What Tech Calls Thinking: An Inquiry into the Intellectual Bedrock of Silicon Valley

By Adrian Daub

A New York Times Book Review Editors' Choice

"In Daub’s hands the founding concepts of Silicon Valley don’t make money; they fall apart." --The New York Times Book Review

From FSGO x Logic: a Stanford professor's spirited dismantling of Silicon Valley's intellectual origins

Adrian Daub’s What Tech Calls Thinking is a lively dismantling of the ideas that form the intellectual bedrock of Silicon Valley. Equally important to Silicon Valley’s world-altering innovation are the language and ideas it uses to explain and justify itself. And often, those fancy new ideas are simply old motifs playing dress-up in a hoodie. From the myth of dropping out to the war cry of “disruption,” Daub locates the Valley’s supposedly original, radical thinking in the ideas of Heidegger and Ayn Rand, the New Age Esalen Foundation in Big Sur, and American traditions from the tent revival to predestination. Written with verve and imagination, What Tech Calls Thinking is an intellectual refutation of Silicon Valley's ethos, pulling back the curtain on the self-aggrandizing myths the Valley tells about itself.

FSG Originals × Logic dissects the way technology functions in everyday lives. The titans of Silicon Valley, for all their utopian imaginings, never really had our best interests at heart: recent threats to democracy, truth, privacy, and safety, as a result of tech’s reckless pursuit of progress, have shown as much. We present an alternate story, one that delights in capturing technology in all its contradictions and innovation, across borders and socioeconomic divisions, from history through the future, beyond platitudes and PR hype, and past doom and gloom. Our collaboration features four brief but provocative forays into the tech industry’s many worlds, and aspires to incite fresh conversations about technology focused on nuanced and accessible explorations of the emerging tools that reorganize and redefine life today.

• Language: English
• Publisher: Macmillan Publishers
• Release date: Oct 13, 2020
• ISBN: 9780374721237

Adrian Daub

Adrian Daub is a professor of comparative literature and German studies at Stanford University, and the director of Stanford’s Program in Feminist, Gender, and Sexuality Studies. His research focuses on the intersection of literature, music, and philosophy in the nineteenth century, and he is the author of several books published by academic presses. His writing has appeared in The Guardian, The New Republic, n+1, Longreads, and the Los Angeles Review of Books. He lives in San Francisco.

Book preview

Introduction

This is a book about the history of ideas in a place that likes to pretend its ideas don’t have any history. The tech industry is largely disinterested in the kinds of questions this book raises; tech companies simply create a product and then look to market it. Mark Zuckerberg put it as follows: I hadn’t been very good about communicating that we were trying to go for this mission. We just showed up every day and kind of did what we thought was the right next thing to do. The mission, the big question, became important only later. Only in hindsight did he have to ask himself: How do I explain this to journalists? The U.S. House of Representatives? Myself? At the same time, Zuckerberg’s quote is meant to imply that there had been such a mission all along, that showing up every day and working on a good, monetizable product was never all Facebook was about. What Tech Calls Thinking concerns where tech entrepreneurs and the press outlets that adore them look once they reach the point at which they need to contextualize what they’re doing—when their narrative has to fit into a broader story about the world in which we all live and work.

As Silicon Valley reshapes the world, journalists, academics, and activists are spending more time scrutinizing the high-minded ideals by which companies like Google and Facebook claim to be guided. As the journalist Franklin Foer put it, Silicon Valley companies have a set of ideals, but they also have a business model. They end up reconfiguring your ideals in order to justify their business model. This book asks where companies’ ideals come from. The question is far from a sideshow: It concerns how the changes Silicon Valley brings about are made plausible and made to seem inevitable. It concerns the way those involved in the tech industry understand their projects and the industry’s relationship to the wider world. It isn’t so much about the words that people in Silicon Valley use to describe their day-to-day business—interesting books could be and have been written about the thinking contained in terms like user, platform, or design. Rather, it is about what the tech world thinks it’s doing when it looks beyond its day-to-day business—the part about changing the world, about disrupting X or liberating Y. The stuff about Tahrir Square protests and $27 donations. What ideas begin to track then? And what is their provenance?

Indeed, the very fact that these ideas have histories matters. Silicon Valley is good at reframing questions, problems, and solutions, as the jargon of design thinking puts it. And it is often deeply unclear what the relationship is between the reframed versions and the original ones. It’s easy to come away with the sense that the original way of stating the problem is made irrelevant by the reframing. That perhaps even the original problem is made irrelevant. Some of this is probably inherent in technological change: it’s hard to remember the history of something that changes how memory works, after all. In the 1960s, the communication theorist Marshall McLuhan (1911–1980) proposed that the effects of technology do not occur at the level of opinions or concepts, but alter sense ratios or patterns of perception steadily and without any resistance.

