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think we can view the promotion of ed-tech as a similar sort of process — the stories designed to convince us that the future of teaching and learning will be a technological wonder. The "jobs of the future that don't exist yet." The push for everyone to "learn to code."

The Matrix is, after all, a dystopia. So why would Matrix-style learning be desirable? Maybe that's the wrong question. Perhaps it's not so much that it's desirable, but it's just how our imaginations have been constructed, constricted even. We can't imagine any other ideal but speed and efficiency.

The first science fiction novel, published over 200 years ago, was in fact an ed-tech story: Mary Shelley's Frankenstein. While the book is commonly interpreted as a tale of bad science, it is also the story of bad education — something we tend to forget if we only know the story through the 1931 film version

Teaching machines and robot teachers were part of the Sixties' cultural imaginary — perhaps that's the problem with so many Boomer ed-reform leaders today. But that imaginary — certainly in the case of The Jetsons — was, upon close inspection, not always particularly radical or transformative. The students at Little Dipper Elementary still sat in desks in rows. The teacher still stood at the front of the class, punishing students who weren't paying attention.

we must also decolonize the ed-tech imaginary

Zuckerberg gave everyone at Facebook a copy of the Ernest Cline novel Ready Player One, for example, to get them excited about building technology for the future — a book that is really just a string of nostalgic references to Eighties white boy culture. And I always think about that New York Times interview with Sal Khan, where he said that "The science fiction books I like tend to relate to what we're doing at Khan Academy, like Orson Scott Card's 'Ender's Game' series." You mean, online math lectures are like a novel that justifies imperialism and genocide?! Wow.

This ed-tech imaginary is segregated. There are no Black students at the push-button school. There are no Black people in The Jetsons — no Black people living the American dream of the mid-twenty-first century

Part of the argument I make in my book is that much of education technology has been profoundly shaped by Skinner, even though I'd say that most practitioners today would say that they reject his theories; that cognitive science has supplanted behaviorism; and that after Ayn Rand and Noam Chomsky trashed Beyond Freedom and Dignity, no one paid attention to Skinner any more — which is odd considering there are whole academic programs devoted to "behavioral design," bestselling books devoted to the "nudge," and so on.

so much of the ed-tech imaginary is wrapped up in narratives about the Hero, the Weapon, the Machine, the Behavior, the Action, the Disruption. And it's so striking because education should be a practice of care, not conquest

Almost 69 percent of social referrals were dark! Facebook came in second at 20 percent. Twitter was down at 6 percent

if you think optimizing your Facebook page and Tweets is "optimizing for social," you're only halfway (or maybe 30 percent) correct. The only real way to optimize for social spread is in the nature of the content itself. There's no way to game email or people's instant messages. There's no power users you can contact. There's no algorithms to understand. This is pure social, uncut

the social sites that arrived in the 2000s did not create the social web, but they did structure it. This is really, really significant. In large part, they made sharing on the Internet an act of publishing (!), with all the attendant changes that come with that switch. Publishing social interactions makes them more visible, searchable, and adds a lot of metadata to your simple link or photo post. There are some great things about this, but social networks also give a novel, permanent identity to your online persona. Your taste can be monetized, by you or (much more likely) the service itself

the tradeoffs we make on social networks is not the one that we're told we're making. We're not giving our personal data in exchange for the ability to share links with friends. Massive numbers of people -- a larger set than exists on any social network -- already do that outside the social networks. Rather, we're exchanging our personal data in exchange for the ability to publish and archive a record of our sharing. That may be a transaction you want to make, but it might not be the one you've been told you made. 

"Only about four percent of total traffic is on mobile at all, so, at least as a percentage of total referrals, app referrals must be a tiny percentage,"

only 0.3 percent of total traffic has the Facebook mobile site as a referrer and less than 0.1 percent has the Facebook mobile app

mechanical skill is a proper subset of the set of all tasks a student needs to master in order to really learn a subject. And a lecture, when well done, can teach novice learners how to think like expert learners; but in my experience with Khan Academy videos, this isn’t what happens — the videos are demos on how to finish mathematics exercises, with little modeling of the higher-level thinking skills that are so important for using mathematics in the real world.

The Khan Academy is a great new resource, and it's a sign of greater things to come... but it's much more akin to a book than a teacher.

