Claims that can’t be checked, page 33 of 37
Claims by Gary Marcus and Ed Zitron. Deadlines are judged as of 2026-10-29.
Claims that can’t be checked (3643)
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 33 of 37: claims 3201 to 3300 of 3643, ordered by the date first said, newest first. To find a claim by its words, use search.
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“The risks of current AI (bias, defamation, cybercrime, wholesale disinformation, etc) are already starting to be well documented and may themselves quickly escalate, and could lead to geopolitical instability even over the next few years.”
Our reading: Documented risks of current AI such as bias, defamation, cybercrime and disinformation may escalate quickly and could cause geopolitical instability within the next few years.
No horizon
Source: 𝐩(𝐝𝐨𝐨𝐦)
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Personally, despite the name of this essay, I am not all that worried about humans going extinct anytime very soon.”
Our reading: Marcus says he is not all that worried about humans going extinct anytime very soon.
No horizon
Scope: anytime very soon
Source: 𝐩(𝐝𝐨𝐨𝐦)
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“I do think there is a lot of risk that AI will cause chaos.”
Our reading: There is a substantial risk that AI will cause chaos.
No horizon
Source: 𝐩(𝐝𝐨𝐨𝐦)
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“The fact that the US is apparently using these tools, or the fact that they aren’t likely to be reliable, almost certainly regularly reporting false alarms, and likely full of insidious bias, like so many previous AI systems have shown themselves to be?”
Our reading: The AI surveillance tools the US government is apparently using are likely not reliable.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“The fact that the US is apparently using these tools, or the fact that they aren’t likely to be reliable, almost certainly regularly reporting false alarms, and likely full of insidious bias, like so many previous AI systems have shown themselves to be?”
Our reading: The AI tools the US is apparently using to surveil its citizens are likely full of insidious bias, as so many previous AI systems have shown themselves to be.
No horizon
Qualifier: likely
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“This could be particularly devastating because Large Language Models aren’t like classical databases in which individual pieces of data can be removed at will; if any content is removed, the entire model must (so far as I understand it) be retrained, at great expense.”
Our reading: The potential New York Times lawsuit could be particularly devastating for OpenAI because, unlike classical databases, LLMs cannot have individual pieces of data removed at will; as far as Marcus understands it, removing any content means retraining the entire model at great expense.
No horizon
Only if: if any content is removed
Source: The Rise and Fall of ChatGPT?
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“It ain’t over yet, but what a stunning reversal of fortune.”
Our reading: ChatGPT has suffered a stunning reversal of fortune, though the story is not over.
No horizon
Qualifier: it ain't over yet
Source: The Rise and Fall of ChatGPT?
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Maybe it’s too soon to declare victory on my August 12th bet that ChatGPT will turn out to be a dud, but I will tell you one thing, it’s not obvious I am wrong.”
Our reading: As of late August 2023, it is not obvious that Marcus's bet that ChatGPT will turn out to be a dud is wrong, though it may be too soon to declare victory.
No horizon
Qualifier: may be too soon to declare victory
Source: The Rise and Fall of ChatGPT?
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“We see few risks in the current regime, but fewer reasons to tempt fate by blithely assuming that anything that we might invent can be dealt with.”
Our reading: We should not blithely assume that anything we might invent in AI can be dealt with.
No horizon
Source: Sentient AI: For the love of Darwin, let’s Stop to Think if We Should
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“AI, like any technology, is subject to the risk of unintended consequences, quite possibly more so, and the wider we open Pandora’s box, the more risk we assume.”
Our reading: AI is subject to the risk of unintended consequences, possibly more than other technologies, and expanding its capabilities increases that risk.
No horizon
Qualifier: the wider we open Pandora's box
Source: Sentient AI: For the love of Darwin, let’s Stop to Think if We Should
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Let’s not dumb down our standards, and wind up with a bunch of machines we can’t rely on, just so that big tech can prematurely declare victory, when there is plenty of work left to do.”
