You’re Doing It Wrong: Notes on Criticism and Technology Hype

Maybe more people are writing about the real and potential problems of technology today than ever before. That is mostly a good thing. The list of books and articles from the last few years that have nuanced and illuminating perspectives on the contemporary technological situation is rich and long.

Recently, however, I’ve become increasingly aware of critical writing that is parasitic upon and even inflates hype. The media landscape is full of dramatic claims — many of which come from entrepreneurs, startup PR offices, and other boosters — about how technologies, such as “AI,” self-driving cars, genetic engineering, the “sharing economy,” blockchain, and cryptocurrencies, will lead to massive societal shifts in the near-future. These boosters — Elon Musk comes to mind — naturally tend to accentuate positive benefits. The kinds of critics that I am talking about invert boosters’ messages — they retain the picture of extraordinary change but focus instead on negative problems and risks. It’s as if they take press releases from startups and cover them with hellscapes.

At their most ridiculous, hype-filled criticisms become what historian David C. Brock calls “wishful worries,” that is, “problems that it would be nice to have, in contrast to the actual agonies of the present.” (See also science journalist John Horgan’s recent Scientific American post on the topic.) Perhaps the most beautiful example of a wishful worry is the article titled, “Hacked Sex Robots Could Murder People, Security Expert Warns,” which, sadly for our culture, is not an April Fool’s prank. Part of Brock’s point is that wishful worries are a kind of entertainment. We are, after all, a people that regularly feasts upon dystopian science fiction. Imaginary fears can be fun.

But it’s not just uncritical journalists and fringe writers who hype technologies in order to criticize them. Academic researchers have gotten in on the game. At least since the 1990s, university researchers have done work on the social, political, and moral aspects of wave after wave of “emerging technologies” and received significant grants from public and private bodies to do so. As I’ll detail below, many (though certainly not all) of these researchers reproduced and even increased hype, the most dramatic promotional claims of future change put forward by industry executives, scientists, and engineers working on these technologies. Again, at the worst, what these researchers do is take the sensational claims of boosters and entrepreneurs, flip them, and start talking about “risks.” They become the professional concern trolls of technoculture.

To save words below, I will refer to criticism that both feeds and feeds on hype as criti-hype, a term I find both absurd and ugly-cute, like a pug. (Criti-hype is less mean than the alternative, hype-o-crit, though the latter is often more accurate.)

This post moves through three stages: First, I examine a clear case of contemporary criti-hype: how the film The Social Dilemma and Shoshana Zuboff’s book, The Age of Surveillance Capitalism, overstate the abilities of social media firms to directly influence our thoughts and provide near zero evidence for it. Second, I offer a preliminary history of how criti-hype became an academic business model by taking a look at the examples of the Human Genome Project, nanotechnology, “AI,” and a few others. Third, I talk about some of the costs of criti-hype and offer some solutions before ending on a thoroughly pessimistic note.

Before I proceed, I want to make one thing clear: My point isn’t that technology is risk free. Not at all. For every technological risk that has been overstated in the past, one or more risks have been underestimated and bit people — most often the poor and marginalized — on the hind end. My first book, Moving Violations, is a history of automobile regulation in the United States and examines how groups tried to make cars safer, less polluting, and more fuel efficient. There are entire libraries of books on legitimate and serious technological risks that harm and kill every day. More work can and should be done on these topics. Indeed, I will argue at the end that one response to criti-hype should be doing a better job of steering graduate students away from “emerging technologies” which are little more than promissory notes towards actual technological agonies.

The problems I explore below develop when people begin working on the ethics and governance of technological situations that aren’t real — and not just “aren’t real” in the sense aren’t yet real but aren’t even realistic projections of where the science and technology is headed. Criti-hypers play up fantastic worries to offer solutions, and as we’ll see, often they do this for reasons of self-interest —including self-interest as in $$$$$$$$$$.