“We call on the field to recognize that applications that aim to believably mimic humans bring risk of extreme harms,” she co-wrote in 2021. “Work on synthetic human behavior is a bright line in ethical Al development, where downstream effects need to be understood and modeled in order to block foreseeable harm to society and different social groups.”

chatbots that we easily confuse with humans are not just cute or unnerving. They sit on a bright line. Obscuring that line and blurring — bullshitting — what’s human and what’s not has the power to unravel society

She began learning from, then amplifying, Black women’s voices critiquing AI, including those of Joy Buolamwini (she founded the Algorithmic Justice League while at MIT) and Meredith Broussard (the author of Artificial Unintelligence: How Computers Misunderstand the World). She also started publicly challenging the term artificial intelligence, a sure way, as a middle-aged woman in a male field, to get yourself branded as a scold. The idea of intelligence has a white-supremacist history. And besides, “intelligent” according to what definition? The three-stratum definition? Howard Gardner’s theory of multiple intelligences? The Stanford-Binet Intelligence Scale? Bender remains particularly fond of an alternative name for AI proposed by a former member of the Italian Parliament: “Systematic Approaches to Learning Algorithms and Machine Inferences.” Then people would be out here asking, “Is this SALAMI intelligent? Can this SALAMI write a novel? Does this SALAMI deserve human rights?”

Tech-makers assuming their reality accurately represents the world create many different kinds of problems. The training data for ChatGPT is believed to include most or all of Wikipedia, pages linked from Reddit, a billion words grabbed off the internet. (It can’t include, say, e-book copies of everything in the Stanford library, as books are protected by copyright law.) The humans who wrote all those words online overrepresent white people. They overrepresent men. They overrepresent wealth. What’s more, we all know what’s out there on the internet: vast swamps of racism, sexism, homophobia, Islamophobia, neo-Nazism.

One fired Google employee told me succeeding in tech depends on “keeping your mouth shut to everything that’s disturbing.” Otherwise, you’re a problem. “Almost every senior woman in computer science has that rep. Now when I hear, ‘Oh, she’s a problem,’ I’m like, Oh, so you’re saying she’s a senior woman?”

“We haven’t learned to stop imagining the mind behind it.”

In March 2021, Bender published “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” with three co-authors. After the paper came out, two of the co-authors, both women, lost their jobs as co-leads of Google’s Ethical AI team.

“On the Dangers of Stochastic Parrots” is not a write-up of original research. It’s a synthesis of LLM critiques that Bender and others have made: of the biases encoded in the models; the near impossibility of studying what’s in the training data, given the fact they can contain billions of words; the costs to the climate; the problems with building technology that freezes language in time and thus locks in the problems of the past. Google initially approved the paper, a requirement for publications by staff. Then it rescinded approval and told the Google co-authors to take their names off it. Several did, but Google AI ethicist Timnit Gebru refused. Her colleague (and Bender’s former student) Margaret Mitchell changed her name on the paper to Shmargaret Shmitchell, a move intended, she said, to “index an event and a group of authors who got erased.” Gebru lost her job in December 2020, Mitchell in February 2021. Both women believe this was retaliation and brought their stories to the press. The stochastic-parrot paper went viral, at least by academic standards. The phrase stochastic parrot entered the tech lexicon.

Tech execs loved it. Programmers related to it. OpenAI CEO Sam Altman was in many ways the perfect audience: a self-identified hyperrationalist so acculturated to the tech bubble that he seemed to have lost perspective on the world beyond. “I think the nuclear mutually assured destruction rollout was bad for a bunch of reasons,” he said on AngelList Confidential in November. He’s also a believer in the so-called singularity, the tech fantasy that, at some point soon, the distinction between human and machine will collapse. “We are a few years in,” Altman wrote of the cyborg merge in 2017. “It’s probably going to happen sooner than most people think. Hardware is improving at an exponential rate … and the number of smart people working on AI is increasing exponentially as well. Double exponential functions get away from you fast.” On December 4, four days after ChatGPT was released, Altman tweeted, “i am a stochastic parrot, and so r u.”

“This is one of the moves that turn up ridiculously frequently. People saying, ‘Well, people are just stochastic parrots,’” she said. “People want to believe so badly that these language models are actually intelligent that they’re willing to take themselves as a point of reference and devalue that to match what the language model can do.”

The membrane between academia and industry is permeable almost everywhere; the membrane is practically nonexistent at Stanford, a school so entangled with tech that it can be hard to tell where the university ends and the businesses begin.

“No wonder that men who live day in and day out with machines to which they believe themselves to have become slaves begin to believe that men are machines.”

what’s tenure for, after all?

LLMs are tools made by specific people — people who stand to accumulate huge amounts of money and power, people enamored with the idea of the singularity. The project threatens to blow up what is human in a species sense. But it’s not about humility. It’s not about all of us. It’s not about becoming a humble creation among the world’s others. It’s about some of us — let’s be honest — becoming a superspecies. This is the darkness that awaits when we lose a firm boundary around the idea that humans, all of us, are equally worthy as is.

The AI dream is “governed by the perfectibility thesis, and that’s where we see a fascist form of the human.”

“Why are you trying to trick people into thinking that it really feels sad that you lost your phone?”