Big Tech Isn’t Watching You, It’s Making You Feel Seen!

Reid Hoffman & Greg Beato’s SUPERAGENCY

REID HOFFMAN, CO-FOUNDER OF LINKEDIN, AND TECH WRITER, GREG BEATO recently published their enthusiastic defense of AI & LLMs Superagency: What Could Possibly Go Right with Our AI Future (Authors Equity). A response to the zeitgeist of distrust in AI, the book works to assuage fears about its rapid advancement. The authors try to tamp down panic about possible wide-spread job losses. They protest the innocence of leading AI companies, now under fire. If you haven’t read about it, multiple lawsuits have been brought by media companies, organizations and individuals for massive copyright infringement. The substitutive products built on this data now pose an existential threat to the global media ecosystem.

Above all, Superagency is a techno-optimist effort to calm anxieties about the potential loss of human agency. It’s not the end of agency, they say, but the beginning. Like the printing press, the telephone, the automobile, the internet, they claim AI will catapult us into the next phase of modernity offering humanity—superagency.

To counter the idea that AI’s surveilling you, threatening free-will, free thought and expression, Hoffman and Beato talk about George Orwell’s 1984, dedicating a chapter to framing the novel as a dated text, published as it was in 1949. They insist that “multiple generations” have been wrongly “prophesying an apocalypse that’s just around the corner.”

To support this idea, they engage in a thought experiment derived from 1984, that old wives’ tale. They drop Winston Smith into a street in present-day Manhattan where he’d never have imagined such a massive show of self-expression:

[T]ry to imagine the overwhelm that Winston Smith … would experience if you dropped him in the streets of contemporary Manhattan. The kaleidoscopic storefronts alone might knock him into an uncomprehending stupor. Then add the dizzying presentations of self, the bold displays of personal intimacies and enthusiasms that have nothing to do with the ruling party. The giant billboards filled with images of people who aren’t Big Brother. The smartphones that people clutch to their hearts like cherished talismans.

Hoffman and Beato, brilliant tech minds, are somehow unable to apply the metaphor of Big Brother to the manipulations of consumer culture that bombard everyone on the streets of New York. Every conceivable surface in the city is a constant, kaleidoscopic effort to hijack your mind, grab your attention, trigger your insecurities, and get you to buy, buy, buy. Colossal video displays pulse dizzying brand images at you, trying to burn corporate identities into your eyes, your mind, your hearts, to forever addict you to a lifetime of loyalty in the form of daily habits you mistake for your very own choices, your own decisions, such as clutching your smartphone to your chest like a cherished talisman. Every bit and byte of Manhattan is commanded by the ruling party: Big Business, or more appropriately, Big Tech. No one’s hiding Big Tech’s position.

On their own podcast, Possible, the authors invoke the same thought experiment, but this time, poor Winston is dropped into the middle of Beijing. Here, Beato again questions the constant cultural invocation of Orwell:

‘Oh, this Orwellian hellscape we’re living in’ [is] invoked so much… and I’m like, the world of 1984 is nothing like the world of 2024. And Winston Smith … could walk down the street of Beijing, even, let’s say, and be like, ‘Oh my God, what a free expression utopia,’ compared to what the world in 1984 is depicted.

He can’t possibly understand what he’s saying. The image is startling, though. Imagine a contemporary Winston Smith marveling at the great freedoms of expression available to him were he to walk down the streets of Beijing shouting, “Down with Xi Jinping!” or, perhaps worse, simply being caught as a Muslim Uyghur. He’d be disappeared to the high-tech penal region of Xinjiang and placed in a CCP re-education camp for a “life behind ‘the black gate,’ a euphemism frequently used … to refer to the camps” (Byler, Darren; In the Camps: China’s High-Tech Penal Colony, 2021, Columbia Reports). The poet Tahir Hamut Izgil, one of the only prominent intellectuals to make it out of China since the internments began, published a harrowing tale about his and his family’s experience before they were able to escape. Waiting to Be Arrested at Night (Penguin Press, 2023) is a haunting account of a present-day 1984. If Orwell is too outdated to offer insight to the hypermodern world on how surveillance tech and authoritarianism can and is being used, I recommend both of these.