But clearly that’s only part of the story. To some extent, the amnesia around the concepts that tech companies draw on to make public policy (without admitting that they are doing so) is by design. Fetishizing the novelty of the problem (or at least its framing) deprives the public of the analytic tools it has previously brought to bear on similar problems. Granted, quite frequently these technologies are truly novel—but the companies that pioneer them use that novelty to suggest that traditional categories of understanding don’t do them justice, when in fact standard analytic tools largely apply just fine. But this practice tends to disenfranchise all of the people with a long tradition of analyzing these problems—whether they’re experts, activists, academics, union organizers, journalists, or politicians.

Consider how much mileage the tech industry has gotten out of its technological determinism. The industry likes to imbue the changes it yields with the character of natural law: If I or my team don’t do this, someone else will. Such determinism influences how students pick what companies to work for; it influences what work they’re willing to do there. Or consider how important words like disruption and innovation are to the sway the tech industry holds over our collective imagination. How they sweep aside certain parts of the status quo but leave other parts mysteriously untouched. How they implicitly cast you as a stick-in-the-mud if you ask how much revolution someone is capable of when that person represents billions in venture capital investment.

This is where the limits of our thinking very quickly become the limits of our politics. What if what goes by the name of innovation is ultimately just an opportunistic exploitation of regulatory gaps? And before we blame those gaps, keep in mind that regulation is supposed to be slow-moving, deliberate, a little bit after-the-fact. A lot of tech companies make their home between the moment some new way to make money is discovered and the moment some government entity gets around to deciding if it’s actually legal. In fact, they frequently plonk down their headquarters there.

Take Uber and Lyft, for example. The two ride-share giants are in many ways more agile and cheaper for the consumer than the taxi services they’re slowly destroying, and these companies are accordingly popular with large investment funds, for one primary reason: their drivers are independent contractors who have no bargaining power, no benefits, and very few legal protections. Everything these companies do—from the rewards programs they set up for their contractors to the way the algorithms that assign rides to drivers seem to punish casual driving—is actually designed to nudge their drivers inch by inch toward a full-time employment that they aren’t allowed to call full-time employment. The moment this state of affairs is recognized, all kinds of rules will apply to these companies, making them even more unprofitable and likely putting them out of business. But until such a moment, the companies will explain to you ad nauseam how they’re different and new and how you are missing the point when you apply established categories to them.

This book is about concepts and ideas that pretend to be novel but that are actually old motifs playing dress-up in a hoodie. The rhetoric of Silicon Valley may seem unprecedented, but in truth it is steeped in some pretty long-standing American traditions—from the tent revival to the infomercial, from predestination to self-help. The point of concepts in general is to help us make distinctions that matter, but the concepts I discuss in the chapters that follow frequently serve to obscure such distinctions. The inverse can also be true: some of the concepts in this book aim to create distinctions where there are none. Again and again we’ll come across two phenomena that to the untrained eye look identical, but a whole propaganda industry exists to tell us they are not. Taxi company loses money; Uber loses money—apparently not the same. The tech industry ideas portrayed in this book are not wrong, but they allow the rich and powerful to make distinctions without difference, and elide differences that are politically important to recognize. They aren’t dangerous ideas in themselves. Their danger lies in the fact that they will probably lead to bad thinking.

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In the following chapters, I will try to show not only how certain ideas permeate the world of the tech industry, but also how that industry represents itself to a press hungry for tech heroes and villains, for spectacular stories in what is ultimately a pretty unspectacular industry. A study like this one almost by necessity has to foreground the highly visible founders, funders, and thought leaders. To find out how ordinary coders or designers think, to say nothing of all the folks making up the tech industry who aren’t customarily thought of as belonging to that industry, is a very interesting project in its own right, but it isn’t the project of this book. For better and for worse, the media has a fixation on tech thought leaders. It seems to need certain figures to be able to spin its narrative. Peter Thiel, Elon Musk, Steve Jobs, and others like them knew how to manipulate that—something they learned from another California global export: 1960s counterculture.

Unfortunately, my own spotlighting of these leaders means this book risks recapitulating one of the central misperceptions of the tech industry; it’s anything but clear whether figures like Mark Zuckerberg, Elon Musk, or even Steve Jobs really embody the way the tech sector understands itself. But what is clear is that they represent the way the tech sector has communicated with the outside world. They are easy identificatory figures when one is dealing with an industry that can be disturbingly amorphous and decentralized. (This is, after all, how the pars pro toto Silicon Valley has functioned in general.) They are creatures of the media, inviting us to project our fears, giving shape to our hopes. Most important, they encourage us to think that someone, whether charismatic or nefarious, knows where the journey is going. Visibility in the press is not, of course, the same as representativeness. Making a Theranos movie is not cool. You know what’s cool? Making an Elizabeth Holmes movie.

Giving these ideas’ history back is central to any attempt to interrogate the claims the tech industry makes about itself. But there’s another question that we can ask once we’ve figured out where these ideas come from: Why were these ideas convenient to adapt, and why was it convenient to forget their history? The story of these ideas intersects with the great transformations that information technology has undergone in the last seventy years. Coding went from being clerical busywork done by women to a well-paid profession dominated by men. In recent years, competencies around technology went from highly specialized to broadly distributed, to the point where learn to code has become a panacea for any and all of the ravages of