knowledge (Vogt 1966, 40–43). Based more strongly

**140** on Pressey's work, Crowder favored multiple-choice tests with immediate feedback. This made him the target of criticism stating that, ultimately, his method came close to mere "test and quiz questions" (Deutsch 1964, 44). Eventually, the Skinner school of thought prevailed:

> [Skinner] had produced more than a machine; he had developed an educational technology that promoted a new approach to teaching … The boom in teaching machines was underway in the early 1960s, and most of the devices were based on Skinner's theory of learning. (Benjamin 1988, 709)

#### **Booms**

Skinner's bell-ringing teaching machine, and the *rediscovery* of Pressey's work thus marked the beginning of the boom in teaching machines (Niemiec and Walberg 1989, 264). In 1962, US educational psychologist Robert Glaser introduced the term "instructional system," (Glaser 1962, 1–30) focusing on teaching machines and programmed learning. In 1965, psychologist and educator Robert Gagné published his book *The Conditions of Learning* ([1965] 1970), which quickly became a great success, constituting a paradigmatic work on teaching theory, and sparking broad attention to instructional design. In 1962, Charles I. Foltz published *The World of Teaching Machines: Programmed Learning and Self-Instructional Devices*. The book is a fundamental work within the teaching machines movement; however, according to the introduction, Foltz opted for a wait-and-see attitude and tried not to be too enthusiastic when talking about the matter. All the same, by the mid-1960s a proper market had developed: Foltz estimated that by around 1965 there were approximately 40 to 50 manufacturers of learning devices, plus another 20 companies publishing textbooks and syllabi for them. Accordingly, he calculated that the expected turnover for the following 10 years in this sector would amount to US\$100 million (Foltz 1965, 47). In parallel, a research funding program sponsored by both state-run and private institutions—e.g., the Carnegie Corporation, Ford **141** Foundation—was launched, aiming to support fundamental research at universities on this matter (Czemper and Boswau 1965, 88).

As the ambitions of the parties involved increasingly moved towards slide projection, film-supported (Lumsdaine and May 1958), and computer-based interpretation of the teaching methodology, during the second phase of the short teaching machine boom, there was a rise in the cooperation between universities and hardware manufacturers within the computer industry. These cooperative programs were usually grouped under the term of "computer-assisted instruction," or other programs promoted by the US government, such as the Center for Programmed Instruction run by the US Department of Education (Molnar 1990, 80–83; Niemiec and Walberg 1989). In this context, the Minnesota Educational Computing Consortium (MECC) is worth mentioning. Along with Total Information for Education Systems, founded by Dale LaFrenz and others in 1968, the MECC established a computer network that used modems to connect suburban schools in the greater Minneapolis area to mainframe computers. The network was used to provide learning software and automated learning assistant systems to schoolchildren for decades. One of the most successful and renowned MECC learning programs was *The Oregon Trail* from 1972. A simulation of the Western US during the 1840s, it was for many US citizens one of their first contacts with computer games, and it is considered a *classic* video game to this day (Google, n.d.).

However, we do not want to focus the discussion here on the expansion of teaching machines to think tanks, the emerging computer industry, or the general debate on automation and control. Rather, we are interested in the debate teaching machines triggered in Germany, and the specific scenario this produced.

One of the key institutions in the development of teaching machines and information psychology in West Germany was **142** the Institute for Cybernetics (IfC). Established at the University of Pedagogics in Berlin (*Pädagogische Hochschule zu Berlin*) on August 28, 1964 and headed by Helmar Frank, this was the first institute at a German university to deal with cybernetic pedagogy (Lehnert 1969, 3). "Accordingly, one of the primary goals of cybernetic pedagogy is to objectify certain intellectual achievements performed by educators, i.e., to delegate them to cybernetic machines developed for this specific purpose" (Lehnert 1969, 3).<sup>4</sup> Although the institute was linked to the Association for Programmed Instruction (*Gesellschaft für Programmierte Instruktion*, GPI), it insisted on developing, at least to a certain extent, its own approach to cybernetics. The GPI, on the other hand, was a scientific umbrella association that

