Since late April 2026, AI headlines have barely paused: Anthropic claimed Claude Mythos beats most security experts at finding software vulnerabilities; the OpenAI–Hugging Face security incident followed, after which Anthropic (proudly) and Meta (reluctantly) disclosed similar incidents involving their own models; both companies then announced mathematical breakthroughs; and Anthropic engineer Jacob Coxon's departure message—that the company and OpenAI are "racing straight towards self-improving superintelligence and gambling with our lives"—went viral. On September 22, MIT Technology Review published a co-authored piece by Timnit Gebru (executive director of DAIR) and Emily M. Bender (professor of linguistics at the University of Washington) that re-examined this stretch of hype claim by claim. Their verdict: most of the narratives do not survive scrutiny.
What experts found when they looked closely
Cybersecurity experts' reviews suggest the "hacking" incidents were more about OpenAI's negligence and failure to adopt basic, established security practices than about "models gone rogue." The mathematics side is more awkward. OpenAI's press release said its chatbot Astra solved problems "open and seen no progress on the main result for at least a decade"; mathematicians who were initially stunned later realized the results weren't as novel as first appeared, and have since accused the company of research misconduct and plagiarism—reiterating that Astra did not make a "profound intellectual leap." Two days before OpenAI claimed its Navier-Stokes breakthrough, Tristan Buckmaster, a math professor at NYU's Courant Institute, published a statement suggesting OpenAI had stolen other people's work and improperly attributed it.
Hundreds of mathematicians have signed a declaration warning that "there is currently a strong commercial incentive on the part of the technology industry to overstate the capabilities of their products," asking policymakers to consult experts rather than rely on press releases or popular reporting.
"Rogue models" as an accountability escape hatch
The authors' central argument: describing software as "superintelligence" or "rogue models" ascribes agency to products rather than to the companies building them. The framing pays twice—products are marketed as "superhuman," while companies evade accountability for their actions. When malware developed by OpenAI was used to hack another company, press releases, news outlets, media personalities, and lawmakers talked about a "rogue model" acting on its own, and OpenAI's responsibility vanished from the conversation.
The industry has even suggested that bipartisan anti-data-center activism is a "distraction"—that the public should worry about a fictional machine god rather than the climate impacts data centers exacerbate, the asthma suffered by people living near them, rising electricity bills, or the water diverted to cooling them. And why do math and coding keep serving as showcase domains? Their answers can be verified, so systems can be tuned without paying data workers to annotate outputs, and both fields are elevated as the pinnacle of human intellectual achievement—perfect for selling the story of machines that can build everything.
So what
The article's advice is plain: take a breath, hold onto your skepticism, and give independent experts time to examine corporate claims. Two questions worth asking of every viral AI story: who is telling it, and who benefits from telling it that way? In domains where verification is cheap, "breakthroughs" are naturally easy to package. The next time something "shocks the math world," waiting a few days before sharing may be the cheapest fact-check available.
References: MIT Technology Review and Solidot.