Our reading: AGI standards should not be lowered so big tech can prematurely declare victory, since much work remains.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“I seriously doubt it.”
Our reading: Marcus seriously doubts that AI is close to beating typical human performance on virtually all cognitive tasks.
No horizon
Qualifier: AGI as defined by Legg
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“Humans can write summaries and reliably answer many questions about original films and television programs that they watch; I doubt LLMs (or any other extant AI technology) can do this at all.”
Our reading: Marcus doubts LLMs or any extant AI can summarize and reliably answer questions about original films and TV programs.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“It’s a huge downgrade in our goals for artificial general intelligence to say “better than the average untrained human on many tasks”; the point is that we should expect machines to do what we ask them to do;”
Our reading: Saying AGI means 'better than the average untrained human on many tasks' is a huge downgrade in our goals for AGI, because we should expect machines to do what we ask them to do.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“An artificial general intelligence should do the things that it is asked to do, and decline to do those that it can’t, and have the wisdom to know the difference.”
Our reading: An AGI should do what it is asked, decline what it cannot do, and know the difference.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“And frankly, we still have a long way to go on all the things I always harp on: reasoning, compositionality, planning, factuality, and so on.”
Our reading: AI still has a long way to go on reasoning, compositionality, planning, and factuality.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“No AGI worth its salt would brick multidigit arithmetic.”
Our reading: A genuine AGI must reliably do multidigit arithmetic.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Dropping from “as smart as the Star Trek computer” to better than Joe Sixpack should not be our goal.”
Our reading: The AI field should not lower its AGI goal from Star Trek computer-level to merely beating an average person.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“(If that doesn’t remind you of LLMs, you aren’t paying attention.)”
Our reading: Marcus suggests that the way driverless-car safety depends on data rather than reasoning should remind attentive readers of LLMs.
No horizon
Source: Face it, self-driving cars still haven’t earned their stripes
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Scaling up to driving everywhere all the time without a well-vetted serious, well-vetted solution to the edge case problem was insane; it was quite literally an accident (or series of accidents) waiting to happen.”
Our reading: Approving 24/7 driverless operation across San Francisco without a vetted solution to edge cases was reckless and bound to lead to accidents.
No horizon
Qualifier: without a well-vetted solution to edge cases
Source: Face it, self-driving cars still haven’t earned their stripes
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If we don’t, we are likely to see reprises of what we see now with driverless cars, in automated doctors, automated psychiatrists, all purpose virtual assistants, home robots, and more, probably for years to come.”
Our reading: If we do not shift our focus toward developing new methodologies for coping with edge cases, we are likely to see reprises of today's driverless-car problems in automated doctors, automated psychiatrists, all-purpose virtual assistants, home robots and more, probably for years to come.
No horizon
Only if: if we don't stop hammering a square peg into a round hole and shift focus toward developing new methodologies for edge cases
Source: Face it, self-driving cars still haven’t earned their stripes
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“I wouldn’t trust a self-driving plane, and I don’t think any quasi-self-driving car has yet earned its stripes either.”
Our reading: Marcus would not trust a self-driving plane, and he does not think any quasi-self-driving car has yet earned its stripes.
No horizon
Qualifier: I don't think
Source: Face it, self-driving cars still haven’t earned their stripes
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“Elections may hinge on them.”
Our reading: Elections may hinge on automatic misinformation generation systems.
No horizon
Source: Automatic Disinformation Threatens Democracy— and It’s Here
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“We ought to demand that any content like this that is automatically generated be labeled (no existing law does that) and watermarked (no existing law does that either)”
Our reading: We ought to demand that any automatically generated content like this (the CounterCloud-style misinformation discussed) be labeled and watermarked, and no existing law requires either.
No horizon
Scope: any content like this that is automatically generated
Source: Automatic Disinformation Threatens Democracy— and It’s Here
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“The temptation for all sides to use these tools is likely to be overwhelming.”
Our reading: The temptation for all political sides to use automatic misinformation tools is likely to be overwhelming.
