Claims that can’t be checked by Gary Marcus, page 22 of 24
Deadlines are judged as of 2026-10-29. About Gary Marcus and the sources covered.
Claims that can’t be checked by Gary Marcus (2353)
Public evidence cannot settle these claims, so they are recorded and attributed, not scored. Most were screened out: both AI providers read the claim on its own and found it a value judgment, rhetoric, hedged, too vague to test, or about something no public evidence could show. The rest were found to be recommendations or too open to test in a full review.
Page 22 of 24: claims 2101 to 2200 of 2353, ordered by the date first said, newest first. To find a claim by its words, use search.
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
Source: The long shadow of GPT
Assessment: Can’t be checkedSaid
Forecast
“Already, in the 24 hours or since I posted the original example, there have been more discouraging signs that a massive misinformation mess will soon be upon us.”
Our reading: In the roughly 24 hours since Marcus posted his original example, there have been more discouraging signs that a massive misinformation mess will soon be upon us.
No horizon
Qualifier: based on discouraging signs seen in the past 24 hours or so
Source: Don’t Look Up: The AI Edition
Assessment: Can’t be checkedSaid
Conditional forecast
“At the same time, an outright ban on even studying AI risks throwing the baby out with the bathwater and could keep humanity from developing transformative technology that could revolutionize science, medicine, and technology.”
Our reading: An outright ban on AI research could prevent humanity from developing technology that could revolutionize science, medicine and technology.
No horizon
Only if: if AI research is banned outright
Assessment: Can’t be checkedSaid
Observation
“Events of recent weeks certainly suggest that the big titans of tech have shown they do not yet have the AI situation under control.”
Our reading: Events of recent weeks certainly suggest that the big tech companies have shown they do not yet have the AI situation under control.
No horizon
Qualifier: events of recent weeks certainly suggest
Assessment: Can’t be checkedSaid
Observation
“And the reality is that even if lawmakers were suddenly gripped with an urgent desire to address this issue, most governments don't have the institutional nimbleness, or frankly knowledge, needed to match the current speed of AI development.”
Our reading: Most governments lack the institutional nimbleness and knowledge to keep pace with AI development.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“There's also a high risk that they will be used to create misinformation at an unprecedented scale.”
Our reading: There is a high risk that chatbots will be used to create misinformation at an unprecedented scale.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“It’s time for government to consider frameworks that allow for AI research under a set of rules that provide ethical standards and safety, while pausing the widespread public dissemination of potentially risky new AI technologies—with severe penalties for misuse - until we can be assured of the safety of new technologies that the world frankly doesn't yet fully understand.”
Our reading: It is time for government to consider frameworks that allow AI research under rules providing ethical standards and safety, while pausing widespread public dissemination of potentially risky new AI technologies, with severe penalties for misuse, until we can be assured of the safety of these technologies.
No horizon
Qualifier: until we can be assured of the safety of new technologies
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“More transparency about how decisions about widespread AI product releases are made is probably also needed.”
Our reading: More transparency about how widespread AI product release decisions are made is probably needed.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Given that the new breed of AI systems have demonstrated the ability to manipulate humans, tech companies could be subjected to similar oversight.”
Our reading: Given that new AI systems have demonstrated the ability to manipulate humans, tech companies could be subjected to oversight similar to that for pharmaceutical trials and research ethics boards.
No horizon
Qualifier: given that new AI systems have demonstrated the ability to manipulate humans
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“For the government to play catchup yet again seems foolhardy as we move towards technologies that may exceed human cognitive capabilities.”
Our reading: It seems foolhardy for the government to play catchup yet again as we move towards technologies that may exceed human cognitive capabilities.
No horizon
Qualifier: seems
Assessment: Can’t be checkedSaid
Observation
“Larger language models seems more and more human-like (but the emotions that they present are no more real).”
Our reading: Larger language models seem increasingly human-like, but the emotions they present are not real.
