The Great Automaton

Mario Laul
12 min readDec 9, 2020


Automation and Progress

The history of technology can be viewed as the history of automation. A quote from more than a century ago by the philosopher and mathematician Alfred North Whitehead sums up nicely the connection between automation and progress: “Civilization advances by extending the number of important operations which we can perform without thinking of them.” [1] In a similar vein, Friedrich Georg Jünger, a controversial conservative critic of modernity, highlighted the trend towards automation as the essence of technological progress. In 1946, Jünger [2] wrote:

“[W]hen we observe the work processes of technology, the striking feature is the growing automatism to which they become subjected. Technological progress is synonymous with an increase in all kinds of automations. The entire work process, up to the finished product, is performed by automatic machinery and with repetitious mechanical uniformity; the entire factory becomes one single automaton. […] And just as the work processes which result in the end product are performed by an automaton, so the end product itself is very often an automaton designed for repetitious mechanical work processes. […]

We are surrounded by an automatism towards which all branches of technology are developing. The greater part of our production tools work automatically. Our transport is automatized in the form of the ubiquitous railways, motor ships, motor cars, airplanes, elevators, and so on. Our light, water, and heating systems function automatically. With our automatic weapons it is the same. There are vending and food-serving automatons, radio and movie automatons, all of them designed for the task of repetitious performance with mechanical uniformity, just as a phonograph record repeats the same piece over and over. It is exactly this automatism which gives its peculiar stamp to our civilization and sets it apart from the techniques of other eras. It is automatism by which our technology achieves its growing perfection. Its signature is the independent and unchanging repetitious operation of its apparatus.“

In 1971, the first commercially available microprocessor on a single small chip — the Intel 4004 — got the nascent Information and Communications Technology (ICT) Revolution off the ground. Neither Whitehead nor Jünger would have been surprised by what happened next: as computational automata, computers have not only replaced the need for direct human involvement in many situations, but have enabled operations that far exceed individual human capacities.

Are we living in a digital [3] automation dreamland? No. We’re not even close. Many digital technologies are still in their early stages of development, not deployed at scale, or not sufficiently interconnected. But the general trend is undeniable: the ICT Revolution has ushered in an entirely new era in the all-encompassing drive to automate.

Automation as Freedom and Control

Manual work plays an important role in personal learning, development, and satisfaction. There is dignity and creativity in work done by hand, and considerable economic and social value can be created through skillful human effort. But a lot of manual labor is also inefficient and socially unappreciated. The dirtiest, most dangerous, and demanding jobs in particular are often reserved for groups that are marginalized — manual work has long been associated with social inequality.

Historically, the most effective method for reducing the physical burdens on humans has been automation through mechanization. There is something deeply satisfying about seeing a grueling task automated. Automation means freedom from physical drudgery, freedom to provide for more, freedom to direct human attention to other, potentially more sophisticated and gratifying pursuits. As such, it is a major, if not the most important, contributor to material wealth and well-being.

Are there negative externalities to technological progress through automation? Certainly. The mass production and consumption enabled by automation puts dangerous pressures on the natural environment, while technologies such as weapons of mass destruction and Artificial Intelligence (AI) pose an existential threat to all life on Earth. Innovation can turn a large number of paid jobs obsolete, dislocating entire industries quicker than those most affected can adapt. Even though past doomsday scenarios about humans running out of work as machines ‘take over’ have obviously been overstated, the process of changing social institutions in response to technological innovation has rarely been pleasant or easy.

But perhaps more concerning than the prospect of material wealth without paid work — something that could well turn out to be more of a blessing than a problem — is the effect of automation on the relationship between individuals and institutions. Technology is not merely a tool for making lives easier, it is also a mechanism for social control and a major organizing force of society. This has been true throughout the ages — think of the relationship between farming and political organization, weapons and physical coercion, or the printing press and propaganda — but it has become particularly evident in the context of the ICT Revolution. As highlighted by Alexander Galloway [4] in 2004 — long before the more negative aspects of global web platforms became a popular concern — the paradox of the Internet is that it is a technology built on the ideals of openness, inclusion and flexibility, while simultaneously being the most highly controlled and controlling form of media ever invented.

Automation and Human Action

The effects of digital automation on human behavior are part of a more general problem known as technological determinism: to what degree do material and technological conditions generate cultural practice? Or to put it more provocatively: to what degree are humans themselves an object of automation? [5]

One of the most fundamental concepts for describing natural processes is causality, or relations of cause and effect. Applying it to human action means asking the question: what led to a particular decision or activity? The relationship between an individual’s consciousness and environment is so complex that a complete description of all the relevant mechanisms is unrealistic. But generally, the immediate answer to why an action occurred refers to some underlying process, preceding event, or informational signal. For example, a particular choice of trajectory in moving through space may be partially determined by a number of different causes. Some may be internal to the actor, such as hunger or other biological impulses; some may stem from the natural environment, such as temperature or obstacles in terrain; and some may be social in their origin, such as paved roads or professional obligations. Technology belongs to the third category and its role in guiding both individual action and social evolution is growing.