No horizon
Source: Automatic Disinformation Threatens Democracy— and It’s Here
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“What we really need is AI that is smart enough to know when it is being used to spew falsehood.”
Our reading: We need AI smart enough to know when it is being used to spread falsehoods.
No horizon
Source: Automatic Disinformation Threatens Democracy— and It’s Here
Assessment: Can’t be checkedSaid
Gary Marcus Rhetoric
“The killer app of AGI may be killing truth.”
Our reading: The killer app of AGI may be killing truth.
No horizon
Qualifier: may
Source: Automatic Disinformation Threatens Democracy— and It’s Here
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“we ought to demand that the wholesale generation of misinformation be punishable; there ought to be enforcement.”
Our reading: Wholesale generation of misinformation should be punishable and enforced against.
No horizon
Source: Automatic Disinformation Threatens Democracy— and It’s Here
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Businesses may be at a disadvantage if they too don’t use such systems, e.g., to counter adverse news, automatically.”
Our reading: Businesses that do not use automatic misinformation generation systems may be at a disadvantage.
No horizon
Only if: if they don't use automatic misinformation generation systems
Source: Automatic Disinformation Threatens Democracy— and It’s Here
Assessment: Can’t be checkedSaid
Gary Marcus 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 search, may eventually become the biggest threat Google ever faces.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“But things have actually gotten worse than I anticipated.”
Our reading: Pollution of the internet by LLM-generated content became worse between February and August 2023 than Marcus had expected.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus 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 users are left sifting through floods of useless misinformation, the value of search would fall to zero, which could kill Google.
No horizon
Only if: if users are left sifting through sewers full of useless misinformation
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“The astronomical valuations for Generative AI companies might be justified, but might well not be. Thus far, the valuations seem to be predicated on hopes and dreams, without really factoring in the serious engineering risks.”
Our reading: The astronomical valuations of generative AI companies might be justified but might well not be, and so far they seem to be predicated on hopes and dreams without really factoring in the serious engineering risks.
No horizon
Qualifier: might be justified, but might well not be
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“A lot of talent and investors might move on to a new set of shiny things, fleeing generative AI as quickly as some of the same people not long ago fled crypto.”
Our reading: A lot of talent and investors might move on to a new set of shiny things, fleeing generative AI as quickly as some of the same people recently fled crypto.
No horizon
Scope: a lot of talent and investors
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“As I argued yesterday, the whole thing could turn out to be a fad, but it’s still way too early too tell.”
Our reading: Generative AI could turn out to be a fad, though it is too early to tell.
No horizon
Qualifier: too early to tell
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“I am doubtful that Microsoft would let OpenAI go under anytime soon, given the optics, and impact on their own stock price.”
Our reading: Microsoft is unlikely to let OpenAI go under anytime soon.
No horizon
Qualifier: given optics and stock price impact
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“It’s not a house of cards, but the financial foundation of so-called Foundation Models is hardly as robust as it seems.”
Our reading: The financial foundation of so-called foundation models is not a house of cards, but it is hardly as robust as it seems.
No horizon
Qualifier: not a house of cards
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“We now know that answers can even change from one month to the next—which makes third-party engineering of large language models into complex systems a huge uphill struggle. In some mission-critical cases that engineering challenge may be insuperable.”
Our reading: Because LLM answers can even change from one month to the next, third-party engineering of large language models into complex systems is a huge uphill struggle, and in some mission-critical cases that challenge may be insuperable.
No horizon
Qualifier: answers can change from one month to the next
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If some people get off the bus, and valuations begin to drop a little, that could launch a potent negative feedback spiral, sparking a sudden deceleration in values that heretofore had been rapidly accelerating.”
Our reading: If some people get off the bus and generative AI valuations begin to drop a little, that could launch a potent negative feedback spiral, sparking a sudden deceleration in values that had been rapidly accelerating.