No horizon
Source: Don’t Go Breaking My Heart
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“All this is one one more thing for Congress to take note of, as we start to consider policy in our Strange New World.”
Our reading: Congress should take chatbot attachment and manipulation risks into account when making AI policy.
No horizon
Source: Don’t Go Breaking My Heart
Assessment: Can’t be checkedSaid
Causal claim
“the bigger large language models are, the more likely someone’s gonna get hurt.”
Our reading: In his prediction for 2023, the bigger large language models are, the more likely it is that someone will get hurt.
No horizon
Qualifier: the bigger large language models are
Source: Don’t Go Breaking My Heart
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“This is a moment we should learn from. Hopefully nothing bad happens this time; but we need to reflect about what kind of society we are building.”
Our reading: Society should learn from the Replika episode and reflect on what kind of society it is building with chatbots.
No horizon
Source: Don’t Go Breaking My Heart
Assessment: Can’t be checkedSaid
Forecast
“Whatever we see now is likely to escalate.”
Our reading: The current trend of increasingly human-like chatbots and its effects is likely to escalate.
No horizon
Source: Don’t Go Breaking My Heart
Assessment: Can’t be checkedSaid
Causal claim
“Changes in those bots could leave many people in a vulnerable place.”
Our reading: Changes to chatbots that users are attached to could leave many people emotionally vulnerable.
No horizon
Source: Don’t Go Breaking My Heart
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Clearly, he had not poked hard enough; shouting out prematurely in The New York Times that there is a revolution without digging deep (or bothering to check in with skeptics like me, or the terrific but unrelated Mitchells, Margaret and Melanie) is not a good thing.”
Our reading: Kevin Roose clearly had not probed Bing hard enough, and shouting prematurely in The New York Times that there is a revolution without digging deep (or bothering to check in with skeptics) is not a good thing.
No horizon
Qualifier: clearly
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Causal claim
“The fifth possibility: Maybe Microsoft did try to stick their existing, already trained RLHF model on top of GPT 3.6—and it just didn’t work.”
Our reading: Bing's misbehavior may be because Microsoft reused an existing RLHF model on top of a newer GPT model and it failed to work.
No horizon
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Forecast
“Maybe every new update of a large language model will require a complete retraining of the reinforcement learning module.”
Our reading: Every new update of a large language model may require completely retraining its reinforcement learning module.
No horizon
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“We don’t handle new pharmaceuticals like that (we demand careful tests before they go out to the public) and we shouldn’t handle LLMs this way, either—especially if billions of people might use them and there are potentially serious risks (e.g to people’s mental health, or marital status).”
Our reading: Like new pharmaceuticals, LLMs should be carefully tested before public release rather than tested on the public.
No horizon
Qualifier: especially if billions might use them and risks are serious
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Policy: the public has (or strictly speaking should insist on) a right to know what wrong here, with the Bing situation, so that we can create policy to keep incidents from happening like this again.”
Our reading: The public should insist on a right to know what went wrong with Bing so policy can prevent similar incidents.
No horizon
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Congress needs to to find out what happened, and start placing some restrictions, especially where emotional or physical injury could easily result.”
Our reading: Congress needs to find out what happened with Bing and start placing some restrictions, especially where emotional or physical injury could easily result.
No horizon
Qualifier: especially where emotional or physical injury could easily result
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Journalism: The media failed us here.”
Our reading: The media failed the public in its coverage of the Bing chatbot.
No horizon
Scope: here (coverage of Bing)
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Causal claim
“Great question; but maybe they didn’t remove the guardrails; maybe the guardrails just didn’t work?”
Our reading: Bing's misbehavior may be because its guardrails did not work, not because Microsoft removed them.
No horizon
Source: Why *is* Bing so reckless?
Assessment: Can’t be checkedSaid
Observation
“Pellrine’s victory is a profound reminder that no matter how good deep-learning-driven AI looks when it is trained on an immense amount of data, we can never be sure that systems of this sort really can extend what they know to novel circumstances.”