Happily, Hoffman and Beato aren’t in China and, to give them the benefit of the doubt, not too many folks in the west, or anywhere, are paying attention to what’s happening in Xinjiang. The Chinese do make it pretty hard. But it’s harder to believe that these authors aren’t aware of the powerful workings of consumerism combined with data-science.

For ages, the advertising business has used tricks of language and mesmerizing images to deliver messages in ways that compel the vulnerabilities of the human mind. Today, advertising and marketing is powered by the speed of machine learning coupled with data-science. It’s not sci-fi. It’s Big Business.

Shoshana Zuboff shone an inescapable flood light on ‘surveillance capitalism’ in her book, The Age of Surveillance Capitalism (Public Affairs, 2019). Hoffman and Beato try to turn the idea on its head claiming Big Business isn’t watching you. It’s making you feel seen.

They write:

The new capacity to aggregate and analyze vast amounts of consumer data gave manufacturers, marketers, and content creators the power to segment markets, target more granular demographics, and cater to specific subcultures, lifestyles, and interests in ways that could never happen in the pre-computer age…. It was the beginning of a more diverse and inclusive world based on comprehensive knowledge. Big Brother, or, perhaps more appropriately, Big Business, wasn’t watching you so much as making you feel seen.

You poor, invisible masses, lost in obscurity. All of you who are withering in anonymity, clamoring in vain for a voice, to be heard, to be seen, your prayers have finally been answered! We aren’t watching you, we aren’t surveilling you. Nay. We SEE you. We see you. (Sniff.)

If these authors had their way, they might update the closing lines of Orwell’s masterpiece to read “But it was all right, everything was all right, the struggle was finished. [Winston] had won the victory over himself. He loved Big Brother Tech.”

AND YET, THERE WERE TALENTED BOOK PEOPLE BEHIND THIS BOOK. Superagency was published by Authors Equity, founded last March by a few legends of the book world, Madeleine McIntosh, former CEO of Penguin Random House, Don Weisberg, former CEO of Macmillan, Nina Von Moltke, former president of strategic development at PRH, and James Clear, author of Atomic Habits.

In an early post on the company’s own Substack, Fair Share, McIntosh cites the “tectonic shifts” publishing has weathered remarkably well “compared to other media.” But a new landscape had arrived that called for change. In the past, McIntosh writes, “readers were influenced to buy particular books by the forces of mass media and mass distribution. In that world, publishers held the unique power to decide which books and authors would win.” Today, she says, we live in “a world without mass media.” That statement confused me, at first. Mass media hasn’t vanished. But it struck me that what she meant translates into my own lingo as: the media universe has been atomized.

There are mass distribution points, like The New York Times, The Wall Street Journal, WaPo, The New Yorker, New York Magazine, The Atlantic, and the like. But the slots available for book coverage are very hard to land. A firehose of new books is constantly being pitched at those venues. They’re competing for readers’ eyeballs and tend to select big name authors, celebrities, or books with attention-grabbing topics that adhere to the unpredictable themes around current affairs.

There are countless smaller digital publications with book coverage slots, a growing menu of social media platforms within which are an ever-growing population of influencers. There are a galaxy of podcasts on several platforms, along with the video platforms, like YouTube and TikTok. There are a growing set of newsletter platforms, like this one, and the demand to leverage data-driven marketing solutions to track, analyze, and optimize for discoverability at every point of distribution.

In this light, if you read the quote above from Superagency on the capacity to analyze vast amounts of consumer data, the power to segment markets, target more granularly, etc., you understand it’s less of an inclusive world that sees authors and more of a world that makes talented authors much harder to be seen amidst oceans of content. Authors, alone, have a hard time getting traction in this atomized media universe unless they also happen to be talented and disciplined marketers who have the time and expertise to cut through the cacophony of content.

McIntosh writes that without the ability to use mass media in the way they had in the past, publishers “lost the power to uniquely influence the consumer.” In sum, she writes, “In the new market, it’s about the author. What they put on the page, and how they break through the noise to capture reader attention: that’s what makes the difference.” Their new venture, thusly, works differently than the traditional model, in recognition of how much of the responsibility has shifted to author-engagement. I myself haven’t worked with AE, so can’t say how they work exactly or if it’s working well. But the model is founded on profit-sharing and a small, collaborative team that the author is a key part of. They also appear to be leveraging the use of AI in ways that don’t offend their literary hearts and minds.