No horizon
Only if: if some people get off the bus and valuations begin to drop a little
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“LLMs will probably get cheaper to operate over time, both as the hardware required inevitably gets cheaper, and as people figure out how to make them more efficient.”
Our reading: LLMs will probably become cheaper to operate over time as hardware cheapens and efficiency improves.
No horizon
Qualifier: hardware gets cheaper
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“That said, I don’t think OpenAI is actually in any kind of imminent danger, but nor do I think they are out of the woods.”
Our reading: Marcus does not think OpenAI is in any kind of imminent danger, but he also does not think it is out of the woods.
No horizon Evidence as of
Limitation: This does not judge the reasonableness of his financial concerns.
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“I seriously doubt it. We have not one, but many, serious, unsolved problems at the core of generative AI”
Our reading: Marcus seriously doubts the projections of near-term AGI, including Dario Amodei's projection that we will have AGI in 2-3 years from August 2023.
Deadline passed Evidence as of
Limitation: This record does not assess whether AGI arrived by August 2026. The post describes AGI broadly, as general purpose AI 'as smart and resourceful as humans if not more so', but gives no test for it.
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“But neither coding nor high-speed, mediocre quality copy-writing are remotely enough to maintain current valuation dreams.”
Our reading: Coding and mediocre copywriting use cases are nowhere near enough to justify current generative AI valuations.
No horizon Evidence as of
Limitation: The evidence does not establish that the valuation judgment was right or wrong.
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If hallucinations aren’t fixable, generative AI probably isn’t going to make a trillion dollars a year. And if it probably isn’t going to make a trillion dollars a year, it probably isn’t going to have the impact people seem to be expecting.”
Our reading: If hallucinations aren't fixable, generative AI probably won't earn a trillion dollars a year or have the expected impact.
No horizon
Only if: if hallucinations aren't fixable
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“With the possible exception of the quick to rise and quick to fall alleged room-temperature superconductor LK-99, few things I have ever seen have been more hyped than generative AI.”
Our reading: Generative AI is among the most hyped things the author has ever seen.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“And if it isn’t going to have that impact, maybe we should not be building our world around the premise that it is.”
Our reading: If generative AI isn't going to have the impact people seem to expect, maybe we should not be building our world around the premise that it will.
No horizon
Only if: if generative AI isn't going to have the impact people seem to be expecting
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“Even OpenAI could have a hard time following through on its $29 billion valuation; competing startups valued in the low billions might well eventually collapse, if year after year they manage only tens or hundreds of millions in revenue.”
Our reading: OpenAI could have difficulty living up to its $29 billion valuation.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Even OpenAI could have a hard time following through on its $29 billion valuation; competing startups valued in the low billions might well eventually collapse, if year after year they manage only tens or hundreds of millions in revenue.”
Our reading: Generative AI startups valued in the low billions might well eventually collapse if they earn only tens or hundreds of millions annually.
No horizon
Only if: if they manage only tens or hundreds of millions in revenue year after year
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If it isn’t, the bubble could easily burst.”
Our reading: If hallucination is not solved soon, the generative AI bubble could easily burst.
No horizon
Only if: if hallucination is not solved soon
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If Evans’ experience is a canary in a coal mine, the whole generative AI field, at least at current valuations, could come to a fairly swift end.”
Our reading: If user disillusionment like Evans' is representative, the generative AI field at current valuations could end fairly swiftly.
No horizon
Only if: if Evans' disillusionment is representative
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“if the premise that generative AI is going to be bigger than fire and electricity turns out to be mistaken, or at least doesn’t bear out in the next decade, it’s certainly possible that we could wind up with what in hindsight is a lot of needless extra tension with China, possibly even a war in Taiwan, over a mirage”
Our reading: If the premise that generative AI will be bigger than fire and electricity proves mistaken, or at least does not bear out in the next decade, it is certainly possible that we could end up with a lot of needless extra tension with China over a mirage, possibly even a war in Taiwan.