A famous song, which — little-known fact — is actually about scoring money from the NSF.

Criti-Hype Today

Some of the clearest examples of criti-hype today center on the role of social media in our lives, especially the claim that its designers can directly and effectively influence our behavior. Perhaps the two most striking examples of this criti-hype trend are Shoshana Zuboff’s book, The Age of Surveillance Capitalism, and the film The Social Dilemma, which includes Zuboff and another criti-hyper Tristan Harris as talking heads.

Both the book and film liken social media companies to puppet masters who have users on strings. Tristan Harris looks at the camera earnestly and says, “Never before in history have 50 designers . . . made decisions that would have an impact on two billion people. Two billion people will have thoughts that they didn’t intend to have” because of the designers’ decisions. But Harris and the other people who appear in The Social Dilemma provide no evidence that social media designers actually CAN purposefully force us to have unwanted thoughts. (Now-old joke: have I ever had a thought on purpose?) The films’ talking heads repeat spectacular claims that social media companies, which are basically advertising companies, would love their customers to believe.

A screenshot from the film The Social Dilemma. Tristan Harris tells the audience, “Two billion people have thoughts that they didn’t intend to have” as the filmmakers show us an animation of puppet masters controlling users like marionnettes.

To some degree, it is unsurprising that Harris reproduces the digital technology industry’s hype-y claims about itself because he comes from it. Harris has a degree in computer science from Stanford and worked at Google but has no training in humanities/social science studies of technology, which might give him critical distance from industry propaganda.

In a notorious scene of The Social Dilemma, Tristan Harris says, “No one got upset when bicycles showed up. Right? Like if everyone’s starting to go around on bicycles, no one said, ‘Oh, my God, we’ve just ruined society.’” Actually the exact opposite is true. There was a moral panic around the threat of bicycles, a well-known fact amongst people who study the social dimensions of technology. An 1894 New York Times article told readers, “There is not the slightest doubt that bicycle riding, if persisted in, leads to weakness of mind, general lunacy, and homicidal mania.” Moreover, there have been moral panics about film, radio, television, and nearly every other older media form, including about how they supposedly manipulated users. For example, everyone should own a copy of the 1980 book, The Clam-Plate Orgy and Other Subliminal Techniques for Manipulating Your Behavior, which played a role in widespread worries about “subliminal messages.” Harris has not taken the time to get perspective on the bigger picture of technology and society.

Ooh. La. La.

What is less obvious is why Shoshana Zuboff, an emerita professor of Harvard Business School, so uncritically repeats the digital industry’s marketing materials, nor why she never points to or assesses evidence that goes against her argument. Yet her writings are full of hyperbole that sounds like she took press releases from Facebook’s and Google’s PR departments and rewrote them to be alarming,

In an editorial related to her book titled, “You Are Now Remotely Controlled,” Zuboff wrote that social media and the like are a “a new ‘instrumentarian’ power that works its will through the medium of ubiquitous digital instrumentation to manipulate subliminal cues, psychologically target communications, impose default choice architectures, trigger social comparison dynamics and levy rewards and punishments — all of it aimed at remotely tuning, herding and modifying human behavior in the direction of profitable outcomes and always engineered to preserve users’ ignorance.” God, that sounds scary. But is it true?

You would think in a 700 page book Zuboff would present mounds of evidence of such an important and central claim that “surveillance capitalism” firms are able to influence our behavior directly to the point where we lost the “will to will,” as she puts it. But in fact, she puts forward very little evidence for this claim.

Her account primarily relies on a few pieces of verification: first, two studies on emotional contagion that Facebook published. In these studies, people who were shown more negative posts were more likely to make their own negative posts and people shown more positive posts were more likely to make positive ones. But these studies are controversial in some circles and hardly show a large impact anyway. The findings were statistically significant because they had enormous sample sizes — in one study, 689,003 people — but their effect sizes were small (in that same study, Cohen’s d = 0.02). This is no demonstration of puppet mastery.

