April 20, 2024

The Master’s Eye: A Social History of Artificial Intelligence – Book Review

pasquinelli Master’s Eye provides a materialist analysis of AI and technology, which Kevin Crane considers an excellent antidote to all the nonsense and hype that is said about AI.

Any of you who have tried to follow the twists and turns of artificial intelligence (AI) in 2023 will probably agree that it has been a grueling exercise. The year began with high-profile public presentations of big language models like ChatGPT and other generative systems, which excited millions of people about what seemed like a magical breakthrough in technology, only for the story to go through a series of massive controversies. . including strikes, legal challenges and important scientific and philosophical debates.

We also had absurdities, like the ridiculous palace drama surrounding the firing and dismissal of ChatGPT figurehead Sam Altman as CEO. And of course we had depressing displays of astonishing ignorance, such as the discredited and failed far-right tech entrepreneur Elon Musk talking nonsense while being interviewed by the discredited far-right Prime Minister Rishi Sunak. The fact that stories about AI are often dominated by rich, ridiculous men who often have no real qualifications to discuss the topic is not only annoying, but also makes it factually harder for people who want to understand the real implications of these technologies to do so.

All of which leads to the excellent timing of this book’s publication. The Master’s Eye: A Social History of Artificial Intelligence by Matteo Pasquinelli is a solid antidote to both the overblown hype and fanciful fatalism that tends to color mainstream coverage of AI.

Technology in historical materialism

Pasquinelli exposes the adversary he seeks to defeat in the introduction:

‘Writing a history of AI in the current situation means taking into account a vast ideological construct: among the ranks of Silicon Valley companies and also high-tech universities, propaganda about the almighty power of AI is the norm and sometimes even repeats machine folklore. achieving “superhuman intelligence” and “self-awareness.” This folklore is well exemplified by apocalyptic Terminator narratives, in which AI systems would reach a technological singularity and pose an “existential risk” to the survival of the human species…” (pp. 8-9).

From here he goes on to point out that at many stages of technological development, new technologies have been fetishized into divine entities beyond reasonable human control. Promoting these ideas is a great way for the people who use them to disclaim their personal responsibility for what the technologies do and make it seem impossible for humans to oppose or redirect the results of these technologies. This is the reason for the apparent contradiction we currently have: many of the wildest and most fatalistic predictions about the usurpation of humanity by AI actually come from technology experts who invest in the sector: the last thing they want is a informed opinion. discussion on how AI could be democratically responsible and socially useful.

Pasquinelli goes back to ancient times to show how the development of technologies, from the very origins of mathematics in the Bronze Age, when a development of increasingly large and complicated agricultural communities discovered that they could use an abstraction from the simple business of count to support better organized and more successful ways of working.

The need for the means of production to facilitate technological change in production by creating a purpose for it is a recurring theme throughout the book. It is widely understood that the steam engine was, in principle, known in classical Greece, but simply did not have any industrial applications until the development of capitalism in the English industrial revolution created such applications. However, the jobs it held, such as pumping water and turning gears, had already been created by new divisions of labor that capitalism had first established.

Pasquinelli shows that while this was true for mechanical energy, it was also true for mechanical computation. Charles Babbage, often seen as the co-inventor of what we now call “computing” with Ada Lovelace (neither of them used that term at the time), originally developed his “difference engine” because of the new need in computing. colonial era of extensive navigation data charts. The need had been created to perform calculations more quickly and accurately, so there was now an opportunity to create technology for this purpose. Babbage began designing the machine that could potentially do this. Lovelace innovated by recognizing that the machine’s functionality could be abstracted further, so it couldn’t just do the calculation you told it to do, but would actually calculate what additional calculations it should do, and that’s why it is called Mother”. of software’ today.

In a really funny little aside, Pasquinelli takes advantage of a particular aspect of Lovelace’s notes in which he raises, but dismisses, the idea that this would eventually make a difference as a self-aware engine as a human being, saying that they would never stop of being ‘extensions’. of human power, or of additions to human knowledge” – it’s pretty funny to realize that she had tried to scare away idiots like Elon Musk two hundred years ago!

Both Lovelace and Babbage served their class, of course: they were part of the bourgeoisie and sought to use computing to further divide labor for completely bourgeois purposes. However, this did mean that the fundamentally collaborative and collective origin and purpose of technology was of clear importance to critics of capitalism. Karl Marx himself soon saw the value of Babbage’s work in developing these critiques.

Developments and debates

As the book progresses the development of computing as we know it, an increasing number of fields of study come together in fascinating ways in sometimes surprising interactions. Early electricity gives rise to telegraphic communication, which begins the study of electronics. It also makes people think of the human brain as a network of signals like a telegraphic exchange, displacing efforts to think of it as a set of rotating gears as in Babbage’s difference engine. Ideas about how the human mind might work and how a calculating machine might emulate it are a two-way exchange of concepts, and an increasingly multidimensional view of how human intelligence might work starts a key debate in computer science.

The first form of reasoning in computers was deductive: “if X is true, then Y, otherwise Z.” Programming like this is easy to do, but it runs into capacity limits as soon as you ask the computer to do something that involves making a judgment where the truth of X contains ambiguity, such as determining whether two lines are crossed or not. It is a letter to do it.

Politics and economics are never far from the surface of any of these processes. The founder of neoliberal thought, Fredick von Hayek, was a great defender of what we today call neural networks. He compares a learning system to a market, his only ideal of a self-organizing system. Pasquinelli points out, through Marx’s writings, that this is a deliberate ahistoricism that ignores that productive In reality, the groups were more key to the development of computing. It also takes us through the fascinating historical paradox that in the 1960s, the distributed processing technologies that make up the Internet were being driven, on the one hand, by a military-industrial complex that wanted a means to retain its control and authority. in the event of a nuclear explosion. war, but on the other, by an academy that believed they were developing the same systems to free people from authoritarianism. Today’s boring libertarians are, in many cases, simply repeating old arguments badly.


In his current conclusion, Pasquinelli ends the book by calling the reader to understand what AI technologies are through a specific approach. automation labor theory, and that AI is not an end point or an apocalypse, but the result of a set of technological advances that have abstracted automation to the point where it can now automate itself. This has happened because we have the technical capacity to make such machines, but there is also an economic incentive to do so and to reorganize divisions of labor once again.

AI does not pursue any extraneous or supernatural agenda separate from the capitalist system that has produced it, and has physical limitations in capacity and energy consumption, like all previous technologies. He implores that the solutions to problems in the age of AI do not lie in determinism, but that “the first step in technopolitics is not technological but political” (p.253), and advises people to take an interest in groups and individuals. who are dedicated to what he calls “action research.” This is the work and activism of uncovering and beginning to challenge the excessive power of the small set of bloated monopolistic technology corporations that have risen to the top of society in the current era. I think it’s an absolutely good way to learn more about how the union movement should be organized in the age of AI.

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