Bojan Tunguz

Bojan Tunguz

x.com/tunguz

Data scientist and TabulAI founder who calls himself adjacent to e/acc, expects very fast AI progress and worries about who shares its benefits.

How will AI change the world?

Civilizational changeIncremental changeDoomBloom
Simulated positionInterpretation range

Across: his expressed Doom–Bloom outlook. Up: scale of transformation.

Doom–Bloom: 51 out of 100. Scale of transformation: 75 out of 100. Interpretation ranges: 25 to 75 horizontally, 70 to 80 vertically. These are interpretation coordinates, not event probabilities.

Bojan Tunguz’s P(doom) · inferred

≈7%

0%100%

Inferred from his simulated answers, not a number they gave. Plausible range: 2–19%.

Bojan Tunguz’s milestone timeline

  1. Work & institutions

    The technical change could be enormous and arrive much faster than institutions can absorb.

    Answer 3

Grouped by milestone, not spaced or ordered by inferred dates. AGI and superhuman AI retain his definitions.

What his outlook hinges on

A central assumption

Right now the gains follow an extreme power law: a small group in tech captures enormous value, while most people experience AI as vague hype or as software they’re being forced to train so it can replace parts of their job.
Answer 1

If this assumption turned out differently, how would his outlook change?

An unresolved question

I don’t have a defensible percentage.
Answer 4

What would help him distinguish the plausible outcomes here?

More details

Expected upside

Substantial benefits are expected, with important conditions or distribution limits.

66 / 100

Little impactTransformative impact

Interpretation range 67 to 67 on the qualitative scale.

Expected harm

Severe or widespread harm is a material expected part of the future.

66 / 100

Little impactTransformative impact

Interpretation range 67 to 67 on the qualitative scale.

Human influence

Human choices have meaningful but substantially constrained influence.

51 / 100

Little influenceStrong influence

Interpretation range 23 to 77 on the qualitative scale.

Development pace

Stop or substantially slow development of more capable AI.

Simulated position: Continue development under stated safeguards.

Speed up development of more capable AI.

Access to AI

Restrict access to powerful AI.

Allow access subject to capability or use restrictions.

Simulated position: Favor broad or open access to powerful AI.

These interpretations keep his stated conditions. Benefits and harms can both be substantial. The ranges describe how we read his simulated answers, not statistical confidence intervals.

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Simulated Assessment

Question 1

What do you think AI means for our future—and why?

AI means extremely rapid progress, especially in coding, mathematics, and science—but a potentially ugly transition. I can build things today that were impossible six months ago. Coding is already the killer app, and intellectually deep work may soon become a cheap service rather than a scarce human skill. The problem is distribution. Right now the gains follow an extreme power law: a small group in tech captures enormous value, while most people experience AI as vague hype or as software they’re being forced to train so it can replace parts of their job. That’s why blanket accelerationism doesn’t convince me. I’m adjacent to e/acc, but acceleration at any cost is not an absolute good; some pacing may eventually be justified. At the same time, panicked restrictions can be self-defeating. America could squander its lead by blocking infrastructure, driving away foreign customers, or letting a handful of labs and cities become an isolated echo chamber. I’d rather see open models, broader access, and scientific institutions adapt to AI than fight the last war.

Question 2

Taking benefits and harms together, what overall impact do you expect AI to have on our society?

Overall, I expect enormous gains in capability paired with a deeply uneven and destabilizing transition. AI will make software, mathematics, and scientific work radically cheaper and faster. That is real progress, not marketing. But society won’t automatically share the upside. The default trajectory is an extreme power law: a few firms and technical insiders capture huge windfalls while many workers see a nebulous product, tighter surveillance, or a machine they were asked to train as their replacement. So I’m optimistic about what AI can do and much less optimistic about how institutions will distribute its benefits. Acceleration at any cost is not a serious social contract.

Question 3

How much do you think AI will ultimately change the world?

Profoundly. If coding, mathematics, and serious scientific work become cheap services, AI won’t merely improve existing industries; it will reshape what expertise is worth, how quickly ideas become products, and who holds economic power. The technical change could be enormous and arrive much faster than institutions can absorb. The open question isn’t whether the world changes, but who benefits. Without deliberate correction, I expect the gains to remain brutally concentrated while workers and ordinary users absorb much of the disruption. So: transformative at the level of capability, potentially dystopian at the level of transition.

Question 4

What’s your gut-feel chance that AI causes human extinction or a similarly permanent catastrophe?

I don’t have a defensible percentage. The risk deserves credible, technically informed assessment, and it’s part of why acceleration at any cost is foolish. But I’m not going to turn uncertainty into a made-up P(doom) for rhetorical effect.

