Introduction from Jon Haidt and Zach Rausch:

A year and a half ago, we teamed up with Lennon Torres, senior campaign manager at The Heat Initiative and LGBTQ+ advocate, to write an article for The Atlantic, “Social-Media Companies’ Worst Argument” (reposted here with no paywall). Together, we refuted the social media companies’ claims that using these platforms is net-positive for teens in historically disadvantaged communities and that regulation would do more harm than good for adolescents in these groups.

Since then, however, these claims have continued to surface as an argument against regulation. In the below piece, originally published by The Hill, Lennon draws on her own experience as a trans woman who grew up sharing her life on social media. She argues that the social media companies use LGBTQ+ kids as an excuse to avoid accountability and reminds the public that despite what the companies claim, “queer people are the ones these platforms fail first and protect last.”

Thank you to Lennon and The Hill for allowing us to share this piece directly with After Babel’s readers. We hope you’ll read it and share it widely.

– Jon & Zach

Don’t Let Big Tech Hide Behind a Rainbow Flag

With Big Tech companies recently losing two key lawsuits over the harm they do to youth — both in rulings they have promised to appeal — a false narrative has begun to re-circulate. The claim is that requirements making digital communities safer for young people will somehow undermine queer expression.

Here is my message, coming from a transgender woman who grew up with and was badly harmed by exploitative social media: Do not let Big Tech hide itself behind a rainbow flag. The truth is, queer people are the ones these platforms fail first and protect last.

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Many gay, transgender and queer kids lack supportive families and affirming schools. To them, digital spaces may seem like a lifeline — a place where they can be themselves. Unfortunately, those digital spaces are often built on the same logic that once targeted kids with cigarettes: Maximize use, minimize accountability and monetize vulnerability. These platforms were designed not to empower us but to get and keep us hooked.

In the social media addiction trial that recently wrapped up in Los Angeles, plaintiff attorney Mark Lanier asked Meta whistleblower Arturo Béjar how Facebook’s leadership dealt with the issue of “addiction.” Béjar replied: “They changed the name of it” — specifically, they stopped calling it “addiction” and called it “problematic use” instead. He added, “You couldn’t talk about it.”

I joined social media at age 13, just as the iPhone became the center of adolescent life. I was attending a performing arts school after five years at a public school where I was teased for being too feminine. I turned to Instagram, Facebook, Snapchat, and YouTube — platforms that gave me access to a community I had never had. But this came with life‑threatening side effects I couldn’t yet see clearly.

Online, I found attention — first from classmates, then from strangers. When I started working professionally as a dancer, hundreds of thousands of followers watched my every move. What felt at first like affirmation quickly became the only place I thought I had value. I got so consumed with how I was being perceived that authenticity didn’t stand a chance.

At some point, it stopped mattering whether the comments were praise or cruelty — what mattered was the hit. I began refreshing comments in bathroom stalls between classes and rehearsals, scrolling before bed and learning how to curate myself for algorithms I didn’t understand. The behavior was compulsive. I didn’t know to call it “addictive design” — I just knew I couldn’t stop scrolling.

Chasing the algorithm for validation wasn’t the only risk. The real danger often arrived in my private messages. Adults I didn’t know approached me with explicit messages and nude images. I was only 13, and I did not yet understand what grooming was. I did not have the language for it — I only knew that the attention I could not find offline seemed to appear online.

I know now that the platforms and their algorithms were delivering me up to these predatory strangers, serving them my profile as engagement bait.

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The Los Angeles lawsuit pointed to Internal Meta documents showing that Instagram’s “Accounts You May Follow” feature1 actively connects predatory adults to minors: “In 2023, this tool recommended to adult groomers ‘nearly 2 million minors in the last 3 months’ — and ‘22 percent of those recommendations resulted in a follow request.’”

Employees warned leadership. Leadership rejected fixing the system, maintaining a 17-strike policy for predators — including sex-traffickers — before suspending the offenders’ accounts.

The architecture of these platforms placed me in the path of adults who saw opportunity in a lonely queer kid. Because queer kids come to online spaces for identity and survival, we are the ideal product: highly engaged, highly vulnerable and highly profitable.

