AI's Jurassic Park moment
We recorded 15 claims from this post. 6 were checked against evidence. 9 can’t be checked. 5 more are held. Read the post at its source.
Claims from this post (15)
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
“It is no exaggeration to say that systems like these pose a real and imminent threat to the fabric of society.”
Our reading: Generative AI systems like chatGPT pose a real and imminent threat to the fabric of society.
No horizon
Assessment: UnresolvedSaid
Observation
“they can easily be automated to generate misinformation at unprecedented scale.”
Our reading: Generative AI systems like ChatGPT, Dall-E 2, and Lensa can easily be automated to generate misinformation at unprecedented scale.
No horizon Evidence as of
Limitation: The supplied experiment predates the November–December 2022 target period [e1].
Assessment: UnresolvedSaid
Causal claim
“they cost almost nothing to operate, and so they are on a path to reducing the cost of generating disinformation to zero.”
Our reading: Because generative AI systems like ChatGPT, Dall-E 2, and Lensa cost almost nothing to operate, they are on a path to reducing the cost of generating disinformation to zero.
No horizon Evidence as of
Limitation: The economically negligible reading of 'zero' is an interpretation.
Assessment: SupportedSaid
Observation
“Alas, the genie can no longer be stuffed back in the bottle.”
Our reading: Misinformation-capable LLM technology can no longer be contained or withdrawn.
No horizon Evidence as of
Limitation: Shows availability during the period, not long-term containment.
Assessment: SupportedSaid
Observation
“For another, chatGPT, just released by OpenAI, is more or less just as capable of producing similar nonsense, such as instant essays on adding wood chips to breakfast cereal.”
Our reading: ChatGPT is about as capable as Galactica of producing nonsense misinformation.
No horizon Evidence as of
Limitation: The packet found no head-to-head test of ChatGPT and Galactica, so 'more or less just as capable' is judged qualitatively, not measured.
Assessment: Can’t be checkedSaid
Conditional forecast
“As one of the most central resources that the world’s programmers rely on, the consequences for software quality and developer productivity could be immense.”
Our reading: If Stack Overflow is flooded with worthless ChatGPT-generated code examples and dies, then, because it is one of the most central resources the world's programmers rely on, the consequences for software quality and developer productivity could be immense.
No horizon
Only if: if Stack Overflow is flooded with worthless generated code examples and dies
Assessment: UnresolvedSaid
Conditional forecast
“If the website is flooded with worthless code examples, programmers will no longer go there, its database of over 30 million questions and answers will become untrustworthy, and the 14 year old website will die.”
Our reading: If Stack Overflow is flooded with worthless generated code, programmers will leave, its database will become untrustworthy, and the site will die.
No deadline stated Evidence as of
Only if: if the website is flooded with worthless AI-generated code examples
Assessment: Can’t be checkedSaid
Forecast
“Nation-states and other bad actors that deliberately produce propaganda, are highly unlikely to voluntarily put down their new arms. Instead, they are likely to use large language models as a new class of automatic weapons, in their war on truth, attacking social media and crafting fake web sites at a volume we have never seen before.”
Our reading: Propaganda-producing nation-states and bad actors are likely to use LLMs to attack social media and create fake websites at unprecedented volume.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“And it’s clear that that is exactly what large language models make possible. They are aiming to create a world in which we are unable to know what we can trust; with these new tools, they might succeed.”
Our reading: LLMs make greatly escalated propaganda volume possible, and propagandists might succeed in creating a world where people cannot know what to trust.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“First, every social media company and search engine should support and extend StackOverflow’s ban; automatically-generated content that is misleading, should not be welcome, and the regular posting of it should be grounds for a user’s removal.”
Our reading: Every social media company and search engine should support and extend Stack Overflow's ban, misleading automatically-generated content should not be welcome, and regularly posting it should be grounds for a user's removal.
No horizon
Scope: automatically-generated content that is misleading
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“In time, though it would not be a popular decision, we may have to begin to treat misinformation as we do libel, making it actionable if it is created with sufficient malice and sufficient volume.”
Our reading: Countries may need to make misinformation legally actionable like libel when created with sufficient malice and volume.
No horizon
Qualifier: if created with sufficient malice and volume
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“User accounts must be more strenuously validated, and new systems like Harvard and Mozilla’s human-ID.org that allow for anonymous, bot-resistant authentication need to become mandatory; they are no longer a luxury we can afford to wait on.”
Our reading: User accounts must be more strongly validated and anonymous bot-resistant authentication should become mandatory.
No horizon
Assessment: SupportedSaid
Observation
“Large language models lack mechanisms for verifying truth; we need to find new ways to integrate them with the tools of classical AI, such as databases, webs of knowledge, and reasoning.”
Our reading: LLMs lack mechanisms for verifying truth.
No horizon Evidence as of
Limitation: The result depends on distinguishing standalone models from augmented systems.
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Large language models lack mechanisms for verifying truth; we need to find new ways to integrate them with the tools of classical AI, such as databases, webs of knowledge, and reasoning.”
Our reading: We need to integrate LLMs with classical AI tools such as databases, knowledge graphs, and reasoning to fight misinformation.
No horizon
Assessment: Can’t be checkedSaid
Rhetoric
“Executives at Meta and OpenAI are as enthusiastic about their tools as the proprietors of Jurassic Park were about theirs.”
Our reading: Executives at Meta and OpenAI are as enthusiastic about their tools as the proprietors of Jurassic Park were about theirs.
No horizon
Held from this post (5)
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: LLMs are great at generating misinformation but poor at fighting it.
- The record does not meet the current rules. Our reading, not assessed: For propagandists, LLM hallucinations and unreliability are a virtue rather than an obstacle.
- The record does not meet the current rules. Our reading, not assessed: The price of a custom-trained large language model (currently under $500,000) will soon drop further.
- The criteria are ambiguous. Our reading, not assessed: Generative AI systems like ChatGPT, Dall-E 2, and Lensa are inherently unreliable, frequently making errors of both reasoning and fact, and are prone to hallucination.
- The criteria are ambiguous. Our reading, not assessed: LLMs are here to stay and society is almost certain to be overrun by a tidal wave of misinformation.