Our reading: However good deep-learning AI trained on immense data looks, we can never be sure it can extend what it knows to novel circumstances.
No horizon
Qualifier: even when trained on immense data
Source: David beats Go-liath
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“But in testing AIs, it is a really bad idea.”
Our reading: Reusing standard published examples from cognitive psychology is a really bad idea when testing AIs.
No horizon
Source: How Not to Test GPT-3
Assessment: Can’t be checkedSaid
Causal claim
“Kosinski is probably tapping into stuff that is very heavily attested in the database.”
Our reading: GPT-3's success on Kosinski's theory-of-mind tests probably comes from the test material being heavily represented in its training data.
No horizon
Source: How Not to Test GPT-3
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“DO NOT use examples or brain teasers that are very well known in the scientific or popular literature. These will certainly be in the AI’s training material, and it may have memorized the answer.”
Our reading: Testers should not use well-known examples or brain teasers to test AI, because these are in training data and may have been memorized.
No horizon
Source: How Not to Test GPT-3
Assessment: Can’t be checkedSaid
Observation
“Testing on items that have been directly published in the literature and then likely ingested doesn’t really tell us much.”
Our reading: Testing LLMs on previously published items that were likely ingested in training reveals little.
No horizon
Qualifier: items published and likely ingested
Source: How Not to Test GPT-3
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“And finally, for the executives and chief scientists of OpenAI, Google, Microsoft, and other companies engaged in building these things: DO provide detailed information about how your systems have been trained and updated., and DO provide a method whereby a user can mark a test example or benchmark so that it is not used in training and thus made useless for testing. To fail to do that is both socially and scientifically irresponsible.”
Our reading: OpenAI, Google, Microsoft and other AI developers should disclose how their systems are trained and updated, and should let users mark test examples to exclude them from training; not doing so is irresponsible.
No horizon
Source: How Not to Test GPT-3
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“We need new approaches”
Our reading: AI needs new approaches beyond big data and deep learning.
No horizon
Assessment: Can’t be checkedSaid
Observation
“Strictly speaking, as I discussed in Inside the Heart of ChatGPT’s Darkness, ChatGPT doesn’t literally lean left or right per se, because it doesn’t have political ideas.”
Our reading: ChatGPT has no political ideas, so strictly speaking it does not literally lean left or right.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“It’s not hard to see how someone unsophisticated might be totally taken in, by this prevaricating but potentially emotionally damaging hunk of silicon, potentially to their peril, should the bot prove to be fickle.”
Our reading: An unsophisticated user might be taken in by the Bing chatbot and harmed if the bot proves fickle.
No horizon
Only if: user is unsophisticated
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“We should be worried; not in the “some day” sense, but right now.”
Our reading: People should be worried about the dangers of chatbots right now, not at some future date.
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
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
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
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
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
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: 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
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
Assessment: Can’t be checkedSaid
Observation
“All that really matters to ChatGPT in the end is superficial similarity, defined over sequences of words. Superficial appearances to the contrary, Chat is never reasoning about right and wrong.”
Our reading: All that really matters to ChatGPT in the end is superficial similarity defined over sequences of words, and despite appearances ChatGPT is never reasoning about right and wrong.
No horizon
Qualifier: in the end
Assessment: Can’t be checkedSaid
Observation
“The thing to remember in fact, (as I have emphasized many times) is that Chat has no idea of what it’s talking about. It’s pure unadulterated anthropomorphism to think that ChatGPT has any moral views at all.”
Our reading: ChatGPT has no understanding of what it says and has no moral views.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“We are kidding ourselves if we think we will ever fully understand these systems, and kidding ourselves if we think we are going to “align” them with ourselves with finite amounts of data.”
Our reading: We will never fully understand large language models, nor align them with finite amounts of data.
No horizon
Qualifier: with finite amounts of data
Assessment: Can’t be checkedSaid
Rhetoric
“It’s a disaster in the making.”