Big Tech claims to defend queer kids’ rights by opposing regulations like requiring age-appropriate design and limits on addictive features. In reality, they are using us as a shield to avoid accountability. They weaponize our dependence on online connection to argue that any safety guardrail is “anti‑LGBTQ.” They warn lawmakers that protecting kids will erase queer expression. This is a lie, and a strategic one.

In reality, features that harm young people — endless scroll, autoplay, compulsive engagement loops, recommendation pipelines driven by surveillance data, settings that expose kids to ill-intentioned adult strangers — do not create queer communities. They create dependency. They bury our identity in algorithms optimized for outrage, objectification and profit.

Queer kids do not need online platforms that claim to celebrate us in Pride campaigns while exploiting and exposing us to harassment at disproportionate rates. We need them to prioritize our safety and mental health.

I know this because I lived it. Only after a decade of anxiety, addictive patterns, algorithmic harm, grooming, and harassment could I finally withdraw from exploitative social media. Even then, the choice felt impossible. Most of my childhood had unfolded online. The most intimate parts of my life — my gender transition, top surgery, and coming out — became content opportunities to me. That is the cruelty of these platforms: They teach you to equate visibility with safety, engagement with belonging, and exploitation with connection.

Regulation is not a threat to queer expression but a prerequisite for queer safety. It won’t solve every problem, but it will do the first and most important thing: force the companies profiting from our attention to finally take responsibility for the harm they have caused.

Reprinted with permission from The Hill.

Two weeks ago, on March 25, a jury in Los Angeles found Meta and Google liable in a landmark case. The jurors determined that the parent companies of Instagram and YouTube had acted with “malice, oppression, or fraud,” addicting and harming the young plaintiff, known as KGM.

Just one day prior, a jury in New Mexico found Meta liable for “misleading consumers about the safety of its platforms and endangering children.”

Many kinds of evidence were presented to the juries, from internal documents and research done by the companies themselves to testimony from experts and former employees. The evidence revealed that the companies had intentionally designed their products in ways they knew would harm children.

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The companies used a two-pronged defense strategy. First, they blamed others: It was KGM’s fault for opening accounts before she was 13. It was her parents’ fault that she got addicted and depressed. Whatever harm happened, we’re just a neutral platform! The jury did not respond well to this strategy.

Second, they claimed that there is no scientific evidence that their platforms cause harm to adolescent mental health. Mark Zuckerberg has repeatedly asserted that the academic evidence is merely correlational. He grants that heavy users are more depressed, but notes that correlational evidence cannot prove that social media caused their depression.

There are thousands of similar cases coming, and we can be confident that the companies will lean hard into this strategy: denying any scientific evidence of causation. When making such claims, defenders of social media usually refer to an essay in Nature that made similar assertions. But as we showed in The Anxious Generation, and in our academic articles and many posts here on After Babel, there is abundant scientific evidence of causation. We are writing this post to make it easier for everyone to learn about that evidence.

The editors of The World Happiness Report (WHR) recently asked us to put all of the evidence together. The annual report shows how countries vary on measures of well-being. Each year there is a special topic or focus, and for the 2026 report, the focus was on social media’s effects on well-being. We wrote the target essay laying out the case for harm, and other authors brought a variety of perspectives.

Knowing that thousands of jury trials were on the horizon, we laid out our argument like a hypothetical civil trial, asking our imagined jury this question: Are social media platforms dangerous consumer products whose design has led to a variety of harms to young people? We call this the Product Safety Question. We present seven lines of converging evidence showing that these platforms are causing harm.

At the end of our chapter, we show that the levels of harm uncovered while answering the Product Safety Question are so high that we can also answer a different but related question: Are social media platforms causing harm to entire populations? We call this the Population Harm Question, and it’s at the center of some states’ and school districts’ cases.