The other bit of evidence Zuboff regularly relies on is . . . Pokémon GO. Zuboff describes it in frightening ways, “Game players did not know that they were pawns in the real game of behavior modification for profit.” But all that happened was that companies like McDonald’s, Sprint, and Starbucks paid Pokémon GO-maker Niantic money for each player who showed up to their locations to acquire virtual goods in the game. Are you scared now?

In fact, there is a great deal countervailing evidence that cuts against hype about online companies being able to influence our behavior. Zuboff and Co. never take this evidence into account because it would undermine their cases. Articles such as “Ad Tech Could Be the Next Internet Bubble” and “The new doc com bubble is here: it’s called online advertising” as well as Tim Hwang’s book, Subprime Attention Crisis: Advertising and the Time Bomb at the Heart of the Internet detail how terrible online advertisements are both at finding the right target and influencing us even when they do find sympathetic eyeballs. One study by business school professors used six different advertising platforms found the targeting of ads performed worse than random guessing. If your friends are like mine, you regularly see what has become a genre of Facebook post, wherein people put up screenshots of ridiculous and inappropriate ads that Facebook showed them. Contra Harris and Zuboff, it seems that Mark Zuckerberg cannot sell me fucking socks, let alone purposefully/significantly change my politics or self-concept.

To be clear, I am NOT saying that there’s nothing to worry about or study when it comes to how social media use shapes behavior. There are many things to be concerned about and try to better understand, including misinformation, radicalization, the formation of mobs through online platforms, and more. There are also plenty of reasons to question Facebook’s, Google’s, and other firms’ monopolistic powers and potentially even to break them up. But none of these problems or our criticisms of them have anything to do with social media companies being able to control our minds.

Criti-hypers like Harris and Zuboff reproduce the most far-fetched claims of the online advertising companies to such a degree that an old joke wonders if they are secretly being paid by those companies to keep air in the online ad bubble. Mercifully, there are many critical works on digital technology that do not engage in criti-hype and indeed challenge senseless claims about powers of new technologies, including Evgeny Morozov’s pioneering work on “solutionism”; Meredith Broussard’s questioning of artificial intelligence; Morgan Ames’, Christo Sims’, and Roderic Crooks’ critically examining claims around “EdTech”; Sarah Roberts’, Tarleton Gillespie’s, Mary Gray’s, Siddharth Suri’s, and other folks’ unveiling of the hidden work behind online platforms; and many other examples.

But we shouldn’t take these counter-examples as evidence that academic research is free of criti-hype. Indeed, at some point, criti-hype unquestionably became an academic business model.

How Criti-Hype Became an Academic Business Model

How did criti-hype become an academic business model? This history has yet to be written, and, in general, I think we need a more robust, self-reflexive understanding of how funding has shaped research priorities and critical approaches in academic science and technology studies.

I believe, however, that one stream of this business model arose out of the Human Genome Project’s Ethical, Legal, and Social Implications program, which put 3% and later 5% of the HGP’s budget towards studying moral and social issues. Since that time, it has become the model wherein academic humanities and social science researchers attach themselves to new “emerging technologies” to study the ethics and social implications of speculative risks. Indeed, I think we can talk about the ELSIfication of some fields, including science and technology studies

(A common criticism of ELSI is that it effectively involved scientists buying off, controlling, and/or domesticating social scientists and philosophers to stave off more radical critiques. This is interesting and deserves more examination. But in this post, I want to focus on the agency of the academic humanities and social science researchers who played along with hype to score cash money and prestige.)

There were certainly things to criticize about the Human Genome Project. Friends who were working during that period recount stories of scientists who were far-too overly-confident about their abilities to control genetic manipulations once they were made.