> brought together researchers and practitioners from the fields of programmed instruction, language laboratories, and remote transmission didactics (e.g., educational TV). The association deserves particular credit for succeeding in attracting scientists from all four possible fields of programmed instruction. Whether they represent[ed] the liberal arts (Prof. Zielinski), cybernetics (Prof. H. Frank; Prof. K. Weltner), empirical pragmatism or behaviorism (Prof. W. Correll) the GPI not only respect[ed] but welcome[d] their views. (Heyder 1965)

The differences between the Berlin Institute for Cybernetics and the GPI may illustrate how cybernetic pedagogy differentiated itself from the range of operational approaches to programmed instruction and the discourse on teaching machines. Nonetheless, both institutions—along with the Center for Educational Technology (*Bildungstechnologisches Zentrum*) in Wiesbaden broke ground in the development of teaching machines and programmed instruction in Germany. The fact that the IfC had cooperated with local computer companies and was equipped with its own computer center—initially sponsored by Siemens

through an S-303-P system, and later by Nixdorf with four N-820 **143** computers (Lehnert 1969, 4)—offers a particularly relevant thread.

# **Helmar Frank and the Institute for Cybernetics**

Cybernetician Helmar Frank turned to information aesthetics early on, which later became the theoretical foundation of his cybernetic pedagogy. Writing his doctoral thesis on this subject in Stuttgart in the late 1950s (Frank 1959), he was part of the scene where Max Bense transferred information aesthetics to practical and theoretical computer art projects. After completing his doctorate, Frank initially investigated teaching machines in Karlsruhe as part of Karl Steinbuch's group, before being appointed professor for information science at the University of Pedagogics in Berlin in 1963. There, he transferred his theoretical preliminary considerations on information aesthetics to pedagogy, defining his future field of work in the book *Cybernetic Foundations of Pedagogics* (*Kybernetische Grundlagen der Pädagogik*) from 1962. In the late 1960s, Frank moved from Berlin to Paderborn, where he led the recently-established Research and Development Center for Objectified Educational Methods (*Forschungs- und Entwicklungszentrum für objektivierte Lehr- und Lernverfahren*, FEoLL), and founded the Institute for Cybernetics. In Paderborn, Frank also pursued a political strategy, as West Germany planned to establish an IT center there in cooperation with the computer manufacturer Nixdorf and the new local university.

Accordingly, Frank and his colleagues focused their work on materializing his initial theoretical considerations, which was done with a double emphasis: "*constructive* and *empirical* work to produce computer-related material as a school subject" (Frank and Meyer 1972, 23).5 For this, Frank decided to describe all

**144** processes as cybernetic feedback operations, thus setting the basis both for didactics in general, as well as for his *Rechnerkunde* (Computer Science)—the very first example of computer science teaching in Germany: "the computer is introduced on two levels of observation: first as an educational object that the reader will *become familiar* with, and secondly as an educational object that he will learn to *teach to*" (Frank and Meyer 1972, 23). This learning process takes place as a dialog between humans and machines, during which each learns from the other. This, however, meant that one must have a precise understanding of the machine in order to be taught by it. That is why Frank begins his *Rechnerkunde* with a section on what is today known as computer engineering, before moving onto practical computer science. This resulted in an inductive learning process:

> From a didactic point of view, using problem-oriented programming languages (Algol, Fortran, Cobol, etc.) to introduce students to data processing is the incorrect approach, as they cloud, if not completely obstruct, our view of the objectification conducted by the computer. When learners have attempted to program a computer using machine code or machine-oriented code, and have thus familiarized themselves with the computer's functionality, they do not need (and at the same time will not have the necessary knowledge) to learn higher programming languages. (Frank and Meyer 1972, 21)

Nevertheless, a central aspect of Frank's cybernetic pedagogy is that his *Rechnerkunde* does not constitute an end by itself. Rather, it gives learners an entry point to the study of cybernetics. Frank understood computers as models that could help in exemplifying cybernetic principles, calling them, accordingly, MORE; a German abbreviation for model computer (*Modell-Rechner*). Before outlining these model machines, a brief overview of the MORE program and its predecessors is required.