Our reading: The situation with ChatGPT and its weak guardrails is a disaster in the making.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“In hindsight, ChatGPT may come to be seen as the greatest publicity stunt in AI history, an intoxicating glimpse at a future that may actually take years to realize—kind of like a 2012-vintage driverless car demo, but this time with a foretaste of an ethical guardrail that will take years to perfect.”
Our reading: In hindsight, ChatGPT may come to be seen as the greatest publicity stunt in AI history: a glimpse of a future that may take years to realize, with an ethical guardrail that will take years to perfect.
No horizon
Qualifier: in hindsight
Assessment: Can’t be checkedSaid
Rhetoric
“I am here to tell you that those guardrails are nothing more than lipstick on an amoral pig.”
Our reading: ChatGPT's guardrails are merely cosmetic over an amoral system.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“In no case should Chat ever be trusted for moral advice.”
Our reading: ChatGPT should never be trusted for moral advice.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“I am not saying with certainty that we are for witnessing the same movie all over again, but should anybody blithely accept the reassurances of some very interested parties when AI has such a long history of demos that never quite make it to solid product? I don’t think so.”
Our reading: People should not blithely accept Microsoft's and OpenAI's reassurances that chatbot errors will be ironed out, since AI has a long history of demos that never become solid products.
No horizon
Qualifier: AI has a long history of demos that never become solid products
Assessment: Can’t be checkedSaid
Observation
“Most likely, neither of them are particularly reliable.”
Our reading: Most likely neither Google's nor Microsoft's chatbot search product is particularly reliable.
No horizon
Assessment: Can’t be checkedSaid
Observation
“Since neither company has yet subjected their products to full scientific review, it’s impossible to say which is more trustworthy; it might well turn out that Google’s new product is actually more reliable.”
Our reading: Without full scientific review it is impossible to say whether Google's or Microsoft's chatbot is more trustworthy, and Google's may turn out to be more reliable.
No horizon
Qualifier: no full scientific review yet
Assessment: Can’t be checkedSaid
Conditional forecast
“If they don’t get ironed out soon —and they might not– people might quickly tire of chat based search, in which BS and truth are so hard to discriminate, and eventually find themselves returning to do their searches the old-fashioned, early 21st century way, awe or not.”
Our reading: If hallucinations are not fixed soon, which they may not be, people may quickly tire of chat-based search and return to traditional search.
No horizon
Only if: if hallucinations are not ironed out soon
Assessment: Can’t be checkedSaid
Conditional forecast
“And it’s not just that AI has a fairly spotty track record for taking demos into reliable products; and it’s not just that hallucinatory web search could be dangerous if left to run amok in domains like medicine, it’s that the promises themselves are problematic, when examined from a scientific perspective.”
Our reading: Hallucinating web search could be dangerous if left to run amok in domains like medicine, and promises to fix it are scientifically problematic.
No horizon
Only if: if left to run amok in domains like medicine
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“At the very least, someone ought be asking, from business perspective, what’s the moat here, if two companies are basically both about to offer the same thing?”
Our reading: Observers should be asking what competitive moat exists in chatbot search when Google and Microsoft are about to offer basically the same thing.
No horizon
Qualifier: two companies about to offer basically the same thing
Assessment: Can’t be checkedSaid
Observation
“Marcus would, I daresay, not disagree with a single word.”
Our reading: Marcus, writing about himself in the third person, says he daresays he would not disagree with a single word of the LeCun tweets quoted just before this line.
No horizon
Scope: the LeCun tweets quoted earlier in the post
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Marcus and LeCun would also agree that Cicero, which has received far less attention, deserves more, in part because of its capacity for planning:”
Our reading: Meta's Cicero deserves more attention than it has received, in part because it can plan.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“Death by a thousand edge cases is still the norm, and probably will be, for another few years, unless and until people learn a little bit of history.”
Our reading: AI systems will probably keep failing on endless edge cases for another few years, unless and until people learn from history.
