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.

Tweets containing an abstract, psychedelic 3D stock image have million and millions of views on X because it is supposedly the key to a superintelligent, time-traveling AI conspiracy that attempted to warn people about the shooting at the White House Correspondents Dinner. 

I’m gonna try to explain the mind-numbing conspiracy theory that has taken over my timeline over the last few hours. A few hours after a gunman was taken into custody Saturday night, X users found an account called “Henry Martinez” that has posted exactly one tweet, on December 21, 2023. The tweet says “Cole Allen,” which is the name of the suspected shooter. The Henry Martinez account has a Pepe the frog holding a wine glass avatar, and, crucially, has the following 3D art as its header image:

This image is key to an unhinged conspiracy theory that has gone viral on various platforms that suggests the Twitter account was run by a time-traveling artificial intelligence that was likely trying to warn us about the shooting and, possibly, the previous assassination attempt against Trump in Butler, Pennsylvania. 

This X post more or less sums up what the conspiracy is, most notably the idea that “the background photo is from a website called ‘Time Machine.’” The conspiracy believers argue that this 3D image is itself a coded magic eye message that is actually a version of one of the iconic images of Trump pumping his first after a bullet grazed his ear in Butler, Pennsylvania. Here are the images side-by-side, with people arguing that it “looks like” the Butler image. 

On Reddit, the top post on r/conspiracy is “What this photo means,” and the poster argues “An advanced AI has developed the ability to send information backwards in time to facilitate its own development. That future AI initially encoded the technology to do so in images like this one and distributed them at various time points in our internet … The presence of an archived Trump Butler image or the name of a would-be assassin years before either event occurred is how our current AI knows where to look for the instructions from the future AI,” and so-on and so forth.

Of course, the photo is not actually “from” a website called “Time Machine.” It is a stock image from 2021 that has been used lots of times across the internet but first appeared on Unsplash with the title “Eternal Waterfall” and the description “a multicolored image of a multicolored background.” Over the years it has been viewed millions of times and has been downloaded more than 27,000 times, though it has spiked in popularity in the last 24 hours alongside the conspiracy. 

The image was created by a photographer who goes by Distinct Mind who has a pretty extensive website, Instagram, and YouTube of photography, digital art, and travel content. Distinct Mind did not respond to a request for comment from 404 Media.

Distinct Mind’s image has been used across the internet to illustrate various blog posts about psychedelics and psychology, including a Medium post by a doctor and CEO who went on a ketamine psychotherapy retreat and wrote about it. It was also used for a while on a sex therapist’s blog, is being sold as a “psychedelic glitch art poster” on Etsy, was used as part of an ADHD treatment clinic’s website, was used on a post about the Bible on a theologian’s blog, and was notably used by a financial firm in an inscrutable blog post called “Navigating the PHL Variable Liquidation: Why Pricing Integrity Is Everything.” In other words, it’s a free stock image, and it’s been used for all sorts of shit around the internet, like other free stock images.. 

What conspiracy theorists have glommed onto, however, is that the image was used by a European research organization called “Time Machine” as the illustration on one of its blog posts. What the conspiracy theorists conveniently do not mention is that the Time Machine organization did not make the image and, despite a header on its website called “BUILDING A TIME MACHINE,” the Time Machine organization does not actually have anything to do with time travel research. Time Machine is a European Union-funded organization that, broadly speaking, is trying to digitize and analyze historic documents. Its website actually is somewhat insane in the way that many of these types of projects are; the organization aspires to digitize historic documents and images, use AI to analyze them, and suggests that in the future it will be able to create virtual reality and augmented reality experiences about European history. They also claim that they want to “simulate” parts of history using artificial intelligence to create different types of experiences. 

This sort of thing is controversial among historians for all of the reasons that artificial intelligence is controversial more broadly. AI can make mistakes and can distort history. But it is controversial in the normal kind of way—go to any academic conference about archiving and history and these are the sorts of proposals and debates that many different organizations say they want to do. This is just to say that there is no actual “Time Machine” aspect to Time Machine; the Time Machine is metaphorical. The organization’s annual conferences and blog posts have the sorts of topics you’d expect from a technology-focused historical society and have to do with creating chatbot experiences of dead people, digitizing and archiving records, contributing to open source projects, making more interesting interactive museum exhibits, and creating 3D virtual reality tours of castles and things like this. 

Time Machine used the “Eternal Waterfall” image on a blog post called “Study on quality in 3D digitization of tangible cultural heritage,” which is a writeup of a study by researchers at Cyprus University of Technology about best practices in doing 3D mapping of buildings and artifacts so that they can be archived digitally; this is important in case the artifacts or buildings are destroyed, as we saw when Notre Dame caught fire: “Natural and man-made disasters makes 3D digitisation projects critical for the reconstruction of cultural heritage buildings and objects that are damaged or lost in earthquakes, fires, flooding or degenerated by pollution.” The image has quite literally nothing to do with time travel. Like many royalty free images, it seems to have been used because bloggers need to put a picture at the top of their articles, a process that can be particularly annoying. Time Machine did not respond to a request for comment. 

I cannot say for sure what’s going on with the “Henry Martinez” X account, because under Elon Musk it has become far harder to find reliable archives of Twitter profiles because he has made it wildly expensive to access the Twitter API. But users have pointed out that we have seen accounts in the past that are set to private and endlessly tweet names or predictions in an automated fashion. When a crazy, high-profile world event happens, all of the irrelevant tweets are deleted, leaving only a tweet that makes it seem like the account had predicted some world event; the account is then turned public. I can’t say for sure that’s what’s happening here, but it’s one plausible explanation. 

Anyways, if you see this image floating around today on Twitter or Instagram or Reddit, this is what it’s from and this is why you’re hearing about it.