The importance of communication technologies in imposing and reproducing worldviews and habits of behavior is a case in point. While all forms of mass media have been used as such, Internet-connected personal computers and smartphones, combined with social media, data mining, and predictive analytics, have made ICT-based communication a particularly powerful tool for manipulation. It is now possible to disseminate information — either purposely or as a byproduct of some semi-automated background process — at speeds capable of triggering coordinated action in many parts of the world simultaneously. Algorithmic trading on financial markets can contribute to macroeconomic trends that lead to major shifts in policy; search engines can personalize results to reinforce specific moral or political views; social media platforms can optimize news feeds to trigger consumer decisions, or perhaps particular behaviors in response to a global pandemic — these are just some examples of how algorithmic curation of information can influence human thought and action at scale.

Surgically targeted but scalable automation of digital content production — text, sound, video, and increasingly virtual reality — warrants a special emphasis. In the past, creating and organizing content was a manual, time-consuming process. That has been changing recently. Outright automation has been easiest in the case of previously standardized content such as weather predictions, sporting results, and financial reporting. But machine intelligence is now also applied to generating news stories, educational materials, fiction, essays, email replies, translations, and more. It is certainly not unreasonable to imagine a world in which the vast majority of digital content are automatically created and disseminated according to an arbitrary set of rules and preferences, otherwise known as ideology. This is functionally equivalent to educational and mass media systems of the past. What’s different is the unprecedented scale, speed, and precision at which it can be done with ICT.

There are some important caveats to this emphasis on the role of digital automation in driving human action. First, the autonomy of technology should not be overstated. As things stand, human beings are still deeply involved in the design, engineering, and maintenance of most digital systems. Despite increasing automation and the co-evolutionary dynamic between technology and humans, there is no such thing as fully autonomous technology. Second, much of the global population is still in the process of gaining access to digital innovations. More widespread adoption is only a matter of time but, as of today, the societal effects of ICT vary greatly between different geographies. And third, despite a growing number of everyday experiences being mediated by computers, it is still rather easy to remind ourselves that human existence is not necessarily dependent on digital technology — all that’s required is some physical and mental distance between ourselves and our devices. But creating that distance is going to get increasingly difficult as our dependence on digital institutions grows.

Automation and Decentralization

An important recent development in the evolution of digital automation is the emergence of decentralized blockchain and smart contract networks that enable Internet-native forms of economic organization, signaling the deployment phase of the ICT Revolution. [6]

Alongside centrally controlled public and private web platforms, the growth of blockchain networks will strengthen the bureaucratic [7] structure and organization of society. But instead of human administrators, the mundane rule-following in handling information and facilitating transactions connected to that information will increasingly be done by computers. As more administrative functions become digitized and automated, the proverbial middlemen get replaced by globally distributed middlemachines.

Public blockchain networks are built on the ideological design principles of decentralization, permissionless access, tamper- and censorship-resistance, and individual control over personal information and assets. As a result, blockchain-based systems are difficult to unilaterally change or regulate, a feature encapsulated in the twin concepts of sovereign networks and ‘autonomous’ software. The essential idea is that decentralized networks and applications could represent an alternative to institutional functions currently dominated by governments and private corporations by delivering digital services with less reliance on centralized operators, while providing end-users with improved levels of transparency, security, and autonomy.

Much more likely than the wholesale replacement of governments and corporations with blockchain networks, is their growing integration and convergence with the rest of the digital infrastructure. The final outcome of this is impossible to predict but it will definitely result in more automation and fewer options to censor or otherwise restrict the bureaucratic machinery of recordkeeping. In an optimistic scenario, the resulting system will massively improve global administrative efficiency, while enabling new and universal forms of economic empowerment, inclusion, and autonomy. In a more pessimistic scenario, decentralized networks will simply reproduce known institutional failures and amplify existing inequalities, potentially leading to increased social instability. Sooner or later, this would underscore the value of institutional checks and balances, including public accountability. Whether such concepts fundamental to modern institutions are compatible with public blockchain networks and decentralized applications remains to be seen.

Conclusion: The Political Economy of Automation

Automation is the outcome of humanity’s socially determined impulse to build and experiment, and a systemic tendency of any civilization geared towards material growth through technological innovation. Automation has two main consequences. On the one hand, by amplifying the productive capabilities of society, it expands the built environment, thereby increasing material convenience and well-being. As such, automation is a sign of economic inventiveness and progress. On the other hand, automation raises a number of difficult economic, social, and philosophical challenges. Addressing these challenges is the core purpose of the political economy of automation, which can broadly be described as dealing with three sets of issues:

(I) Unemployment and wealth inequality

Will automation lead to widespread technological unemployment? If so, is dealing with the short- to mid-term economic, social, and psychological aftermath a matter of personal responsibility, or should governments and private firms provide direct support for those most affected? Should this include the expansion of social guarantees, including the introduction of a Universal Basic Income (UBI)? What might be the second- and third-order effects of such a policy? Will growing automation combined with traditional capitalist ownership models exacerbate wealth inequality? If so, what can be done about it?