But there was also a great deal of criti-hype around genetic engineering. One example is The President’s Council on Bioethics 2003 report, Beyond Therapy: Biotechnology and the Pursuit of Happiness, which included professors like Leon Kass, Francis Fukayama, and Robert George and worried about the dangers of designer babies, ageless bodies, and that people might make themselves . . . too happy. Sounds like wishful worries to me.

While we should not downplay the way genetic information is being used in medicine today, it’s also clear that the most extraordinary of earlier visions of genetic engineering have not come true — not even close. Even with CRISPR today, genetic engineering is far more difficult than some people imagined.

After the Human Genome Project, the next emerging technology that criti-hype formed around may have been nanotechnology, which, as Patrick McCray showed in The Visioneers, boosters claimed would transform the world. Arizona State University (ASU) president Michael Crow and a co-author wrote, “The first thing to say is that if — as is variously claimed — nanotechnology is going to revolutionize manufacturing, health care, travel, energy supply, food supply, and warfare, then it is going, as well, to transform labor and the workplace, the medical system, the transportation and power infrastructure, the agricultural enterprise, and the military.” The authors made a number of recommendations, including that more funding should be directed to . . . people like them: “If we wanted to be serious about preparing for the transformational power of a coming nanotechnology revolution, we would need first get serious — at this very early stage — about developing knowledge and tools for effectively connecting R&D outputs with desired societal outcomes.”

In 2003, the US Congress passed 21st Century Nanotechnology Research and Development Act, which directed that some NSF money be used for research on the societal, ethical and environmental concerns of nanotechnology research to “bring about improvements in quality of life for all Americans,” much like the Human Genome Project’s ELSI. Part of NSF’s funds went to the creation of The Center for Nanotechnology in Society at Arizona State University.

In 2008, another set of authors, including ASU faculty David Guston, Cynthia Selin, and Erik Fisher, cited the Crow et al essay as a source of authority: “The widespread understanding that nanotechnology constitutes an emerging set of science-based technologies with the collective capacity to remake social, economic, and technological landscapes (e.g., Crow & Sarewitz, 2001) has, in itself, generated tangible outcomes.” (Why ASU is such a center of criti-hype will be the subject of a longer essay.)

Guston went on to edit a series titled the Yearbook in Nanotechnology and Society, which ran for three years before nanotech exuberance evaporated and it was discontinued, becoming no longer a . . . yearbook. The second yearbook edited by Jameson Wetmore (ASU again) and Susan Cozzens (Georgia Tech) contained these dramatic claims, “Nanotechnology is enabling applications in materials, microelectronics, health, and agriculture, which are projected to create the next big shift in production, comparable to the industrial revolution. Such major shifts always co-evolve with social relationships. This book focuses on how nanotechnologies might affect equity/equality in global society. Nanotechnologies are likely to open gaps by gender, ethnicity, race, and ability status . . . . ”

Now, many of these exaggerations about nanotech now seem outlandish to the point of being LOL funny. But the point is that these worries about nanotechnology were a black mirror for claims made by the technology’s boosters, and there were clear financial incentives for academic social science researchers to go along with the hype. If nanotechnology was not as big a deal as its boosters claimed, there also wouldn’t be reason to fund social science research on the topic.

More recently, “AI” is the area of technology that has likely experienced the greatest amount of criti-hype. As Yarden Katz and others have argued, “AI” is really best thought of as a rebranding exercise: around 2017–2018, corporations using “AI” to describe things that had previously been known by other faddish terms, like “Big Data.” Most notably, Google renamed its Google Research division Google AI.

At about the same time, a number of academic centers opened up to look at ELSI of “AI,” often funded with money from private foundations and the digital technology industry itself. (I think there are more of these “AI” centers than there ever were for nanotech, and one hypothesis is that there is learning going on around criti-hype in academia. The business model is diffusing.) For sure, these academic centers have put out some nuanced work on problems of digital technology, but they have also, without a doubt, engaged in criti-hype.