Taking the Companies to Trial

In our hypothetical case against the companies — particularly Instagram, TikTok, and Snapchat — we begin with the apparent victims, the people who allege harm: Gen Z, the cohort born roughly between 1996 and 2011. They were the first generation to go through puberty with social media in their pockets, accessible at all times through smartphones beginning in the early 2010s. They have the clearest view of what happened to them and their peers.

We then turn to those who spend the most time with young people — parents, educators, and clinicians. They also witnessed the effects of social media across many young people, over many years.

If we could call all of these groups to the stand, what would they say? We offer a brief synopsis of each line of evidence below. You will find far more detail in our WHR chapter.

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Line 1: What the Victims Say

Across surveys in multiple countries, many young people report that social media has harmed them directly and indirectly. They describe widespread experiences of cyberbullying, sexual exploitation, sleep disruption, lower confidence, and worse mental health. They also express strikingly high levels of regret toward the major platforms they have used for years. In a Harris Poll survey of members of Gen Z, nearly half reported that they wish that TikTok, X (Twitter), and Snapchat were never invented — despite using those platforms for several hours a day.

Internal surveys conducted by Meta found similar results. In their own research, they found that “teens blame Instagram for increases in the rates of anxiety and depression among teens.” One in three teen girls said Instagram made their body-image issues worse (20% said it made it better); and 13% of adolescents reported unwanted sexual advances on Instagram in the previous seven days.

In a courtroom, it is powerful when a victim points to the defendant and says “he did it.” In survey after survey, and in open-ended interviews, Gen Z points to social media platforms as the culprit.

Of course, the victims in a court case could be mistaken or could be lying, so direct positive identification is strengthened when corroborated by eyewitness testimony. The same logic applies here, so let’s move to our second line of evidence and call a variety of witnesses to the stand.

Line 2: What the Eyewitnesses Say

We next turn to the adults who spend the most time with young people. Parents describe changes in their children’s mood, sleep, self-esteem, and friendships; teachers report worsening distraction, attention, and academic performance; and clinicians say social media is exacerbating anxiety, depression, and addiction-like behavior in their young clients.

A 2025 Pew survey of U.S. teens and their parents found that 44% of parents identified social media as the single most negative influence on teen mental health, ahead of “technology generally.” Similarly, the 2025 UK survey by More in Common asked parents to identify what most negatively affects their own children’s mental health. The top response was “social media use/excessive screen time,” followed by concerns closely linked to digital technology, including exposure to harmful online content, bullying, low self-esteem, and lack of sleep.

In our own Harris Poll survey, majorities of parents said that, when thinking about their own children, they wished the major social media platforms had never been invented. And according to findings disclosed in litigation, Meta’s own research found that large majorities of clinicians believed social media worsens anxiety and depression in adolescents.

Line 3. What Company Insiders Say

The attorney for the plaintiff might then call the defendant to the stand and turn to the direct evidence. Suppose, for example, that the attorney had obtained, through pre-trial discovery, a series of text messages from the defendant describing what he was planning on doing, and then, afterward, talking about what he had done.

In our case against the social media companies, we have the equivalent of hundreds of such text messages in the form of internal company emails, messages, memos, documents, presentations, and more.

Here are just a few of the quotations from internal documents revealing what company insiders — employees as well as external consultants hired to offer advice — believed.

These quotes barely scratch the surface of what the internal documents reveal, and we cover more from this line of evidence in our WHR chapter. You can also find a large selection of disturbing quotations at TechOversight.org, and you can find our compilation of 35 studies carried out by Meta at MetasInternalResearch.org.

The evidence is clear: The companies and their leaders knew from their own research that they were harming millions of children and adolescents. As former Facebook president Sean Parker said, they knew what they were doing, and they did it anyway.

These three lines of evidence taken together, we believe, answer the Product Safety Question and demonstrate that these products are not safe for minors. Few parents who knew about the above evidence would want their children to continue using these products. That may be why many tech executives do not let their children use their own products: they know. But there’s no need to stop here; the forensic evidence further strengthens our case.