# **BAKKALAUREUS <sup>145</sup>**

BAKKALAUREUS is the acronym for "Modular System of Combinable Cybernetic Machines which Performs Autonomous and Computer-Supported Examination and Educational Work" (*Baukastensystem aus kombinierbaren kybernetischen Automaten leistet autonom und rechnerunterstützt Examinier- und Schulungsarbeit*) (Frank 1969, 45). The devices using this modular system were developed in Berlin and Paderborn between 1964 and 1973. We argue that their rising complexity simultaneously offers insights into the development of German teaching machines, and shows the successive and increasing influence that digital and computer technology had in this field in Germany.

[Fig. 2] BAKKALAUREUS program at the 1973 Didacta trade fair for the education sector. Source: authors' personal archive.

Introduced in 1970, the ETS/e system was a typewriter with a modified keyboard. A Nixdorf N-820 computer could lock or release the keys via remote control, meaning that the ETS/e could be used for multiple-choice questions. Most early teachinglearning devices within the BAKKALAUREUS program sought to technically support multiple-choice questions (Frank 1975, 89). Although true interactivity between these devices and users had been the main goal of cybernetic didactics since the outset, it was not realized until digital computers were integrated.

[Fig. 3] Schematic illustration of the model computer (MORE). Source: authors' personal archive.

The GEROMAT system, funded by the Volkswagen Foundation and developed in Berlin, was realized in four iterations between 1964 and 1970, and was also part of the BAKKALAUREUS program (Thomas 2006, 42–44). The system had a multimedia supplement for language laboratories with the following components:

The Nixdorf N-820 computer was, however, used again for the ITERATOR system; an emulator of a model computer for 30 learners. Similarly, the MORE (fig. 3) was initially only a *concept* computer—a model computer in both senses of the word. The archive of the Institute for Cybernetics contains comprehensive

**146**

**147**

[Fig. 4] Excerpt from the MORE emulator program in the N-820 assembler. Source: Archive of the Institute for Cybernetics. Courtesy of the Deutsches Technikmuseum Berlin.

materials on the MORE simulation; among them, a 100-page printout of the N-820's assembler listings (fig. 4) which provides information on the computer's working principles. However, a mere emulation of the MORE would have contradicted Frank's own demands; namely, that discovering a "computer's functionality" via programming entailed that it would not be the computer which would be programmed. Consequently, two of Frank's collaborators, Dr. Sommer and Dr. Closhen, built an actual MORE computer, which they finished in the spring of 1970 (Frank and Lehnert 1973, 25). Ingeborg Meyer, a female student of pedagogics who worked at the IfC, used that computer as the basis to design a practical computer science course. Reports on *Rechnerkunde* courses using the MORE can be found until the mid-1970s. They include field reports written by Dr. Simons (1973 and 1975); a syllabus titled *Rechnerkunde Course A/B Using the MORE,* developed by G. Lobin (1973); worksheets for students and **148** evaluation forms of Meyer's *Rechnerkunde Course C* (n.d.); and the book *Rechnerkunde* itself, written by Meyer and Frank.

# **Technical-Didactic Reductions with the MORE**

The prototype of a MORE computer used for this chapter6—part of the IfC archive—is a type of machine known as a TTL computer. There, the system's CPU is not a single component, but a "dissolved" set of individual logic modules (TTL) of the 74 series. These are integrated circuits containing several digital logic gates, which have been repeatedly used in circuit implementations since the 1960s (Texas Instruments 1972). Given that the types of integrated circuits are easily identifiable—the date of manufacture was printed on them—it is possible to narrow down the date on which this MORE prototype was created: the oldest component is from 1973, meaning the prototype could not have been built before this date.

The MORE was designed as a binary 10-bit computer in accordance with the Von Neumann architecture: 7 bits were used for addressing—resulting in a maximum addressable storage of 128 bytes—and 3 bits for instructions—which allowed up to eight instructions. The computer offered two clock speeds: 2 and 4 hertz. It was programmed using switches and binary machine code, and the data output was represented, as binary values, with LED lights. The MORE was initially programmed on paper. Programs were written as mnemonic code, which were then manually translated into machine code—chains of zeros and ones. Thus, programmers obtained detailed knowledge on the construction of machine instructions.

6 The MORE was studied through a series of workshops and research projects led by Stefan Höltgen and Marius Groth at the Signal Lab of the Institute of Media Science of Humboldt-Universität zu Berlin between 2017 and 2019.

[Fig. 5] MORE punch-card reader. Source: authors' personal archive.