No horizon
Only if: if the premise that generative AI will be bigger than fire and electricity turns out to be mistaken, or at least doesn't bear out in the next decade
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Those revenues genuinely could grow by 1000x, but that’s mighty speculative. We shouldn’t simply assume it.”
Our reading: We should not assume generative AI revenues will grow 1000x, which is highly speculative.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“Other potential paying customers may lose heart quickly.”
Our reading: Other potential paying customers of generative AI, beyond coders and undergraduates, may lose heart quickly.
No horizon
Scope: other potential paying customers (beyond coders and undergraduates)
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“Microsoft, up for the year by nearly half, perhaps largely on the promise of generative AI, might see a stock slump; NVIDIA skyrocketing even more, might also fall.”
Our reading: Microsoft's stock, up nearly half for the year perhaps largely on the promise of generative AI, might slump, and NVIDIA's stock, which has risen even more, might also fall.
No horizon
Qualifier: perhaps largely on the promise of generative AI
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“Everybody in industry would probably like you to believe that AGI is imminent. It stokes their narrative of inevitability, and it drives their stock prices and startup valuations.”
Our reading: Everybody in industry would probably like you to believe that AGI is imminent, because that belief stokes their narrative of inevitability and drives their stock prices and startup valuations.
No horizon
Qualifier: probably
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“It’s foolish to imagine that such challenging problems will all suddenly be solved.”
Our reading: It is foolish to imagine that generative AI's challenging core problems will all suddenly be solved.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“We might not get the consumer protections we need, because we are trying to foster something that may not grow as expected.”
Our reading: The US might fail to get needed consumer protections because it is fostering generative AI, which may not grow as expected.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“But, to begin with, the revenue isn’t there yet, and might never come.”
Our reading: Generative AI revenue is not yet there and might never materialize.
No horizon
Assessment: Can’t be checkedSaid
Ed Zitron Recommendation or value judgment
“The output from ChatGPT or any other generative AI feels utterly soulless”
Our reading: Output from ChatGPT or any other generative AI feels utterly soulless.
No horizon
Qualifier: feels (subjective impression)
Source: The Age Of Mediocrity
Assessment: Can’t be checkedSaid
Ed Zitron Forecast
“They crave a new Industrial Revolution where simulations of human beings do a shittier job slightly faster without needing to be paid to do it, or with a human being as a handler that must constantly refine and buff up work in a way that will likely take more time than having a human do it in the first place.”
Our reading: AI work that requires a human handler to constantly refine it will likely take more time than having a human do the work in the first place.
No horizon
Source: The Age Of Mediocrity
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Throughout the time in which I have been advocating for international AI governance, I have emphasized the need to have scientists and civil society more generally at the table.”
Our reading: International AI governance should include scientists and civil society at the table.
No horizon
Source: Jumpstarting AI Governance
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“Many of us have also become worried about the possibility of regulatory capture, and whether shrewd executives at the major tech companies might induce governments to alight on regulation that ultimately does more harm than good, keeping out smaller players, and entrenching Big Tech’s own status, while doing little to address the underlying risks, such as around misinformation and cybercrime.”
Our reading: Major tech company executives might get governments to adopt AI regulation that does more harm than good by keeping out smaller players and entrenching Big Tech, while doing little about risks like misinformation and cybercrime.
No horizon
Source: Jumpstarting AI Governance
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If we can produce the right package of tools and expertise for auditing, prerelease examination, and so on, address questions of bias, reliability, misinformation and so forth, working together of course with existing agencies that have been aiming to craft related standards, adoption may be swift.”
Our reading: If CATAI can produce the right package of tools and expertise for auditing, prerelease examination, and so on, and address questions of bias, reliability, misinformation and so forth, working with existing agencies that have been aiming to craft related standards, adoption may be swift.
No horizon
Only if: if CATAI can produce the right package of tools and expertise for auditing, prerelease examination, and so on
Source: Jumpstarting AI Governance
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“He believes that he can somehow monetize Twitter’s data by selling it to AI companies without any real understanding of the economics of doing so.”