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The Forensic Evidence

In Lines 4 through 7 of the evidence, we focus on the heart of the academic debate over social media’s effects: whether heavy social media use (~5 or more hours per day) is causing internalizing disorders (such as anxiety and depression) among adolescents (especially girls).1 There is wide agreement among academic researchers that heavy users of social media are more likely to be depressed and anxious than light users, but does that mean that social media causes those outcomes, or is it merely correlated with them? The claim that it is mere correlation is at the heart of the social media companies’ legal defense strategy.

To address that question, we examine the four major bodies of academic research in turn: cross-sectional studies, longitudinal studies, randomized controlled trials of social media time reduction, and natural experiments.

At this point in our case, we are calling on the forensic experts to give their scientific analysis and opinions of the evidence, which can help connect the defendant to the alleged harm. In a criminal trial, this might be a ballistics or DNA expert; in our case, we’re calling the academic researchers to the stand. They’ve studied social media and internalizing disorders in teens for more than a decade, and though their access to data is more limited than that of the companies, their expert analysis consistently links the defendants to the alleged harm.

Line 4. Cross-sectional Studies

The largest body of academic evidence is cross-sectional, which means that data is collected at a single time (as with a survey), with no experimental manipulation. While these studies cannot establish causation on their own, they are an important starting point: they ask whether heavy users of social media are in worse mental health than light users or non-users. Across hundreds of studies, the answer is generally yes. The main point of contention, however, is not whether an association exists, but how seriously to take it.

In one of the most informative studies, Kelly et al. (2019) analyzed data from 10,904 14-year-olds in the UK Millennium Cohort Study and found that adolescents who spent five or more hours a day on social media were about twice as likely to meet criteria for depression as those who used it for less than one hour a day. Among girls, the relative risk was even higher at 2.65 — comparable to sleep deprivation and online harassment, and larger than the risk elevation associated with poverty.

Additional studies reinforce this conclusion. These elevated risk findings were central to the U.S. Surgeon General’s warnings in 2023 and 2024.

Even the studies that our critics cite as finding “no association” between social media use and internalizing disorders in teens look much more concerning when the data is analyzed more carefully, as we show in Exhibit J of our WHR essay. In many cases, researchers blend together variables — for example, different technologies (e.g., email and social media), different outcomes (e.g., general feelings of wellbeing and anxiety), or different populations (e.g., adults 18+ and teen girls) — in ways that dilute the relationship at the center of the debate: heavy social media use associated with internalizing disorders, especially among adolescent girls. Analyses that unblend these categories almost always reveal that heavy teen social media users — and especially girls — are at substantially elevated risk for depression and anxiety. (See Haidt & Rausch, preprint for a deeper examination of blending).

Cross-sectional studies consistently show that heavy adolescent social media users are at substantially elevated risk for depression and anxiety. Next, we turn to the longitudinal studies, which help address the question of temporal order.

Line 5. Longitudinal Studies

The longitudinal literature on social media and mental health allows researchers to follow individuals over time and can help clarify whether social media use predicts subsequent changes in mental health, whether poor mental health predicts subsequent social media use, or some combination of the two. The available longitudinal studies present clear and consistent evidence that social media use predicts later depression.

The strongest evidence comes from recent large-scale studies. An analysis of a sample of 6,595 U.S. adolescents, ages 12–15, found that heavy social media use predicted later increases in internalizing symptoms. Another study, using the longitudinal Adolescent Brain Cognitive Development (ABCD) dataset, showed that increases in social media use predicted subsequent increases in depression. Meanwhile, other researchers using the ABCD dataset showed that earlier internalizing disorders failed to predict subsequent social media use.

Some studies also find bidirectional relationships (i.e., higher social media use today predicts worse mental health a year from now, and worse mental health today predicts higher social media use a year from now), and within those studies, the forward relationship from social media use to later depression remains robust.2

In other words, this second line of forensic evidence shows that not only are heavy users of social media doing worse, at any given time (that’s the cross-sectional finding); it’s also the case that those who use more social media at one point in time are generally found to be worse off at later times.

Line 6. Randomized Control Trials of Time Reduction

The most powerful tool for measuring causation directly is an experiment that randomly assigns participants to either an intervention or to a control condition and then compares the outcomes. While researchers do not, for ethical reasons, ask one group of kids to start using social media at age 10 and another to stay off it until age 16, there are numerous experiments where young adult participants have been asked to either reduce their social media use (intervention) or continue their use as usual (control condition).

