Six months after the Pause letter, AI is still erratic — and still something we should still be deeply concerned about
We recorded 9 claims from this post. 7 were checked against evidence. 2 can’t be checked. 8 more are held. Read the post at its source.
Claims from this post (9)
In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.
Assessment: UnresolvedSaid
Causal claim
“We have vastly more attention on AI policy, throughout the world, and I definitely give the pause letter (which I signed but didn’t write) some credit for that.”
Our reading: Global attention on AI policy has vastly increased since March 2023, and the pause letter deserves some credit for that.
No horizon Evidence as of
Limitation: A new meeting is not a worldwide measure of attention.
Assessment: Can’t be checkedSaid
Causal claim
“My own guess is that between the release of GPT-4 in November 2022 and the May 2023 testimony OpenAI ran some preliminary tests and decided that the system would not meet expectations.”
Our reading: Marcus guesses that, between GPT-4's release (which he dates to November 2022) and the May 2023 testimony, OpenAI ran some preliminary tests and decided GPT-5 would not meet expectations, and that this explains why it is not training GPT-5.
No horizon
Qualifier: my own guess
Assessment: SupportedSaid
Observation
“Voluntary guidelines aren’t laws, and they aren’t enforcement mechanisms, either; companies can still do as they please.”
Our reading: At least in the United States, voluntary AI guidelines are not laws or enforcement mechanisms, and companies can still do as they please.
No horizon Evidence as of
Limitation: The result depends on reading the sentence in its immediate White House-commitments context.
Assessment: SupportedSaid
Observation
“At least in the United States, policy around AI is still largely notional, not actual.”
Our reading: US AI policy remains largely notional rather than actual.
No horizon Evidence as of
Limitation: The result depends on the surrounding discussion of new commercial AI safeguards.
Assessment: SupportedSaid
Observation
“Large language models still make stuff up (“hallucinate”), still can’t be trusted in their reasoning, and remain unreliable.”
Our reading: LLMs still hallucinate and their reasoning cannot be trusted.
No horizon Evidence as of
Limitation: The results concern specific models, tasks, and prompts rather than every possible use.
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“We have far too little machinery in place to surveil or address such threats.”
Our reading: We have far too little machinery in place to surveil or address threats such as a new form of bioweapon attack that could arise if superintelligent AI were at some point imminent and posed a genuine threat.
No horizon
Scope: threats from hypothetically imminent superintelligent AI
Assessment: UnresolvedSaid
Causal claim
“If we don’t know what is in the data sets, we can’t know what biases these systems will spread through society if they are widely used, we can’t know the extent to which individual content creatore are being exploited, and worse any outside efforts to mitigate risks are greatly undermined.”
Our reading: If we don't know what is in AI training data sets, we can't know what biases these systems will spread through society if widely used or the extent to which individual content creators are being exploited, and outside efforts to mitigate risks are greatly undermined.
No horizon Evidence as of
Only if: if we don't know what is in the data sets
Assessment: UnresolvedSaid
Causal claim
“The apparent economics of AI (we will see if they yet come to pass as imagined) are too seductive to too many, to people building AI companies, to people investing in AI companies, to people getting paid 6 and even 7 digit salaries, and to people expecting campaign donations from big tech companies.”
Our reading: The apparent economics of AI, which may or may not come to pass as imagined, are too seductive to too many people (AI company builders, investors, people paid 6- and 7-digit salaries, and those expecting big-tech campaign donations) for any AI moratorium to happen in the near term.
No horizon Evidence as of
Limitation: Public statements may omit motives or present them selectively.
Assessment: UnresolvedSaid
Forecast
“We are obviously never going to have a moratorium anytime in the near-term.”
Our reading: There will be no moratorium on AI development in the near term.
No deadline stated Evidence as of
Limitation: The main contemporaneous account comes from the organization advocating the pause.
Held from this post (8)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The record does not meet the current rules. Our reading, not assessed: GPT-5, essentially the only thing the pause letter proposed to pause, seems to be on pause, if Sam Altman's May 2023 Senate testimony meant what Marcus thinks it did.
- The two reviews read the claim differently
- The criteria are ambiguous. Our reading, not assessed: Society has no real plan to mitigate long-term AI risks.
- The two reviews reached different assessments. Our reading, not assessed: LLMs remain unreliable and none of the basic issues Marcus has highlighted for 20 years has been solved.
- The two reviews read the claim differently
- The two reviews read the claim differently
- Attribution is uncertain
- The two reviews reached different assessments. Our reading, not assessed: None of the big AI companies discloses what is in their training data sets despite pledging transparency.