As its main memory, the MORE has a punch card reader through which programs and data could be loaded but not stored (fig. 5). Despite having only eight *opcodes*—instruction machine codes the MORE has every function of a Turing-complete code; that is, the computer could be programmed for any task, and could thus be used to this day as a *didactically-reduced* model computer equivalent to any kind of Turing-complete digital computer according to the Von Neumann architecture.

## **Rechnerkunde**

The MORE's role is expanded in the *Rechnerkunde* pedagogics. In their book, Frank and Meyer present five steps, all using the MORE, to "scientifically examine the phenomenon of computers" (Texas Instruments 1972, 13):

[Fig. 6] MORE brochure published by ELFE (front). Source: authors' personal archive.

University-level computer science courses usually cover steps two and three, but according to Frank and Meyer, their *Rechnerkunde* already dealt with all five steps at a high-school level. This was possible thanks to the didactic-technical reduction implemented in their computer and its simple design, which was intended to be mass produced after a trial period. The MORE would be built by the Berlin-based teaching machines company ELFE (fig. 6). However, beyond brochures, we have been unable to find substantial information about this company—except for the advertisement of the EMF 2000 model computer (a wall-installed

demonstration machine), and the EMT 2000 (a small device for **151** students), as well as templates of the latter machine, which could actually be used for programming exercises.

*Rechnerkunde* also describes the MORE's construction, its functionality, and programming, and elaborates on the computer's educational scope. According to Frank and Meyer, *Rechnerkunde* classes should use six main questions as guidelines:

These six questions structured the *Rechnerkunde* didactics, which Frank formally explained thus: I, M, P, O, and S are condition fields, and E is the decision field in which didactic decisions can be made. Hence, for a given teaching method, the combination of these variables formed the D function, being expressed by Frank, for example, as DIMPOSMORE or D32MORE—where 32 designates didactic function number 32 in a set of 63 possible ways to distribute the six educational variables across the two subsets of condition and decision fields. This formal description is also at the basis of the *Rechnerkunde* teaching program (Frank and Lehnert

7 This question is not just interesting because it hints at the Shannon-Weaver model of communication, but also because the IfC used it to justify the use of Esperanto in its teaching, arguing that by employing a new language to learn about other subject matters, students would be free from the interference of their mother tongues (metaphors, double meanings, etc.) during the learning process.

	- Elementary introduction to digital message processing (Frank)
	- Binary code
	- Dual arithmetic
	- Logical functions and Boolean algebra
	- Adders
	- Computer architecture
	- External program control (state machine)
	- Internal program control (Turing machine)
	- Transfer to current commercial computers
	- Teaching methodology approach to Rechnerkunde (Meyer)

Lessons should include the MORE as quickly as possible to help exemplify theoretical teaching in practice. Furthermore, students should incorporate the lessons learned into possible applications with the MORE, through which they would learn how to code by trial and error.

# **Single-Board Teaching Computers**

In the late 1960s and early 1970s, the teaching machines of the Institute for Cybernetics represented promising technologies. At the 1973 Didacta trade fair (fig. 2), the MORE and the BAKKALAUREUS program were in effect presented as the teaching technologies of the future—not just for the field of computer science. Moreover, according to our findings both projects were implemented at vocational schools and high schools in and around Paderborn and Berlin. When microprocessor technology began to dominate the market from the mid-1970s on, computers became so affordable that schools were able to purchase them in large quantities, and technological progress itself "canceled" the Institute for Cybernetics' systems:

The workstation computer with the appropriate equipment actually appears to be a universal teaching machine. Its current possibilities exceed those of the former teaching

[Fig. 7] Signetics Instructor 50. Source: authors' personal archive.

automats by far. Teaching machines benefit from all the ergonomic features of the workstation computers (graphic user interfaces, voice input and output, high-resolution graphic screens, etc.). (Zuther 1996, 101)

The MORE system, *which* from a didactic perspective was open, was then gradually replaced by *closed* microcomputers which brought about an important shift in *Rechnerkunde*. Basically, it was turned inside-out: computer science didactics has since then departed from machine-centric and bottom-up approaches, favoring problem-oriented teaching, which take the user interface as their starting point (Höltgen 2016, 141–51). However, both the MORE's architecture and textbooks on single-board computers—e.g., SEL-Z80 Trainer—show that the didactic and technical principles of cybernetic pedagogy and the MORE are by no means outdated. Today, the technical principles of that