A recent meta-analysis by Burnell et al. (2025) of 32 such experiments has shown that reductions of social media use caused substantial declines in symptoms of internalizing disorders like depression and anxiety — even though most of these studies lasted only a week or two.3

The experimental results are all the more remarkable given that these studies are not designed to measure impacts that could be produced by entire communities reducing their use of social media. For example, if all students in a given school district ceased to use social media, that would leave more overall time for in-person interactions with peers and therefore the beneficial impacts on mental health could be even stronger, including for students with low levels of social media use. Furthermore, kids who do not use social media would cease to be penalized for their inability to socialize with their peers on these platforms, which in turn might help improve their mental health.

Even Meta’s own internal research confirmed evidence of benefits caused by social media reductions. In a 2020 Facebook deactivation experiment, code-named Project Mercury, Meta found that users who stopped using Facebook or Instagram for just one week reported lower feelings of depression, anxiety, loneliness, and social comparison. One internal researcher warned that keeping such findings secret would resemble the refusal by tobacco companies to admit that their own research revealed severe harms of cigarette consumption.

This sixth line of evidence is arguably the most damning: experiments using random assignment provide consistent causal evidence that when users reduce the amount of time they spend on social media, their mental health improves. The defendants themselves found this in their own internal experiments, and they tried to bury it.

Line 7. Natural Experiments

Our final line of evidence comes from natural experiments. Because high-speed internet made social media much more appealing (photos and videos would load faster), if some regions of a country got broadband connections a year or two before other areas, researchers can compare: did the mental health of young people in those early adopter regions change before those of the later regions? These studies are especially valuable because they offer population-level evidence that is not available from short-term laboratory experiments.

Across the major natural experiments we reviewed — in Germany, Italy, Spain, and the United States — the evidence indicates that the spread of high-speed internet worsened mental health, with the harms falling most heavily on young people, especially women and adolescent girls. Documented effects include declines in self-reported mental health, increases in hospital-diagnosed mental disorders, and rising suicide rates. Additional natural experiments point in the same direction.4

This final line of forensic evidence may be the most policy-relevant of all, because it allows us to examine what happened as these technologies actually spread through entire populations. It comes closest to the ideal experiment of having one group of adolescents gain access to always-available social media while another does not. And the results are again clear: as high-speed internet spread — and with it, ever-present social media — mental health outcomes worsened, especially for young people and especially for girls.'

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Harm to Millions is Harm at the Population Level

Our seven lines of evidence make it clear: the answer to the Product Safety Question is No, social media platforms are not safe for young people. These consumer products were designed — intentionally — to maximize the number of children and adolescents who would be drawn to them and the amount of time that each would spend on them. The leaders and researchers at these companies know that heavy users of social media suffer many indirect harms (mental health problems, body image issues, addiction), and that even light users are often exposed to dangerous direct harms (such as sextortion, or death from purchasing fentanyl-laced drugs, or performing a dangerous challenge).

The Population Harm Question is a different one. It is quite possible for a consumer product to be extremely dangerous and yet have no effect on the aggregate statistics of a nation. That would be the case for any product that is used by only a tiny portion of the population. But social media platforms are arguably the most widely used products among young people in the developed world, used regularly by a large majority of adolescents in the United States. In fact, a third of American adolescents say that they are on one of the major platforms “almost constantly.” So if several of the product safety concerns we have documented are affecting more than 20% of all users (as with self reports of sleep deprivation and mental health damage), that quickly adds up to a population-level effect.