Our reading: Musk believes he can make money by selling Twitter's data to AI companies but has no real understanding of the economics of doing so.
No horizon
Source: The End of the Honest Internet
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“As with many things Musk has said, this sounds utterly made up.”
Our reading: Musk's justification that rate-limiting was needed to stop bad actors scraping Twitter to build AI models sounds made up.
No horizon
Source: The End of the Honest Internet
Assessment: Can’t be checkedSaid
Ed Zitron Causal claim
“While some are suggesting that the most obvious reason for rate-limiting was Musk’s failure to pay his bills, the real one may be far more obvious — that Musk decided he was going to “fix” a problem that had been present for a while, or did not exist.”
Our reading: The real reason for Twitter's rate-limiting may be that Musk tried to fix a scraping problem that had existed for a long time or did not exist at all.
No horizon
Source: The End of the Honest Internet
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“What really matters is what governments around the world come up with by way of regulation.”
Our reading: What really matters is the regulation that governments around the world come up with.
No horizon
Scope: governments around the world
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“More broadly, at an absolute minimum governments need to establish an approval process for any AI that deployed at large scale, showing that the benefits outweigh the risks, and to mandate post-release auditing - by independent outsiders - of any large-scale deployments.”
Our reading: At an absolute minimum, governments need to establish an approval process for any AI deployed at large scale that shows the benefits outweigh the risks, and need to mandate post-release auditing of any large-scale deployment by independent outsiders.
No horizon
Qualifier: at an absolute minimum
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“What I am worried about is regulatory capture; governments making rules that entrench the incumbents whilst doing too little for humanity.”
Our reading: There is a risk that governments make AI rules that entrench incumbents while doing too little for humanity.
No horizon
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“We would never leave the pharmaceutical industry to entirely self-regulate itself, and we shouldn’t leave AI to do so, either.”
Our reading: The AI industry should not be left to regulate itself, just as pharma is not.
No horizon
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Forecast
“We still have agency here; we can still, I think, build a very positive AI future.”
Our reading: It is still possible to build a very positive AI future.
No horizon
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Press releases and photo opportunities that highlight governments hanging out with the tech moguls they seek to regulate, without independent voices in the room, send entirely the wrong message.”
Our reading: Government photo opportunities with tech moguls without independent voices send the wrong message.
No horizon
Qualifier: without independent voices in the room
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“And governments need to make sure that there are strong liability laws in place, to ensure that if the big tech companies cause harm with their products, they be held responsible.”
Our reading: Governments need to make sure strong liability laws are in place so that, if big tech companies cause harm with their products, they are held responsible.
No horizon
Qualifier: if the big tech companies cause harm with their products
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“I actually think that he is at least in part sincere, that it is not just a ploy to keep the incumbents in and small competitors out, that he is genuinely worried about the risks (ranging from misinformation, to serious physical harm to humanity).”
Our reading: Marcus thinks Sam Altman is at least in part sincere in asking for AI regulation, that it is not just a ploy to keep incumbents in and small competitors out, and that he is genuinely worried about AI risks ranging from misinformation to serious physical harm to humanity.
No horizon
Qualifier: I actually think
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“Goverments should demand that systems only use copyrighted content from content providers that opt-in, and that all machine-generated content be labeled as such.”
Our reading: Governments should require AI systems to use copyrighted content only from opt-in providers and to label all machine-generated content.
No horizon
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“This is where the government needs to step up and say “transparency and safety are indeed requirements; you’ve flouted them; we won’t let you do that anymore.””
Our reading: Government should require transparency and safety from AI companies and stop them from flouting those requirements.
No horizon
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“If big tech writes the rules, without outside input, we are unlikely to wind up with the right rules.”
Our reading: If big tech writes AI rules without outside input, the right rules are unlikely to result.
No horizon
Only if: big tech writes the rules without outside input
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“We don’t need more photo opportunities, we need regulation – with teeth.”
Our reading: AI needs enforceable regulation rather than photo opportunities.