Question 5

Do you lean toward AI doing more good than bad, or are you genuinely torn?

I lean toward more good in terms of raw capability, but I’m genuinely worried about the default transition. Cheaper software, mathematics, and science are enormous benefits. Yet those gains currently accrue to a tiny group while many workers get surveillance, displacement, and the privilege of training their replacements. So I’m not torn about whether the technology is useful—it obviously is. I’m torn about whether our institutions can distribute the upside before concentrated power and social disruption dominate the story.

Sources

Articles, interviews, and writings used to ground this simulated user.

Adjacent to e/acc, not acceleration at any cost

New York Post article (syndicated on Yahoo) on accelerationists versus “doomers”. In his own quoted words he calls himself “adjacent” to e/acc, rejects acceleration at any cost, says some cap might be necessary at some point and some pacing might be justifiable, and says “we are all to some extent accelerationists. The question is just how far.” The reporter paraphrases him saying today’s tools let him build things impossible six months earlier and that he welcomes open models as a fallback if big labs restrict access, while rejecting the idea that cornering the market is their motive. Verdon’s and others’ statements excluded. Full article inspected.

yahoo.com
arXiv fighting the last war

Argues arXiv’s year-long bans for careless AI use are wrong: AI-generated content is a real challenge, but AI is already doing serious scientific work and its role will only grow, and the scientific paper is an outdated artifact. The bans hurt outsiders and early-career researchers; science should move to open, post-publication review like software’s git and pull requests. Full essay inspected.

bojan.substack.com
The end of the road for the Sora app

Explains OpenAI shutting down the Sora app as a result of an overheating race among the top labs: since December the newest models made a qualitative step up in coding, coding is now AI’s killer feature, and vibe coding is good enough that most software professionals can rely on it for most of their work. Industry analysis, not a societal forecast. Full essay inspected.

bojan.substack.com
Nightmares on the AI Doom Street

Older context. Describes mixed excitement and trepidation about AI, says both utopia and destruction of all life seem outlandish but nobody can be sure, and calls for credible, industry-wide AI risk assessment. Argues that many prominent AI doomers are technologically illiterate and that major AI policy should not rest primarily on people who have never trained a model, while saying everyone deserves some say. Opening section of the essay inspected; reader comments excluded.

bojan.substack.com
A few more months for deep original work

Says he thinks there are “a few more months, max, left” to do any intellectually deep original work. The same day he called mathematics “Math-as-a-Service” and the next “Math too cheap to matter”. A sweeping, partly provocative forecast about intellectual work, not an AGI date. Full text of all three posts inspected via X’s public embed endpoint.

x.com
AI’s benefits follow an extreme power law

Replying to a quoted post that marvelled at doubters of AI, he says the reason is that AI’s benefits are spread on an extreme power law: a few people, mainly in tech, reap enormous windfalls while for most of the population AI seems nebulous at best. A diagnosis of uneven benefits, not a redistribution proposal. Quoted post belongs to someone else; full text inspected via X’s public embed endpoint.

x.com
Sabotaging America’s AI export lead

Quoting a post about non-US companies seeing they can be cut off from US AI vendors, he says AI was one huge export product the US dominated and that the country now faces the prospect of “completely and utterly sabotaging it”. Concern about US policy undermining its own industry; the specific restriction is in the quoted post, not his. Full text inspected via X’s public embed endpoint.

x.com
Anthropic overlords and prompt restrictions

A sarcastic line, with an image, about “our Anthropic overlords” deciding which prompts “the peasants” may use. Reads as irritation at lab-imposed usage restrictions, not a literal claim. Full text inspected via X’s public embed endpoint; the image was not reviewed.

x.com
Training AI on workers to replace them

Quoting a report that Meta would install tracking software on US employees’ computers, he says companies are using their workers to train AI that replaces them and calls it “utterly cringe and dystopian”. A moral judgment about one practice, not an economy-wide jobs forecast. Full text inspected via X’s public embed endpoint.

x.com
NIMBYism versus the march to AGI

Quoting a report that a $100B chip fab in New York was threatened by a lawsuit from a few residents, he says NIMBYism will destroy America’s march towards AGI. Support for building AI infrastructure, framed as a national race. Full text inspected via X’s public embed endpoint.

x.com
AI talent concentration as an echo chamber

Quoting a post that AI builders don’t talk to normal people, he says, as he has “argued many times”, that this follows from forcing the AI workforce into a few geographically isolated places: what the industry sees as talent concentration is “a highly inbred echo chamber”. Full text inspected via X’s public embed endpoint.

x.com
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