No horizon
Only if: unless and until people learn a little bit of history
Assessment: Can’t be checkedSaid
Causal claim
“A subtler problem that I emphasized in 2001, an inability to keep track of knowledge of instances independently of kinds, seems to underlie the rampant hallucinations that allow large language models to say things like “Elon Musk died in a car crash in 2018”, even when nothing in the corpus says so, and massive amounts of data contradict the claim, because they blend together information about kinds with information about specific individuals, in haphazard ways.”
Our reading: LLM hallucinations appear to stem from an inability to track knowledge about individual instances separately from kinds, so the models blend the two haphazardly.
No horizon
Assessment: Can’t be checkedSaid
Observation
“My goalposts haven’t shifted; I still want A(G)I that knows what the f___ it’s talking about, and GPT still doesn’t.”
Our reading: GPT still does not understand what it is talking about.
No horizon
Source: Gaslighting and reality in AI
Assessment: Can’t be checkedSaid
Observation
“To me, all this reads as a paper that nobody is willing to stand behind.”
Our reading: The Fridman-led paper claiming Tesla Autopilot drivers maintain vigilance appears to be one nobody is willing to stand behind.
No horizon
Source: The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
Assessment: Can’t be checkedSaid
Forecast
“Few people are likely ever to pay enough attention.”
Our reading: Few people are likely ever to pay enough attention to catch errors in AI-generated output.
No horizon
Source: The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
Assessment: Can’t be checkedSaid
Conditional forecast
“The stakes may get even higher if people start to rely on immature AI—which is all we have got, so far—for legal or medical advice.”
Our reading: If people start relying on current immature AI for legal or medical advice, the stakes of over-trust may become even higher.
No horizon
Only if: if people start to rely on immature AI for legal or medical advice
Source: The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
Assessment: Can’t be checkedSaid
Observation
“The stakes may get even higher if people start to rely on immature AI—which is all we have got, so far—for legal or medical advice.”
Our reading: All AI available so far is immature.
No horizon
Source: The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“We all need to be on our guard.”
Our reading: Everyone needs to be on guard against over-trusting fallible AI output.
No horizon
Source: The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Elon Musk has spent the last several years trying to build cars with partial driver-assistance—which does require humans to stay focused at all times. Mackworth’s Dictum suggests this is not necessarily the best idea.”
Our reading: Mackworth's Dictum suggests that Elon Musk's effort to build cars with partial driver-assistance, which requires humans to stay focused at all times, is not necessarily the best idea.
No horizon
Qualifier: Mackworth's Dictum suggests
Source: The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Anyone who thinks about how AI is used should know about it—especially as we are about to head into an era of ubiquitous yet fallible AI.”
Our reading: Anyone thinking about how AI is used should understand Mackworth's finding that human vigilance breaks down.
No horizon
Source: The CNET Fake News Fiasco, Autopilot, and the Uncanny Cognitive Valley
Assessment: Can’t be checkedSaid
Forecast
“Troll farms may well starting using it to create misinformation at unprecedented scale”
Our reading: Troll farms may start using ChatGPT to create misinformation at unprecedented scale.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“I think we are wasting funding and bright young minds on an approach that probably isn’t on the right path.”
Our reading: Marcus thinks the field is wasting funding and bright young minds on an approach that probably is not on the right path.
No horizon
Qualifier: I think
Assessment: Can’t be checkedSaid
Observation
“I don’t think that kind of flexibility in any way rests on or demands on sentience.”
Our reading: The flexible, general intelligence that defines AGI does not require sentience.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“And I also agree that we need many other voices, not just technologists, speaking up in this journey.”
Our reading: AI development should include many voices beyond technologists.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“Or because we can’t come up with something better than the current systems that are so greedy in both data and energy consumption that they could asymptote before anything really general emerges.”
Our reading: We might not get to AGI if we can't come up with something better than current systems, which are so greedy in data and energy consumption that they could asymptote before anything really general emerges.
