“A lot of machine learning researchers are worried. And yet most people carry on as if they weren’t.”
Our reading, the sentence that was checked:
Many machine learning researchers worry about very bad outcomes from AI, yet most people carry on as if they didn't.
Assessment: Unresolved Evidence as of
Where and when Gary Marcus wrote it
Marcus on AI, Should we worry more about short-term AI risk or long-term AI risk?, paragraph 10.
- Said
- Source observed
- live page, full text, public
- Evidence as of
- the cutoff for this assessment
- Assessment recorded
- assessment marcus-should-we-worry-more-about-short-f915b5-a1
We recorded 11 claims from this post. See every claim from this post.
The wording above is the version this site observed on 2026-10-29. The source may have been edited after 2023-03-14. This page does not claim the wording was captured then.
What the claim commits to
- Kind
- Observation
- Deadline, as the speaker wrote it
- None stated. This site does not add one.
- Deadline state when assessed
- No horizon
- Deadline state on 2026-10-29
- No horizon (the release’s reference date)
From the speaker
- A lot of machine learning researchers are worried
- most people carry on as if they weren’t
- 2022 survey
Our interpretation
- A lot means a substantial share, not necessarily a majority.
- Assigning a meaningful probability to extremely bad outcomes is evidence of concern in the survey context; it is not a direct emotional measure.
- Most means more than half. Carry on as if they weren't refers to behavior apparently unresponsive to the stated risk.
- Most people could mean the public or the machine-learning community; neither population is silently substituted for the other.
- The compound observation combines the explicitly referenced 2022 survey with behavior ongoing at publication. Its enclosing target period is 2022 through March 14, 2023; behavioral evidence must address the latest pre-post state.
Counts as supported if: The referenced survey establishes substantial researcher concern, and representative evidence establishes that a majority of the intended population behaved without a meaningful response to that concern.
Counts as contradicted if: The survey establishes negligible researcher concern, or representative behavioral evidence shows that most of the intended population meaningfully responded to the risk.
Retrospective: these criteria were written after the outcome was public.
Current assessment
Was it true for the period described?
Outcome: Unresolved
The record was checked, and the evidence available by the cutoff does not settle it.
Scored on a plain reading. The speaker named no measure for this claim, so it was judged on the reading an informed reader would take, stated below under our interpretation. Both reviews had to find that reading fair.
- Evidence as of
- Deadline state when assessed
- No horizon
- Assessment recorded
- Policy version
- 2026-10-28.7
Rationale
The first clause is supported: 48% of respondents assigned at least a 10% chance to an extremely bad outcome. The second clause remains unestablished. Neither risk estimates nor policy preferences measure how most people behaved. The public polling also cautions against assuming that continued ordinary activity means indifference. The compound claim is unresolved, rather than mixed, because no matching behavioral evidence conclusively contradicts it.
Limitations
- The researcher survey had a 17% response rate.
- The public poll covers U.S. adults and expressed preferences.
- The second clause could partly express a judgment about how much action would be appropriate.
Evidence (2 items)
Supports the claim: AI Impacts,
48% of respondents
Why it matters here: This directly supports substantial concern among surveyed researchers. The report records a 17% response rate, so extrapolating precisely to all machine-learning researchers requires caution.
- Publisher
- AI Impacts
- Kind of source
- Independent measurement
- Describes events of
- Public from
Context only: Monmouth University Polling Institute,
A majority (55%)
Why it matters here: The U.S. poll shows majority support for a policy response, cautioning against an inference of public indifference. Policy preferences are not actual behavior, and U.S. adults are not necessarily Marcus's intended population.
- Publisher
- Monmouth University Polling Institute
- Kind of source
- Independent measurement
- Describes events of
- Public from
What would settle it
Identification of the intended population and a defensible behavioral measure, followed by representative evidence about that behavior near March 2023. Separating the clauses would allow the researcher-concern observation to be supported independently.
Where it was said (1)
Said once in the sources this register covers.
: Marcus on AI, Should we worry more about short-term AI risk or long-term AI risk?
A lot of machine learning researchers are worried. And yet most people carry on as if they weren’t.
- Where
- paragraph 10
- Published
- 2023-03-14
- Source observed
- , live page
- Access
- full text, public
History
Assessment versions
- Assessment marcus-should-we-worry-more-about-short-f915b5-a1: Current. Outcome: Unresolved. Evidence as of 2026-10-28. Public date not recorded.
Recorded events
Assessment publishedBy this site
First assessment published after both reviews and the final-text check passed.
About assessment marcus-should-we-worry-more-about-short-f915b5-a1.