For example, in its 2017 report, the AI Now Institute, which is associated with New York University, paraphrased another report from the consulting firm McKinsey claiming that 60 percent of occupations would have 1/3 of their activities automated. This would be an enormous increase in productivity from a single set of technologies, probably one of the largest in history. These claims precisely mirrored the advertising digital technology firms were putting out as well as visions coming out of organizations like the World Economic Forum that we were on the cusp of a “Fourth Industrial Revolution.”

The AI Now report argued, “To prepare for these changes, it will be essential that policymakers have access to robust data on how advances in machine learning, robotics and the automation of perceptual tasks are changing the nature and organization of work, and how these changes manifest across different roles and different sectors.” This of course means more funding for exactly the kinds of research that these “AI” ELSI centers were doing. And AI Now called for funding in several different ways throughout the report.

There are other examples of criti-hype around “AI,” too. I have watched people in “critical AI studies” give conference presentations in which they spun out elaborate and frightening dystopian futures based on no other evidence than a few Google Image searches.

But, just as happened with nanotech, the wind appears to be going out of the sales of “AI.” Some researchers suggest that we may be entering a new “AI Winter,” a period of decreased funding in the area, or at least an “AI Autumn,” as exuberance for the technology fades and expectations come back to earth. The claims made around productivity and unemployment particularly appear to be bunk. Examining 40 “AI” firms, Jeffrey Funk has estimated that it will take decades for them to have any marked effect on productivity by, for example, increasing the efficiency of offices. Recent reports predict that “AI” will not lead to significant near-term changes in employment. (Keystone, MIT)

Sometimes the relationship between social science researchers and scientists/engineers working on an emerging technology can become so cozy that it undercuts criticism altogether. Once someone researching the social implications of synthetic biology told me that the field was, in her estimation, mostly salesmanship and bullshit. “That’s what you need to write then,” I told her. She said that if she told the truth she would lose access to the people she was studying, and since she was planning to do this research for much of the rest of her career, that wasn’t an option. Here, social science becomes as bad as the worst forms of access-preserving journalism.

Moreover, at times, it can appear that social scientists and humanities folks are trying to create demand for something that no one wants. As Jane Flegal put it in her dissertation on geo-engineering, “For one, the supply of research on solar geoengineering — social scientific and otherwise — has outpaced any demand function.” By doing criti-hype, researchers hope others will want to buy their wares.

It will be interesting to see what happens to researchers and centers currently dedicated to — even named after — synthetic biology, geoengineering, and “AI.” Most likely they’ll just fade away. But here’s the depressing thing: no matter what bit of science and technology becomes hot and faddish next and no matter how unrealistic and hollow the claims made about its future are, some academic researchers will emerge to say they are doing the “ethics” or “anticipatory governance” or “responsible innovation” or whatever-the-fuck of that thing. And they will pull down big, stanky, oozey chunks of cheese from funding bodies for doing it, too. You don’t even need to say “maybe” this will happen. It’s a guarantee.

The Costs of Criti-Hype

If the only downside of criti-hype was folks blowing federal tax dollars making edited volumes that no one reads, it wouldn’t be worth talking about. Welcome to modern life — it’s rubbish.

But criti-hype comes with real costs. Here I will focus on two:

First, criti-hype helps create a lousy information environment and lends credibility to industry bullshit. In Bubbles and Crashes, Brent Goldfarb and David Kirsch write about the role of narratives in creating speculative bubbles around new technologies. When academics engage in criti-hype, they lend more authority to these narratives.

Here is one example of how credibility-lending can work: McKinsey says 60 percent of occupations would have 1/3 of their activities automated by “AI.” Let’s be real. McKinsey says this because it sells consulting services to firms and wants executives in those firms to believe they will be soon be dealing with a radically transformed environment. In other words, McKinsey wants to scare the shit out of us.

Then NYU’s AI Now Institute cites McKinsey’s report as a credible source (it wasn’t one) and says that policymakers should take it seriously and put money into examining the problems it identifies. “AI” startups making pitch decks and journalists writing hype-y articles about fantastic changes just over the horizon can now cite something published out of NYU. The narrative has become more plausible and compelling.