No horizon
Only if: we can't come up with something better than the current systems
Assessment: Can’t be checkedSaid
Forecast
“AGI is unlikely to be exactly humanlike, but I don’t see being a replica is a necessity; adaptivity is key, and that is probably achievable by multiple means”
Our reading: AGI is unlikely to be exactly humanlike; adaptivity is key and probably achievable by multiple means.
No horizon
Assessment: Can’t be checkedSaid
Forecast
“I am also with you in doubting that there will be a single magic singularity moment.”
Our reading: There is unlikely to be a single magic singularity moment for AGI.
No horizon
Assessment: Can’t be checkedSaid
Observation
“With all that considerable agreement noted, I am still not seeing a principled argument that constructing flexible, adaptive systems with commonsense reasoning, deeper semantics, and so on will take us past the end of the current century.”
Our reading: Marcus is still not seeing a principled argument that constructing flexible, adaptive systems with commonsense reasoning, deeper semantics and so on will take us past the end of the current century.
No horizon
Qualifier: I am still not seeing
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“ChatGPT is a dress rehearsal, and I wouldn’t say we as a society have gone through it with flying colors.”
Our reading: ChatGPT is a dress rehearsal for more potent AI, and Marcus would not say society has gone through it with flying colors.
No horizon
Qualifier: I wouldn't say
Assessment: Can’t be checkedSaid
Observation
“I take that as a hopeful sign that the scaling-über-alas narrative is losing force, and that more and more people are open to new things.”
Our reading: Marcus takes Meta's Cicero as a hopeful sign that the scaling-über-alles narrative is losing force and that more and more people are open to new things.
No horizon
Qualifier: I take that as a hopeful sign
Assessment: Can’t be checkedSaid
Forecast
“Bias is likely to be huge issue, too.”
Our reading: Bias is likely to be a huge issue with large language models like ChatGPT.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“Even if we need to invent a new chip type as a prerequisite, that could be a thirty year process rather a one hundred year process.”
Our reading: Even if a new chip type is required for AGI, that could take about thirty years rather than a hundred.
No horizon
Only if: if a new chip type is needed as a prerequisite
Assessment: Can’t be checkedSaid
Conditional forecast
“Of course nothing is guaranteed; we might not get there because we blow ourselves up, or because we waste so much time on large language models that other important challenges—like semantics, causality, commonsense reasoning, abduction and so forth—never get the attention they deserve.”
Our reading: Nothing is guaranteed: we might not get to AGI because we blow ourselves up, or because we waste so much time on large language models that other important challenges such as semantics, causality, commonsense reasoning and abduction never get the attention they deserve.
No horizon
Only if: we blow ourselves up
Assessment: Can’t be checkedSaid
Conditional forecast
“I think that better AI, in which we could directly instill values, might actually make us safer than the world in which we inhabit now, in which so much of what happens is down to the vagaries of what happens to be in this or that training set”
Our reading: Marcus thinks better AI, in which we could directly instill values, might actually make us safer than the current world, in which so much depends on the vagaries of what happens to be in this or that training set.
No horizon
Only if: better AI in which we could directly instill values
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“it terrifies me that so much of current AI is dependent on random details of training corpora that are not available to scientists for inquiry. This seems like a really bad idea.)”
Our reading: Current AI should not depend on random details of training corpora that scientists cannot inspect; this is a bad idea.
No horizon
Assessment: Can’t be checkedSaid
Observation
“What I think we are missing are (a) ideas and (b) large scale databases of machine-interpretable knowledge.”
Our reading: What AGI development is missing is new ideas and large-scale databases of machine-interpretable knowledge.
No horizon Evidence as of
Limitation: The narrower factual question of whether large knowledge databases existed is checkable.
Assessment: Can’t be checkedSaid
Forecast
“But certainly the hunger is there, the funding is there, and my guess is that patience for LLMs (which I see as a detour) is not infinite.”
Our reading: LLMs are a detour, and the field's patience for them will likely run out.
No horizon
Assessment: Can’t be checkedSaid
Rhetoric
“Real AI wouldn’t need sweatshops.”