**154** small teaching computer can still be found in the form of affordable systems, such as Arduino, Calliope, and the Raspberry Pi, and small build-it-yourself TTL computers such as the Gigatron or the Instructor 50 (fig. 7). The fact that the incremental blackboxing of computers—through miniaturization, networking, and virtualization on the user's side, and vertical technological differentiation on the manufacturer's side—had revived old forms of curiosity (Höltgen 2022, 204), can be considered, we contend, a comeback of cybernetic pedagogy. It is a curiosity that reviving *Rechnerkunde* and its epistemological approach is nowadays expressed in the hacking, making, and repairing of computers.

## **Conclusion**

This short history of teaching machines and their shift from the USA to West Germany shows how distinct their underlying discourse became. Starting with a simple conceptualization of teaching mechanisms as a form of operant conditioning, an understanding of the learning process as a type of self-monitoring feedback loop quickly developed. This in turn led to an increasing reassessment of *performance* as the goal of teaching machines. In Germany, the latent *cybernetization* of these systems yielded a coupling between specialized educational content and teaching machines, giving birth to a sort of meta-system where both form and content became congruent. So, what caused the failure of this brief boom in teaching machines? Pointing to the fact that the brilliant and successful educational projects their creators anticipated had failed to materialize seems to us to be too narrow a viewpoint. We think that addressing the slightly more abstract issues teaching machines produced—e.g., their "control-political" effects—is a more productive strategy.

Even during the early phase of teaching machines in the US, it became clear that there were *frictions* between reality and the extreme functionality of the methods employed. One major point of criticism addressed behaviorism's understanding of learning,

and thus its associated conceptualization of humanity—which did **155** not view learning as a subjective process. Instead, behaviorism viewed the subjects being taught—in the context of a stimulusresponse *external governing*—as an overly-individual, manageable component of the process. This reduced subjects to *learning objects* that were no longer subject to their own will. Moreover, a debate emerged around the frictions between teaching programs and machines: the oft-cited phrase "the program is everything, the learning machine nothing," summarizes the criticism of socalled "page-turning machines" (Deutsch 1964, 39). This appraisal considered that using teaching machines in complex learning situations—e.g., industrial vocational training—would make students feel *patronized* by machines, resulting in a tendency to disobey them (Schirm 1964, 132). In this respect, teaching machines may be seen as the systemic reaction to a stage of crisis—i.e., lack of teachers, new challenges in education, the Sputnik crisis—at the core of which lie the consequences of a politics of control (Schestakow 1965; Vogt 1966).8

In Germany, the development of teaching machines proved less crisis-driven and more a consequence of the increasing role of science in governance from the 1940s on. "Regulate what can be regulated; ensure anything that cannot be regulated becomes regulable" (Schmidt 1941, 81). In line with the notion of predictability, which was a topic of discussion in the UK at around the same time, teaching machines seemed to be a sort of utopian answer to the question of whether teaching processes could be fully automated. This utopian promise was finally fulfilled when teaching machines were replaced by *other* machines—Turing machines. Microcomputers entered schools in the second half of the 1970s, replacing the BAKKALAUREUS machines and continuing the MORE's legacy. The fact that this had introduced new technological obstacles that in turn swung the pendulum

8 The fact that learning machines were developed and used in socialist countries is proof that this crisis of control was not just a Western problem (Schestakow 1965).

**156** from *the real* to *the symbolic*—from hardware to programming languages—moved the discourse of computer science to other teaching methods.

To some, teaching machines may seem antiquated, not sufficiently complex or effective, and even almost naive. But what distinguishes teaching machines from today's software-based learning projects? Language learning tools such as Duolingo, the brief boom in open content for university lectures, and classroom tools, all essentially use the same mechanisms as those present in the realm of teaching machines. Drawing a line that goes from the *teaching machines* of the 1950s, passes through the selfinstructional learning model of the 1960s, and arrives at today's debates on gamification seems to be the logical description of the evolution of the field. Nonetheless, the different apparatus and architecture of semi-automated learning systems appear to have developed a life of their own, beyond their intended action-rational functionality. The learning process that uses *ludic methods* and self-regulating features becomes a process that seems constantly threatened by "*the game*." Skinner had already talked about a *pinball-machine effect*, observing that, beyond the programmed educational content, the learning machine itself interrupts the student's gaming operation. Similar to pinball machines, there is a risk, Skinner argued, of interactions with the learning machine that challenge the gaming operation to such an extent that the student's will to beat the machine—i.e., winning the game—could become more dominant than the learning process itself. "The negative aspect of the innovative effect … is that most children are so highly motivated that they would rather conquer or cheat the machine in play than learn from it" (Foltz 1965, 47).