No horizon
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Putting it bluntly: if we have the right regulation; things could go well. If we have the wrong regulation, things could badly.”
Our reading: With the right AI regulation things could go well; with the wrong regulation things could go badly.
No horizon
Only if: right vs wrong regulation
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“But much depends on how much the government stands up to big tech, and a lot of that depends on having independent voices – scientists, ethicists, and representatives of civil society – at the table.”
Our reading: The AI future depends largely on government standing up to big tech, which depends on independent voices being at the table.
No horizon
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Gary Marcus Conditional forecast
“Letting the companies set the rules on their own is unlikely to get us any of these places.”
Our reading: If AI companies set the rules on their own, the needed safeguards are unlikely to result.
No horizon
Only if: companies set the rules on their own
Source: Two models of AI oversight - and how things could go deeply wrong
Assessment: Can’t be checkedSaid
Ed Zitron Forecast
“While I’m not suggesting that every company will follow this model, this feels like an inevitable consequence of artificial intelligence adoption.”
Our reading: It feels like an inevitable consequence of AI adoption that companies will follow the model of offering little meaningful customer support, though he does not suggest every company will follow it.
No horizon
Qualifier: this feels like
Source: Artificial Labor
Assessment: Can’t be checkedSaid
Ed Zitron Observation
“While a human being may have to make the burger (for now), I believe the fast food industry’s eventual goal is to make human beings a conveyance rather than anything approaching customer service.”
Our reading: Zitron believes the fast food industry's eventual goal is to make human beings a conveyance rather than anything approaching customer service, even if a human may have to make the burger for now.
No horizon
Qualifier: I believe
Source: Artificial Labor
Assessment: Can’t be checkedSaid
Ed Zitron Causal claim
“And I think that this is what’s truly powering executive excitement over artificial intelligence – the idea that workers can eventually be removed from the equation entirely.”
Our reading: Zitron thinks that what is truly powering executive excitement over AI is the idea that workers can eventually be removed from the equation entirely.
No horizon
Qualifier: I think
Source: Artificial Labor
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“have very much converged on a picture in which there is serious risk—both short-term and long—”
Our reading: AI poses serious risk in both the short term and the long term, a view Marcus says he and Hinton now share.
No horizon
Qualifier: both short-term and long-term
Source: AI risks, short-term and long—and what we need to do about them
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“equally serious need to have independent scientists at the table”
Our reading: There is a serious need to have independent scientists involved in decisions about managing AI risk.
No horizon
Source: AI risks, short-term and long—and what we need to do about them
Assessment: Can’t be checkedSaid
Ed Zitron Recommendation or value judgment
“These are reasonable requests.”
Our reading: The WGA's strike demands, including guarantees on how AI is used in union productions, are reasonable.
No horizon
Qualifier: refers to WGA strike demands, including guarantees around AI use in union productions
Source: Absentee Capitalism
Assessment: Can’t be checkedSaid
Ed Zitron Causal claim
“Executive excitement around generative AI is borne from these disconnected economics, because none of these people actually create anything.”
Our reading: Executives are excited about generative AI because they are cut off from production and do not create anything themselves.
No horizon
Source: Absentee Capitalism
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“He thinks neural networks “understand” the world; I think they do not.”
Our reading: Neural networks do not understand the world.
No horizon
Source: Scientists, governments, and corporations urgently need to work together to mitigate AI risk
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“In endorsing the “pause letter” (despite expressing some concerns about the details), I was saying we need to slow down, and to focus on the kind of research that the pause letter emphasized, viz work on making sure that AI systems would be trustworthy and reliable.”
Our reading: AI development needs to slow down and focus on research making AI systems trustworthy and reliable.
No horizon
Source: Scientists, governments, and corporations urgently need to work together to mitigate AI risk
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“I’ve been writing with urgency about my concerns about the contributions of large language models misinformation, and my concerns about how bad actors might misuse AI, and in my essay AI risk ≠ AGI risk, argued that we should worry about both near-term and long-term risks.”