AS IF THE ATOMIZATION OF MEDIA WASN’T ENOUGH, large language models (LLMs) have made life even harder for writers. LLMs, like ChatGPT, have upended the business models of companies that had previously been mass media distribution points, like The Atlantic, Vox Media, The New York Times. LLMs have thrown a wrench in the works of all media outlets that, since the turn of the 21^st century, had relied, symbiotically, on digital traffic from search engines like Google.

In an interview with Bob Safian in December of 2024, Nicholas Thompson, CEO of The Atlantic, aptly describes LLMs as replacing “search engines,” like Google, with “answer engines,” like ChatGPT. Instead of directing traffic to the content the user has searched for, LLMs scrape original content from outside sources and provide answers. They were neither directing traffic to the original source, nor citing it. Stopping the flow of traffic to media sites poses a clear problem for companies like The Atlantic, and puts the entire media industry in danger.

At the end of 2023, The New York Times sued OpenAI and its key investor, Microsoft. The suit “contends that millions of articles published by The Times were used to train automated chatbots that now compete with the news outlet as a source of reliable information.” In April of 2024, a group of eight newspapers owned by Alden Global Capital, the second largest newspaper operator in the US, including The Daily News, The Chicago Tribune and The Denver Post, also sued Microsoft and OpenAI, claiming “the chatbots regularly surfaced the entire text of articles behind subscription paywalls for users and often did not prominently link back to the source.”

Thompson has been a key public proponent of finding a jointly lucrative path for media companies and AI pioneers, like OpenAI. In the spring of 2024, The Atlantic chose to make a licensing deal directly with OpenAI. It was perceived by some as risky. OpenAI could pilfer their data for the term of the contract and then leave them in the dust, legally unscathed, with their LLM improved. Talking with Axios’s Sara Fischer on a panel in Davos last month, Thompson answered a question about the rationale. “Trying to build ethics into an AI system that was built on stolen data is complicated,” he said, and he laid out the options media companies have. In sum: you can sue, you can make a deal, or you can change the whole structure. Thompson chose to make a deal in recognition of the need, going forward, to find “a fair exchange of value” for high-quality writing.

The press release describes a partnership in which OpenAI was granted a license to use content from The Atlantic as long as that content was cited and linked to. The two companies were also joining forces on something of an innovation incubator to create “new products and services to better serve its journalism and readers.” As Thompson said to Safian at the end of last year, “If OpenAI ultimately is able to build an answer engine that also drives readership directly to products created by media organizations that is a much better future for media.” Leading LLMs have recently begun to nominally provide linked citations, but both the ‘answers’ summarized from original sources and what are very subdued links (easy for users to miss), remain a problematic digital dam for the flow of traffic to media sites.

In lieu of the kind of pure “permissionless innovation,” Hoffman and Beato advocate for in which tech takes whatever they want whenever they want, the media industry needs innovations that have a fair exchange of value at their core. We need more thought-leaders like Thompson and McIntosh, both of whom are spearheading efforts to face, name and strategize around the obstacles Big Tech and AI pose. Costly lawsuits are necessary to clarify what the law is in this data-driven wild west, but the suits look more and more like fool’s errands if the aim is to stop Big Tech in their tracks. Thompson and McIntosh are wisely trying to understand the situation and are actively looking for and engaging in opportunities to navigate or innovate a way through.

Superagency is more of a book-length puff piece for AI’s rapid advancement than a seriously considered book presenting new, actionable thought-leadership to those for whom the rise of AI poses a very real problem. The book’s blurbers comprise an A-list of gurus from the high temples of artificial intelligence who benefit from the success of a hardcover product-placement for AI like this. Authors Equity may have published the thing, but I remain applauding McIntosh’s effort to co-found and lead a publishing venture that tries to plot a new course. I applaud Thompson, as well, in his effort to partner with Big Tech and even more so for what seems a personal and public mandate to have conversations with and influence the way in which Big Tech thinks about integrating AI into human systems.

There’s no turning back from this historic innovation, but we all have to be on Team Human. It’s worth repeating Thompson: “Trying to build ethics into an AI system that was built on stolen data is complicated.” In the interest of maintaining a healthy economy that prioritizes good journalism, good writing and critical thought, we have to prioritize “a fair exchange of value.” {∞}