The algorithm has taken on a particularly mythical role in our technology-obsessed era, one that has allowed it wear the garb of divinity. Concepts like “algorithm” have become sloppy shorthands, slang terms for the act of mistaking multipart complex systems for simple, singular ones.
—Ian Bogost (2015)
The Growing Power of Programmers and the Preceding Automation of Non-Coders.
The early 2000s saw a rapid acceleration of the world’s technological capacity to store, communicate, and compute information, leading to the institutionalization of a “data imperative” across organizations of all types. This shift brought about immense changes to the tech industry and capitalism in general, with data being touted as the “new oil.” As a result, any company or public or nonprofit corporation had the opportunity to try and mine their own data. The dot-com bust didn't stop the rise of Silicon Valley, as a new mode of production powered by big data and analytics surged. This new economy brought about increased incomes and soaring property values, but also led to more and more people becoming homeless. The coronavirus pandemic has only further emboldened the claims of tech “solutionists” and created new kinds of inequalities, particularly in digital education. The most visible feature of this new economy is the extreme urban wealth and poverty that exist side-by-side. This pits the owners of capital (venture capitalists, company founders, and tech employees) against those who work for them (service workers, subcontractors, and day laborers). San Mateo County is the most unequal county in California, with the top 1% making 49.1 times more than the bottom 99%. This inequality is also reflected in other hubs of digital capitalism, such as Seattle and the San Francisco Bay Area, where Black and Latinx people are overrepresented at lower income levels and in lower rungs of the tech industry labor force.
The Coding Elite: Leveraging Force on a Large Scale
Karl Marx famously believed that the development of technology was closely interconnected with the relations of production and the ideologies created by them. He highlighted this idea clearly in a well-known passage from The Poverty of Philosophy:
Social relations are closely bound up with productive forces. In acquiring new productive forces men change their mode of production; and in changing their mode of production, in changing the way of earning their living, they change all their social relations. The hand-mill gives you society with the feudal lord; the steam-mill, society with the industrial capitalist. The same men who establish their social relations in conformity with the material productivity produce also principles, ideas, and categories in conformity with their social relations.
In the world of today, the most influential class is the coding elite. This class of software developers, tech CEOs, investors, and computer science and engineering professors work to create software systems that are powered by data and algorithmic ingenuity. It is this elite class that is responsible for the digitization of society and has enabled the rise of the software capitalist. At universities around the country, especially at Stanford University, the line between academia and the tech industry has become blurred as professors move between their own start-ups, key positions in large firms, government-sponsored research labs, and classrooms. The most sought after people in this world are those who understand computer code and can build and own the code. This mastery of computational techniques enables the coding elite to have power that is both cultural, political and economic. Culturally, they have an understanding of the trustworthiness of numbers and use these to advance computational techniques across disciplines. Politically, they are able to control the world through code which allows them to legibly speak for people and objects, admit and exclude and make decisions the same way law does, but with automated enforcement. In terms of economics, the products of digital tech sector firms are attractive to venture capitalists as they scale quickly with the number of users. This is due to network effects and automated feedback loops that improve predictive accuracy and market possibilities. Overall, the coding elite is a powerful class of people that have been enabled by digitization and their influence is both cultural, political and economic. They have the power to shape society and its future.
The long history of information technology is a continuous effort to gain control over labor, materials, and markets, an effort which began during the industrial revolution. According to Burris (1989, 1993), this has led to a class of experts who have become increasingly autonomous from their bureaucratic masters, especially when dealing with computerized forms of control. This has caused a flattening of social hierarchies, a polarization of organizations between expert and non-expert sectors, and a fusion of technical and managerial functions. These experts are often more powerful than those with credential certifications as their expertise and ability to accomplish tasks better and faster is what gives them the power. This is especially true for the coding elite, who are dismissive of credentialing and believe that craft should prove its value through application. The tech industry helps this process by carving away at tasks which were previously the domain of professionals and by using management gurus, specialized magazines, and tech evangelists to spread belief in a particular technology. These tech evangelists are tasked with building a loyal following, thus consolidating power into the hands of those who understand and are able to implement code. This brings into question the legitimacy of professional judgement being displaced by the coding elite and algorithms. The coding elite often draw on behavioral economics or social psychology to prove their point that machines are more consistent than human decision-makers. They point to the fact that algorithms do not need sleep and are vigilant at all times and that the existence of data renders human decision-makers inadequate. Moreover, they argue that people should use algorithms to reform their own conscious practices of reasoning. The ideology at work here is that human mentation is frail and flawed and that algorithms can be used to tame this. However, what lies beneath this is the powerful economic incentives to better predict or direct behaviour.
From a world where algorithms dictate the way of life to a world where algorithms are an integral part of life.
The main goal of the coding elite is, at this point, quite mysterious. Their visions of the future vary widely, with some hoping for a new social species in the form of general AI that surpasses human intelligence, while others express optimism for a more ethical and equitable form of AI. Moore's law, which states that computer power tends to grow exponentially, provides a likely trajectory for the development of AI, but it's not clear who will benefit from its use. Some have suggested that the elite who control the technology will have the greatest advantage, potentially using it to enhance themselves physically and mentally. On the other hand, those who are being surveilled and disadvantaged by AI may not have the same access to its benefits. Discussion of AI often assumes a certain level of futurism and hype, but it's important to remember that the technology is already being used, and it's having real-world effects. AI is designed, sustained, and powered by people, and like other forms of surveillance and control, it is often used to discriminate against the most vulnerable and marginalized populations. While it may be possible to develop AI that is ethical and equitable, this is not yet a reality, and it's up to the coding elite and the rest of society to ensure that the technology is used for the benefit of all.
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