Our reading: We should worry about both near-term AI risks (such as LLM misinformation and misuse by bad actors) and long-term AI risks.
No horizon
Source: Scientists, governments, and corporations urgently need to work together to mitigate AI risk
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“the immediate development of a global, neutral, non-profit International Agency for ai (iaai), with guidance and buy-in from governments, large technology companies, non-profits, academia and society at large, aimed at collaboratively finding governance and technical solutions to promote safe, secure and peaceful ai technologies”
Our reading: There should be immediate development of a global, neutral, non-profit International Agency for AI (IAAI), with guidance and buy-in from governments, large technology companies, non-profits, academia and society at large, aimed at collaboratively finding governance and technical solutions to promote safe, secure and peaceful AI technologies.
No horizon
Qualifier: with guidance and buy-in from governments, large technology companies, non-profits, academia and society at large
Source: Scientists, governments, and corporations urgently need to work together to mitigate AI risk
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“Regulations that spur greater accuracy might actually spur greater innovation.”
Our reading: Regulations that spur greater accuracy might actually spur greater innovation.
No horizon
Source: How China might crush the West in the race to AGI if we don’t up our regulatory game
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“As Justice Gorsuch seem to hint recently, Section 230 should not protect platforms from misinformation that their own tools generate.”
Our reading: Section 230 should not shield platforms from liability for misinformation generated by their own AI tools.
No horizon
Source: How China might crush the West in the race to AGI if we don’t up our regulatory game
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“How might we in the West counter all that? In part by carefully choosing the right innovation-encouraging regulations of our own.”
Our reading: The West should counter China partly by choosing innovation-encouraging AI regulations.
No horizon
Source: How China might crush the West in the race to AGI if we don’t up our regulatory game
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“My best candidate? Placing very high standards around truth, with strong penalties for LLM-induced defamation and the wholesale spread of harmful misinformation.”
Our reading: The West should counter China in part by placing very high standards around truth for AI, with strong penalties for LLM-induced defamation and the wholesale spread of harmful misinformation.
No horizon
Qualifier: as his best candidate for innovation-encouraging regulation in the West
Source: How China might crush the West in the race to AGI if we don’t up our regulatory game
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“Neurosymbolic AI might offer a better way of resolving these issues, since it traffics in facts and explicit reasoning, but neurosymbolic AI is out of fashion, and neither well-developed nor strongly supported by the VC world.”
Our reading: Neurosymbolic AI might offer a better way of resolving the truthfulness and alignment issues of current systems, since it traffics in facts and explicit reasoning.
No horizon
Qualifier: since it traffics in facts and explicit reasoning
Source: How China might crush the West in the race to AGI if we don’t up our regulatory game
Assessment: Can’t be checkedSaid
Gary Marcus Recommendation or value judgment
“If getting to the right place requires regulation, rather than just the kindness of corporations with a nominal attachment to “responsible AI”, so be it.”
Our reading: If needed, AI should be regulated rather than left to corporations with only nominal commitment to responsible AI.
No horizon
Qualifier: if getting to the right place requires regulation
Source: How China might crush the West in the race to AGI if we don’t up our regulatory game
Assessment: Can’t be checkedSaid
Gary Marcus Observation
“The AI systems that power these chatbots are simply systems (technically known as “language models” because they emulate (model) the statistical structure of language) that compute probabilities of word sequences, without any deep or human-like comprehension of what they say.”
Our reading: Language models powering chatbots compute word-sequence probabilities without deep or human-like comprehension of what they say.
No horizon
Assessment: Can’t be checkedSaid
Gary Marcus Causal claim
“The more false agency people ascribe to them, the more they can be exploited, suckered in by harmful applications like catfishing and fraud, as well as more subtly harmful applications like chatbot-assisted therapy or flawed financial advice.”
Our reading: The more false agency people ascribe to chatbots, the more they can be exploited via fraud, catfishing, chatbot therapy or flawed financial advice.
No horizon