In a word, insights on the connection between learning subjects and teaching machines, on the technology used for this purpose, and on the epistemology of cybernetics can be derived from these pages. In this sense, the reward which learning subjects receive from teaching machines would not merely be the

acquisition of knowledge, but also an ostensible experience of **157** self-empowerment and self-efficacy. At the core of the project on teaching machines there is a (rather naive) image of learning subjects as individuals who are not controlled by superordinate, teleological logic—or processed by a learning algorithm. Instead, they would use their own intuitive capacity to act, thus developing learning results intuitively based on pre-structured processes. Regarding the discourse on teaching machines, however, it would make more sense to understand acting subjects as connected subjects; as entities that can be addressed through the educational tool of the game. This self-determined learning is twice as effective because these game-like processes create an experience within which training and development reach a high level of effectiveness, given that the subjects in this context are self-motivated, adapting themself voluntarily—and because their performance becomes measurable.

Nonetheless, the gamification of learning has been fruitful, although outside the regulations of syllabi. In hacker spaces, coding dojos, and repair cafés, the old black boxes called computers are repeatedly transformed into a new subject matter, and are learned through the cybernetic-autodidactic methods of trial and error, and learning by doing. In an effort to acquire the knowledge hidden within the technology, a subversive epistemology started spreading in the late 1950s, leading to some of the findings discussed in this chapter. In that vein, before the MORE documentation was found in the uncatalogued estate of the IfC, the device itself was scrutinized (see footnote 6). Consequently, by teaching about and through the device, fully in the spirit of Frank's *Rechnerkunde*, the experimenters learned from the device, deriving the didactics behind it.

In the context of this book, therefore, teaching machines provide a self-evident insight into the question of *frictions*. On the one hand, they provided an approach which understood that these systems would amount to the pure implementation of previously devised theories and models—the one embodied in Skinner's

**158** work. On the other, they provided a perspective that found, at the very technological depths of these machines, lessons that would *inform* the teaching-learning process. In brief, these views allow one to trace two essentially frictional agencies: one aiming at using teaching machines as the instruments for the deployment of a program; the other letting the program be the product of technological processes itself. It may thus be argued that the first approach, always at odds with the episteme machines produced, played a relevant role in the decline of teaching machines. However, such an argument does not acknowledge, for example, that Frank's undertaking—representative of the second perspective—was also affected by not understanding the modes and rhythms by which the episteme of machines unfolds. Does the battle between TTL computers and microprocessors mentioned above not speak to this? Perhaps the *frictions-*motivated method of analysis allows us to verify that one of the main insights we can get from the age of cybernetics is that, at the bottom of complex technological systems, a new sort of knowledge is being developed: one that tends to escape the control of humans, giving way, for example, to the *everlasting life* of teaching machines, now concretized in gamification systems or open microcomputer sets that continue to inform our modes of learning and knowledge.

#### **References**

**160** Nohr, Rolf F. 2019. *Unternehmensplanspiele 1955–1975: Die Herstellung unternehmerischer Rationalität im Spiel. Unter Mitarbeit von Tobias Conradi, Tim Glaser, Kerstin Hoffmann und Theo Röhle*. Münster: Lit Verlag.

Norberg, Arthur L. 2005. *Computers and Commerce: A Study of Technology and Management at Eckert-Mauchly Computer Company, Engineering Research Associates, and Remington Rand, 1946–1957*. Cambridge: MIT Press.

Pressey, Sidney L. 1926. "A Simple Apparatus which Gives Tests and Scores—and Teaches." *School and Society* 23 (586): 668–72.

Schestakow, Aleksandr Ivanovič, ed. 1965. *Programmiertes Lernen und Lehrmaschinen*. Berlin: Berlin Verlag.