(II) Personal freedom and social control

What are the potential downsides of automation in areas such as law enforcement, military, surveillance, and behavioral nudging? What are the legal and privacy implications of the growing role of machines in organizing human life? By increasing society’s dependence on technological systems understood and controlled by a small minority, is automation a threat to personal freedoms and democracy? How do AI or novel administrative and institutional technologies such as blockchain networks play into all this? Does the combination of decentralization and autonomous machines or software dangerously undermine the ability of humans to intervene in the operation of large-scale technological systems? If so, what can be done about it without undermining the economic benefits of innovation?

(III) Social ethics and the long-term future of humanity

What are the ethical implications of automation? Is it practically feasible to make the process of steering technological development more inclusive? What if there’s a fundamental conflict between different points of view regarding the purpose and preferred direction of innovation? Who, under what circumstances, should have the authority to restrict experimentation in a particular area? How to determine the appropriate limits of personal responsibility and liability for the societal effects of automation? What role will automation play in the long-term future of civilization, especially when combined with technologies that could pose an existential threat to humanity, such as AI or weapons of mass destruction?

It would be naïve to think that all these questions can be definitively answered today, once and for all. Instead, dealing with the effects of technological progress will always remain a process of trial and error under conditions shaped by countless individual decisions by scientists, engineers, entrepreneurs, investors, consumers, and policymakers. If governed responsibly for the well-being of all, the Great Automaton in the making has a lot of potential for good. But realizing that potential is a constantly evolving challenge, and should not be taken as given.


[1] Whitehead, A. N. (1948). An Introduction to Mathematics (p. 42). Oxford University Press. (Originally published in 1911.)

[2] Jünger, F. G. (1956). The Failure of Technology: Perfection Without Purpose (pp. 30–31). H. Regnery. (Originally published in German in 1946.)

[3] Any information organized in the form of discrete symbols or digits can be considered ‘digital’, including alphabets, DNA genetic code, and signaling systems such as Morse code. In the context of this text, however, the words ‘digitization’ and ‘digital’ refer specifically to the growing use of digital electronics and computers to store and process data, which started in the second half of the 20th century and became known as the Digital Revolution, or alternatively, the Information and Communications Technology (ICT) Revolution.

[4] Galloway, A. R. (2004). Protocol: How Control Exists After Decentralization (p. 142, 243). MIT Press. (Credit to Jesse Walden who first brought this book to my attention.)

[5] In January 2019, The Guardian published an interview (available here) with Shoshana Zuboff, a social psychologist and technology scholar whose work popularized the term ‘surveillance capitalism’ for describing the business model typical of some of the largest Internet companies in the world, which centers around the commodification of personal data. The title of the interview contains a rather thought-provoking phrase for thinking about the relationship between digital technology and human action: ‘The goal is to automate us’. The same idea applies to institutions, which can be thought of as manual equivalents to rules-based automation: following the basic logic of ‘if A, then B’, institutions prescribe (and ‘automate’) modes of human thought and behavior.

[6] In Carlota Perez’s theory of techno-economic paradigm shifts, modern economic history is divided into five surges of development. Each surge spans approximately 50–60 years and is divided into four distinct phases. The first two phases, called Irruption and Frenzy, represent the Installation period of the new techno-economic paradigm. During this period (1970s to early 2000s in the case of the ICT Revolution), the new paradigm and its key industries are still forming (which increases the role of speculative financial capital), while individualism combined with lagging regulation contribute to a highly uneven distribution of gains from innovation. The latter two phases, called Synergy and Maturity, constitute the deployment stage. According to the model, this is when production capital tends to dominate (i.e. non-financial firms engaged in the production of real goods and services), leading industries consolidate, and ideally, a more equitable distribution of economic gains is achieved through progressive institutional reform and a revised social contract. As the principles and technologies of the new paradigm become standard throughout the economy, the organizational and institutional structure of society changes: what used to be novel and disruptive becomes the new normal, and a source of inertia pushing against subsequent innovation. In this framework, both centralized web platforms and blockchain networks can be seen as ICT-native administrative and institutional structures and part of the emerging ‘new normal’ for organizing society, especially as it relates to control over information — the defining feature of all bureaucratic institutions. To learn more about the theory of techno-economic paradigm shifts, see Perez, C. (2003). Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages. Edward Elgar Publishing. For an interpretation of how blockchain-related innovation might fit into Perez’s model, see here.

[7] For a description of blockchain networks as ideal-typical bureaucracies, see here.