“And man, is it ridiculous that AI doomers warning about spooky superintelligences have somehow had such incredible prominence in the media without ever succeeding in stopping a single thing — or even substantiating their concerns.”
Our reading, the sentence that was checked:
AI doomers warning about superintelligence have not stopped anything or substantiated their concerns despite their media prominence.
Assessment: Contradicted Evidence as of
Where and when Ed Zitron wrote it
Where's Your Ed At, The AI Hater's Manifesto, paragraph 79.
- Said
- Source observed
- live page, full text, public
- Evidence as of
- the cutoff for this assessment
- Assessment recorded
- assessment wyea-the-ai-haters-manifesto-5b3fc5-a1
We recorded 50 claims from this post. See every claim from this post.
The wording above is the version this site observed on 2026-10-28. The source may have been edited after 2026-08-25. 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
- AI doomers warning about spooky superintelligences
- without ever succeeding in stopping a single thing
- or even substantiating their concerns
Our interpretation
- Ever covers the historical record through the post date; no starting date is supplied.
- Stopping requires an actual halt or restriction attributable to the relevant advocates. A safety-related pause alone does not prove advocacy caused it.
- Substantiating means supplying meaningful empirical evidence for a stated concern about advanced AI control or alignment. It does not require a catastrophe to have occurred.
- Media prominence and the description ridiculous are framing, not separately scored numerical claims.
Counts as supported if: A sufficiently comprehensive record establishes neither an attributable halt nor meaningful empirical evidence for the relevant concerns.
Counts as contradicted if: At least one attributable halt or a credible empirical demonstration materially supports a relevant concern about advanced AI control or alignment.
Retrospective: these criteria were written after the outcome was public.
Current assessment
Was it true for the period described?
Outcome: Contradicted
The dated evidence goes against what the claim committed to, under the criteria frozen before grading.
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 categorical absence of substantiation is contradicted under the ordinary reading that substantiation means meaningful empirical support. Research had demonstrated behavior relevant to alignment and control concerns before the post. This does not prove catastrophe predictions, and alternative explanations remain. The separate assertion about advocates stopping anything is not settled: a documented safety pause does not establish their causal influence.
Limitations
- The result depends on interpreting substantiation as empirical support rather than proof of catastrophic predictions.
- The main experiment used conditions designed to facilitate the behavior.
- The advocacy-effectiveness clause remains unresolved.
- The cited research is preprint evidence.
Evidence (3 items)
Goes against the claim: arXiv; Anthropic and Redwood Research authors,
We additionally observe other behaviors such as the model exfiltrating its weights when given an easy opportunity.
Why it matters here: The experiments provide empirical evidence relevant to concerns about models resisting modification and evading control. They contradict the absence of substantiation under the stated reading, while their deliberately facilitating setup does not establish catastrophic risk in deployment.
- Where
- Abstract
- Publisher
- arXiv; Anthropic and Redwood Research authors
- Kind of source
- Preprint, not peer reviewed
- Describes events of
- Public from
Context only: OpenAI,
We wanted to take the time necessary to meet those standards, so we temporarily slowed the pace of scaling.
Why it matters here: OpenAI disclosed interrupted training and a continuing hold on its largest planned frontier reinforcement-learning run. This establishes a safety-related interruption, but does not establish that the advocates Zitron describes caused it.
- Publisher
- OpenAI
- Kind of source
- Company disclosure: the company describing itself, not an independent finding
- Describes events of
- Public from
Context only: arXiv,
Third, we fine-tune models to be more sycophantic and observe increased sensitivity to evaluation cues.
Why it matters here: This research offers an alternative explanation for apparent scheming and reports difficulty distinguishing the mechanisms. It limits how strongly alignment-faking experiments substantiate claims about intentional deception.
- Where
- Abstract
- Publisher
- arXiv
- Kind of source
- Preprint, not peer reviewed
- Describes events of
- Public from
Where it was said (1)
Said once in the sources this register covers.
: Where's Your Ed At, The AI Hater's Manifesto
And man, is it ridiculous that AI doomers warning about spooky superintelligences have somehow had such incredible prominence in the media without ever succeeding in stopping a single thing — or even substantiating their concerns.
- Where
- paragraph 79
- Published
- 2026-08-25
- Source observed
- , live page
- Access
- full text, public
History
Assessment versions
- Assessment wyea-the-ai-haters-manifesto-5b3fc5-a1: Current. Outcome: Contradicted. 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.