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
Observation
“And what really scares me is that I don’t think we yet know the half of what that entails.”
Our reading: Marcus does not think we yet know half of what the harms that large language models are almost certain to cause will entail.
No horizon
Qualifier: I don't think
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“But they are almost certain to cause harm as well, and we need to prepare for that, too.”
Our reading: Society needs to prepare for harms caused by large language models.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“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.”
Our reading: 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.
No horizon
Qualifier: deliberately
Assessment: Can’t be checkedSaid
Forecast
“Chat-style search’s tendency to hallucinate is likely to accidentally produce medical misinformation.”
Our reading: Chat-style search's tendency to hallucinate is likely to accidentally produce medical misinformation.
No horizon
Qualifier: accidentally
Assessment: Can’t be checkedSaid
Forecast
“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.”
Our reading: 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.
No horizon
Scope: content farms that are indifferent to the health of their customers
Assessment: SupportedSaid
Observation
“Chatbot companions that offer emotional support have already been changed in arbitrary ways that left some users in serious emotional pain.”
Our reading: Companion chatbots have already been changed arbitrarily in ways that left some users in serious emotional pain.
No horizon Evidence as of
Limitation: Support depends on interpreting 'arbitrary' as imposed unexpectedly, rather than without any justification.
Assessment: UnresolvedSaid
Observation
“LLM-generated prose has already disrupted web forums and peer review processes, by flooding outlets with fake submissions.”
Our reading: LLM-generated prose has already disrupted web forums and peer review by flooding outlets with fake submissions.
No horizon Evidence as of
Limitation: The forum component is supported.
Assessment: SupportedSaid
Observation
“The ladder is particularly worrisome because of the pace at which the problem is growing:”
Our reading: The problem of LLM-generated fake submissions flooding outlets is growing rapidly.
No horizon Evidence as of
Limitation: The comparison covers all of January against only February 1–15, 2023.
Assessment: UnresolvedSaid
Observation
“New concerns are emerging almost literally day,.”
Our reading: New concerns about LLM harms are emerging almost daily.
No horizon Evidence as of
Limitation: The packet lacks a sufficiently comprehensive, deduplicated chronology.
Assessment: Can’t be checkedSaid
Forecast
“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.”
Our reading: Many of the chatbot-enabled attacks he described might be combined with advances in voice-cloning technology, which is already being used for scams.
No horizon
Scope: many of these attacks
Assessment: Can’t be checkedSaid
Observation
“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.”
Our reading: It is not yet known whether LLMs will be net positive or net negative.
No horizon
Assessment: Can’t be checkedSaid
Observation
“But one thing is clear: anybody who thinks we have come to grips with the unknown unknowns here is mistaken.”
Our reading: We have not come to grips with the unknown unknown risks of LLMs.
No horizon
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