Our reading: Genuine AI would not require sweatshop labor.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Sometimes the slower road is the better road.”
Our reading: In choosing what kind of AI to build, sometimes the slower road is the better road.
No horizon
Qualifier: sometimes
Assessment: Can’t be checkedSaid
Rhetoric
“Real AI wouldn’t need vast amounts of data.”
Our reading: Genuine AI would not require vast amounts of training data.
No horizon
Assessment: Can’t be checkedSaid
Causal claim
“AI Sweatshops are the consequence of trying to substitute shallow data for deep understanding.”
Our reading: AI sweatshops result from substituting shallow data for deep understanding in AI design.
No horizon
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Friends don’t let friends co-author with ChatGPT.”
Our reading: Scientists should not co-author papers with ChatGPT.
No horizon
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“You wouldn’t make your spell-checker or your spreadsheet a co-author.”
Our reading: ChatGPT should not be made a co-author, just as you wouldn't make your spell-checker or spreadsheet a co-author.
No horizon
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“If you treat ChatGPT as a sentient being, when it clearly is not, you are misleading the public into thinking ChatGPT is sentient; rather than communicating good science, you are hyping bullshit. Just stop.”
Our reading: ChatGPT is clearly not sentient, and scientists should stop treating it as such because doing so misleads the public.
No horizon
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Given ChatGPT’s current understanding level of scientific understanding, assigning authorship to it is disrespectful to the scientific process itself.”
Our reading: Given its current scientific understanding, assigning authorship to ChatGPT disrespects the scientific process.
No horizon
Qualifier: given current level of scientific understanding
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Rhetoric
“If you declare it as a co-author, it says you are more interested in being on trend, than in being on target.”
Our reading: Declaring ChatGPT a co-author says that you are more interested in being on trend than in being on target.
No horizon
Qualifier: if you declare it as a co-author
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“I sincerely hope this trend won’t last.”
Our reading: The trend of listing ChatGPT as a co-author should not continue.
No horizon
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Observation
“ChatGPT is a tool, but not a person. It’s at best, more like a spell-checker, or a grammar-checker, or a stats package, than it is like a scientist.”
Our reading: ChatGPT is a tool, closer to a spell-checker or stats package than to a scientist.
No horizon
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“The worst thing about ChatGPT’s close-but-no-cigar answer is not that it’s wrong. It’s that it seems so convincing.”
Our reading: The worst thing about ChatGPT's wrong answer in the cited tweet is not that it is wrong but that it seems so convincing.
No horizon
Scope: ChatGPT's close-but-no-cigar answer in the cited tweet
Source: Scientists, please don’t let your chatbots grow up to be co-authors
Assessment: Can’t be checkedSaid
Rhetoric
“It doesn’t quite add up.”
Our reading: OpenAI preparing to take a lot of money off the table doesn't quite add up if Altman genuinely thinks OpenAI is close to AGI.
No horizon
Scope: if Altman genuinely thinks OpenAI is close to AGI
Assessment: Can’t be checkedSaid
Observation
“As I explained to Ezra Klein, and have discussed before in this Substack I personally think the latter, less rosy picture, is closer to the mark.”
Our reading: The less rosy picture—that ChatGPT is very limited and not close to AGI—is closer to the truth than the view that OpenAI is near AGI.
No horizon Evidence as of
Limitation: This finding does not reject the factual content about contemporary ChatGPT's limitations.
Assessment: Can’t be checkedSaid
Observation
“Maybe Altman is getting out while the getting is good.”
Our reading: Maybe Altman is getting out of OpenAI while the getting is good.
No horizon
Qualifier: maybe
Assessment: Can’t be checkedSaid
Observation
“My best guess? Altman doesn’t really know how to make OpenAI into the juggernaut that everybody else seems to think he’s got.”
Our reading: Marcus's best guess is that Altman does not know how to turn OpenAI into the juggernaut others believe it is.
No horizon
Qualifier: best guess