What Google Should Really Be Worried About
We recorded 9 claims from this post. 1 was checked against evidence. 8 can’t be checked. 2 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: Can’t be checkedSaid
Forecast
“But here’s the thing: the world’s latest and great tool for tricking search engines (hence playing games with SEO, aka Search Engine Optimization) may change everything.”
Our reading: Large language models, as a tool for tricking search engines, may fundamentally change search engine manipulation.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“Large Language Models (like GPT-3, ChatGPT, Galactica, etc) could be used to produce a enormous numbers of marginal blogs and fake reviews to pump each other up, and increase the search rankings of fraudulent garbage—with a minimal amount of human effort.”
Our reading: Large language models such as GPT-3, ChatGPT and Galactica could be used to produce enormous numbers of marginal blogs and fake reviews that pump each other up and increase the search rankings of fraudulent garbage, with a minimal amount of human effort.
No horizon
Assessment: Can’t be checkedSaid
Observation
“The Bialek hoax is probably just the tip of an iceberg.”
Our reading: The Bialek fake-website hoax is probably only a small visible part of a much larger problem.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“It would be irrational for scammers not to use these new tools to vastly expand their reach, and hence vastly expand their profits.”
Our reading: It would be irrational for scammers not to use these new tools (LLMs) to vastly expand their reach, and hence vastly expand their profits.
No horizon
Assessment: Can’t be checkedSaid
Observation
“When the only company that might have significant amounts of data on the question won’t even answer the question, we can guess that there very well may be a problem.”
Our reading: Because Meta, the only company that might have significant data on what fraction of the misinformation it removes is LLM-generated, won't answer the question, we can guess that there very well may be a problem.
No horizon
Qualifier: inferred from Meta's refusal to answer
Assessment: SupportedSaid
Observation
“As I have discussed in earlier essays, the jury is still out on how far Chat-style search can get, given its obvious current problems with truthiness.”
Our reading: Chat-style search currently has obvious truthfulness problems, and it is uncertain how far it can get.
No horizon Evidence as of
Limitation: A documented error establishes the existence of a reliability problem, not its frequency.
Assessment: Can’t be checkedSaid
Forecast
“But either way, search itself seems likely to face a major growing threat from circles of fake websites that are designed to sell ads and mutually reinforce each other’s positions in Search Engine Optimization.”
Our reading: Web search is likely to face a major, growing threat from rings of fake, mutually reinforcing ad-selling websites.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“Cesspools of automatically-generated fake websites, rather than ChatGPT search, may ultimately come to be the single biggest threat that Google ever faces.”
Our reading: Automatically generated fake websites, rather than ChatGPT-style search, may ultimately be the single biggest threat Google ever faces.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“After all, if users are left sifting through sewers full of useless misinformation, the value of search would go to zero—potentially killing the company.”
Our reading: If search results become flooded with useless misinformation, the value of search would go to zero, which could kill Google.
No horizon
Only if: if users are left sifting through misinformation-filled results
Held from this post (2)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The two reviews reached different assessments. Our reading, not assessed: LLMs aren't very good at writing error-free prose, but the people who run content farms won't care about the errors.
- The two reviews reached different assessments. Our reading, not assessed: LLMs make content-farm text that used to be laboriously human-written cheap and therefore more widespread.