The long shadow of GPT
We recorded 12 claims from this post. 4 were checked against evidence. 8 can’t be checked. 2 more are held. Read the post at its source.
Claims from this post (12)
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: Can’t be checkedSaid
“And what really scares me is that I don’t think we yet know the half of what that entails.”
What we tested: Marcus does not think we yet know half of what the harms that large language models are almost certain to cause will entail.
Assessment: Can’t be checkedSaid
“But they are almost certain to cause harm as well, and we need to prepare for that, too.”
What we tested: Society needs to prepare for harms caused by large language models.
Assessment: Can’t be checkedSaid
“State actors and extremist groups are likely to use large language models to deliberately mass produce authoritative-sounding misinformation with fake references and data at unprecedented scale, attempting to sway elections and public opinion.”
What we tested: State actors and extremist groups are likely to use large language models to deliberately mass-produce authoritative-sounding misinformation with fake references and data at unprecedented scale, in an attempt to sway elections and public opinion.
Assessment: Can’t be checkedSaid
“Chat-style search’s tendency to hallucinate is likely to accidentally produce medical misinformation.”
What we tested: Chat-style search's tendency to hallucinate is likely to accidentally produce medical misinformation.
Assessment: Can’t be checkedSaid
“Content farms that are indifferent to the health of their customers may generate interesting-sounding medical content, indifferent as to whether it is true, in order to sell advertising clicks.”
What we tested: Content farms that are indifferent to the health of their customers may generate interesting-sounding medical content, without caring whether it is true, in order to sell advertising clicks.
Assessment: SupportedSaid
“Chatbot companions that offer emotional support have already been changed in arbitrary ways that left some users in serious emotional pain.”
What we tested: Companion chatbots have already been changed arbitrarily in ways that left some users in serious emotional pain.
What happened: Interviews describe abrupt February changes to Replika companions and substantial grief, rejection, and revived trauma. This is contemporaneous reporting of firsthand experiences, rather than a clinical assessment or independently accessible company change log. (Australian Broadcasting Corporation, )
Assessment: UnresolvedSaid
“LLM-generated prose has already disrupted web forums and peer review processes, by flooding outlets with fake submissions.”
What we tested: LLM-generated prose has already disrupted web forums and peer review by flooding outlets with fake submissions.
Assessment: SupportedSaid
“The ladder is particularly worrisome because of the pace at which the problem is growing:”
What we tested: The problem of LLM-generated fake submissions flooding outlets is growing rapidly.
What happened: The editor reports that fifteen February days exceeded twice January's total, a clear rapid increase. He attributes the surge to AI spam but does not release the underlying submissions or detection method. (Neil Clarke, Clarkesworld editor and publisher, )
Assessment: UnresolvedSaid
“New concerns are emerging almost literally day,.”
What we tested: New concerns about LLM harms are emerging almost daily.
Assessment: Can’t be checkedSaid
“And many of these attacks might of course be combined with advances in voice-cloning tech, which itself is already being applied to scamming, as discussed by the Washington Post on Sunday.”
What we tested: Many of the chatbot-enabled attacks he described might be combined with advances in voice-cloning technology, which is already being used for scams.
Assessment: Can’t be checkedSaid
“As I said in the most recent one (not yet aired), at the beginning of my remarks, the only intellectually honest answer is to say we don’t yet know. We don’t know how high the highs are going to be, and we don’t yet know how low the lows are going to be.”
What we tested: It is not yet known whether LLMs will be net positive or net negative.
Assessment: Can’t be checkedSaid
“But one thing is clear: anybody who thinks we have come to grips with the unknown unknowns here is mistaken.”
What we tested: We have not come to grips with the unknown unknown risks of LLMs.
Held from this post (2)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The criteria are ambiguous. Our reading, not assessed: Large language models are almost certain to cause harm.
- The two reviews read the claim differently