When the documented direct and indirect harms are scaled to the number of young people actually using these products, the number of adolescents harmed each year likely reaches into the millions in the U.S. alone. Arturo Béjar’s internal Instagram research found that 13% of users ages 13–15 reported receiving unwanted sexual advances in the previous week — which, if the U.S. is similar to the global average, would imply that about 5.7 million adolescents experience this in any given week. This same research also found that 10.8% of Instagram users ages 13–15 reported being cyber-bullied in the previous week. The number of adolescents experiencing direct harms from social media likely exceeds 10 million each year in the United States alone. (See the subsections in our WHR chapter “Direct harm to millions” and “Indirect harm to millions” for more extensive examples and estimates).5

In other words: the answer to the Population Harm Question is very likely to be “yes.”

The evidence we have presented does not prove that any particular plaintiff is correct, and it does not mean that evidence does not exist on the other side. We have been engaged in a debate with other researchers for seven years now, and you should read their arguments to hear the other side. Scientific debates are never closed; there is always the possibility of new evidence, or of discovering new complications and interactions.

But the next time you hear Mark Zuckerberg or anyone else say that there is “no evidence” of harm, or that the evidence is merely “correlational,” send them a link to this essay, or to our full WHR chapter. There is now a great deal of evidence, from many sources (including Meta’s internal research), using many methods.

Social media companies have been harming millions of children and adolescents for many years now. Until very recently, they faced no liability for these harms, and they never faced a jury. But now the courtroom doors are finally open and the evidence is being seen — by juries and the world. As the punitive damages increase, there will be design changes to the platforms. And there will be justice.

Arizona State University rolled out a platform called Atomic that creates AI-generated modules based on lectures taken from ASU faculty by cutting long videos down to very short clips then generating text and sections based on those clips. 

Faculty and scholars I spoke to whose lectures are included in Atomic are disturbed by their lectures being used in this way—as out-of-context, extremely short clips some cases—and several said they felt blindsided or angered by the launch. Most say they weren’t notified by the school and found out through word of mouth. And the testing I and others did on Atomic showed academically weak and even inaccurate content. Not only did ASU allegedly not communicate to its academic community that their lectures would be spliced up and cannibalized by an AI platform, but the resulting modules are just bad. 

AI in schools has been highly controversial, with experiments like the “AI-powered private school” Alpha School and AI agents that offer to live the life of a student for them, no learning required. In this case, the AI tool in question is created directly by a university, using the labor of its faculty—but without consulting that faculty. 

“We are testing an early version of ASU Atomic to learn what works, and what doesn't, to further improve the learner experience before a full release,” the Atomic FAQ page says. “Once you start your subscription, you may generate unlimited, custom built learning modules tailored specifically to your learning goals and schedule.”

The FAQ notes that ASU alumni and those who “previously expressed interest in ASU's learning initiatives or participated in research that helped shape ASU Atomic” were invited to test the beta. But on Monday morning, I signed up for a free 12 day trial of the Atomic platform with my personal email address — no ASU affiliation required. I first learned about the platform after seeing ASU Professor of US Literature Chris Hanlon post about it on Bluesky. 

“When I looked at it, I was really surprised to see my own face, and the faces of people I know, and others that I don't know” in module materials generated by Atomic, Hanlon said. It had clipped a one-minute snippet from a 12 minute video he’d done as part of a lecture mentioning the literary critic Cleanth Brooks, which the AI transcribed as “Client” Brooks. “What was in that video did not strike me as something anyone would understand without a lot more context,” Hanlon said. When he contacted his colleagues whose lecture videos were also in that module, they were all just as shocked and alarmed, he said. “I mean, it happens to all of us in certain ways all the time, but have your institution do it—to have the university you work for use your image and your lectures and your materials without your permission, to chop them up in a way that might not reflect the kind of teacher you really are... Let alone serve that to an actual student in the real world.”

The videos appear to be scraped from Canvas, ASU’s learning management system where lecture materials and class discussions are made available to students. Canvas is owned by Instructure, and is one of the most popular learning management systems in the country, used by many universities. “ASU Atomic currently draws from ASU Online's full library of course content across subjects including business, finance, technology, leadership, history, and more. If ASU teaches it, Atom—your AI learning partner—can build a hyper-personalized learning module around it,” the Atomic FAQ page says.

As of Monday afternoon, after I reached out at the ASU Atomic email address for comment, signups on Atomic were closed. I could still make new modules using my existing login, however.