We need sound information for all aspects of life and culture, including decisions made by business leaders, policymakers, and citizens participating in democracy. For example, as a society, we experience real opportunity costs when policymakers waste their time dreaming up solutions to massive job displacement from “AI” when it isn’t coming. Indeed, friends of mine working in policy in Washington, D.C., believe that criti-hype is just as damaging as positive hype from boosters when it comes to decision-making.

This leads to our second problem: criti-hype distracts us from real world problems and suffering that are happening right now. Recently, I wrote a post synthesizing a picture of technology and the US economy that I have picked up reading work from multiple fields up over the past five year. In that picture, economically-significant technological change has been slower since 1970 than in the preceding period, digital technology has never had the economic impacts its boosters said it would, and, for a variety of reasons including globalization, many people, especially those without college degrees, have little-to-no access to good jobs. Moreover — despite the hype about, like, apps — nothing about current technological change is likely to change any of these economic conditions soon.

While writing the post, I keep wondering to myself: why have so few people from my own field contributed to the understanding of these issues? There are lots of reasons for this gap, I think, including what topics are popular and faddish, but it seems to me that one important reason is that so many people in my field are looking at “emerging technologies.”

Generally every person working on the “anticipatory governance,” “sociotechnical imaginaries,” or [add your own crappy neologism here] of an “emerging technology” isn’t doing deep academic research into an existing technological problem. It’s an enormous opportunity cost. It is outrageous that I can point to gobs of people in my field working on synthetic biology, “AI,” self-driving cars, and blockchain but not a single person researching septic tanks, mobile homes, trailer parks, or even housing more generally, even though these latter topics are full of technological issues and true human suffering that IS HAPPENING RIGHT NOW.

In some ways, it is another version of an argument that Andy Russell and I made in The Innovation Delusion: innovation-speak distracts us from ordinary problems of technology and infrastructure, including maintenance, repair, and mundane labor. We need to be more honest and reflexive about how innovation-speak has shaped academic social science and humanities research.

(I also believe that most academic criti-hype is so poorly done and has such a short shelf-life before it rots that consuming it is actually harmful to your health. While reading the nanotechnology stuff, I hammered shots of bourbon to washdown handfuls of antidepressants and benzodiazepines. It hurt that bad.)

This leads to the one partial solution that I will consider in this post. Graduate programs should do a better job training students to question claims made around technologies. Our students should be bullshit detectors and hype slayers. Historian of science and mathematics Michael Barany put it this way:

In my experience, young people enter graduate programs enthusiastic about some pretty unrealistic and dramatic visions of near-term technological change, even including things as ridiculous as the singularity and transhumanism. Nuanced understanding of the history, sociology, and economics of technology is good medicine for this condition. A lot of claims about the revolutionary potentials of present technology will appear silly if you know how technology and society have and have not changed from, say, 1850 to the present. We can begin to improve things by pointing graduate students to technologies that have fully-emerged, that have diffused into society, and that have and are creating real problems and actual agonies.

But we shouldn’t be optimistic. Universities will continue turning out criti-hype and producing graduates who do it because it is so lucrative. I know of several academic criti-hypers in the USA and Europe training graduate students to do similar work at this very moment. Criti-hype is one of those phenomena that it’s important to be mindful of but not kid ourselves we’ll be free of it. There’s too many lousy incentives at play, it won’t go away.

This post is drawn from a longer essay I’m writing titled “Don’t Believe the Hype!: Anticipatory Governors and the Political Economy of STS,” which examines how parts of my professional field developed a business model of overplaying the risks of “emerging technologies” to score money from national science and engineering bodies, private foundations, and industry.

I do technology studies, co-organize @The_Maintainers, and profess Science, Technology, and Society at Virginia Tech.

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