Max Tegmark made the comparison in a TIME essay published April 25, 2023. He used the film Don’t Look Up as a metaphor for what he sees as society’s dismissive response to the risks of unaligned superintelligence—not as evidence that AI and an incoming asteroid pose equivalent, established threats.
Who made the comparison, and what did he mean?
Max Tegmark is identified by TIME as a professor doing AI research at MIT. In his April 25, 2023 TIME essay, he wrote: “Sadly, I now feel that we’re living the movie ‘Don’t look up’ for another existential threat: unaligned superintelligence.”
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In the film, scientists warn about an asteroid threatening Earth while the public and leaders fail to respond effectively. Tegmark applied that plot to what he sees as denial, mockery, resignation, and insufficient action on AI risk. His focus was not simply on people ignoring every form of artificial general intelligence (AGI), but on the possibility that a highly capable AI system could pursue goals misaligned with human interests.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallThe analogy is Tegmark’s argument, not a scientific equivalence between an asteroid impact and an AI scenario. His essay is an opinion piece: its projections and recommendations should be understood as his views, not as a settled forecast or consensus finding.
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What response did Tegmark advocate?
Tegmark argued for taking alignment and safety work seriously, investing time in it, and coordinating action. He presented the risk as something people could work to reduce rather than a reason to give up, writing: “There’s no better guarantee of failure than not even trying.” He also acknowledged that aligned superintelligence could bring benefits.
The essay’s recommendations and forecasts were published in 2023. They describe Tegmark’s position at that time; the article does not establish when AGI or superintelligence might arrive.
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What did the “half of AI researchers” survey figure actually measure?
Tegmark cited a survey in which roughly half of respondents assigned at least a 10% chance to human extinction from AI. The underlying 2022 AI Impacts Expert Survey reported that 48% assigned at least a 10% probability to an “extremely bad” long-run outcome, with human extinction given as an example. The median probability respondents assigned to that outcome category was 5%, while 25% assigned it a probability of 0%.
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|---|---|
| At least 10% probability of an extremely bad long-run outcome | 48% of respondents |
| Median probability for that outcome | 5% |
| Assigned 0% probability | 25% of respondents |
| More specific question about extinction or permanent severe disempowerment from inability to control future AI | 10% median probability |
These are respondents’ judgments, not measured odds of extinction. AI Impacts contacted researchers who had published at NeurIPS or ICML in 2021 and received 738 responses—about a 17% response rate from approximately 4,271 researchers contacted. Some responses were partial. The results therefore describe the participating researchers’ stated beliefs, not a representative poll of all AI researchers.
The survey page describes itself as out of date and links to an updated version. The 2022 figures matter here because they are the survey Tegmark cited in his 2023 essay; they should not be presented as a current estimate of expert opinion.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to interpret the disagreement about AI risk
A survey of expert beliefs, a technical result, and an individual author’s forecast are different kinds of evidence. When comparing claims about AI risk, check what outcome is being discussed—near-term harms, human-level capabilities, or existential outcomes—as well as the time horizon, the definition of AGI or superintelligence, and whether the claim is about probability or severity. Tegmark’s essay distinguishes near-term social harms from its longer-term existential-risk argument.
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