In my own test, I went through a series of prompts with a chatbot that determined what I wanted my custom module to be. I told it I was interested in learning about ethics in artificial intelligence at a moderate-beginner level, with a goal of learning as fast as possible. 

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Atomic generated a seven-section learning module, with sections that repeated titles (“Ethics and Responsibility in AI” and “AI Ethics: From Theory to Practice”). The first clip in the first section is a two-minute video taken from a lecture by Euvin Naidoo, Thunderbird School of Management's Distinguished Professor of Practice for Accounting, Risk and Agility. In it, Naidoo talks about “x-riskers,” who he defines as “a community that believes that the progress and movement and acceleration in AI is something we should be cautious about.” Atomic’s AI transcribes this as “X-Riscus,” and transfers that error throughout the module, referring to “X-Riscus” over and over in the section and the quiz at the end. 

The next section jumps directly into the middle of a lecture where a professor is talking about a study about AI in healthcare, with no context about why it’s showing this: 

In a later section, film studies professor and Associate Director of ASU’s Lincoln Center for Applied Ethics, Sarah Florini, appears in a minute-long clip from a completely unrelated lecture where she briefly defines artificial intelligence and machine learning. But the content of what she’s saying is irrelevant to the module because it came from a completely unrelated class and is taken out of context.  

“It makes me feel like somebody that's less knowledgeable about me, they're going to be naive about these positions, and they're going to think either that an ‘expert’ said it so therefore it must be true"

“This was a video from one of the courses in our online Film and Media Studies Masters of Advanced Study. The class is FMS 598 Digital Media Studies. It is not a course about AI at all,” Florini told me. “It is an introduction to key concepts used to study digital media in the field of media studies.” She recorded it in 2020, before generative AI was widely used. “That slide and those remarks were just in there to get students to think of AI as a sub-category of machine learning before I talked about machine learning in depth. That is not at all how I would talk about AI today or in a class that focused more on machine learning and AI tech technologies,” she said. “It’s really a great example of how problematic it is to take snippets of people teaching and decontextualize them in this way.” 

Florini told me she wasn’t aware of the existence of the Atomic platform until Friday. “I was not notified in any way. To the best of my knowledge no faculty were notified. And there was no option to opt in or out of this project,” she said.

Another ASU scholar I contacted whose lecture was included in the module Atomic generated for me (and who requested anonymity to speak about this topic) said they’d only just learned about the existence of Atomic from my email. They searched their inbox for mentions of it from the administration or anyone else, in case they missed an announcement about it, but found nothing. Their lecture snippet presented by Atomic was extremely short and attempted to unpack a very complex topic.

“I don't love the idea of my lectures being taken out of the context of my overall course, and of the readings for that module, and then just presented as saying something,” they told me. “It makes me feel like somebody that's less knowledgeable about me, they're going to be naive about these positions, and they're going to think either that an ‘expert’ said it so therefore it must be true... Or they're gonna think, that's obviously fucking stupid, this ‘expert’ must be dumb. But I could have been presenting a foil!” The clips are so short, it's impossible in some cases to discern context at all.

That lecturer told me the idea of their work being chopped up and used in this way was less a matter of concern for their ownership of the material, and more distressing that someone might come away from these modules with half-baked or wrong conclusions about the topics at hand. “All of the complexity of the topic is being flattened, as though it's really simple,” they said of the snippet Atomic made of their lecture. When they assign this topic to students, it comes with dozens of pages of peer reviewed academic papers, they said. Atomic provides none of that. The module Atomic produced in my test provided zero source links, zero outside readings for further study, no specific citations for where it was getting this information whatsoever, and no mention of who was even in the videos it presented, unless a Zoom name or other name card was visible in the videos. 

“I would really like to know, how did this particular thing happen? How did this actually end up on the asu.edu website?” Hanlon said. “It is such a clunky thing. It is so far removed from what I think the typical educational experience at ASU is. Who decided this would represent us?” 

ASU Atomic, the ASU president’s office, and media relations did not immediately respond to my requests for comment, but I’ll update if I hear back.