This is a topic I'm interested in, but the presentation and exposition on the website leaves a lot to be desired. Yes, it does make you sound like a crank.
Almost all of the theory and predictions presented seems to be those of regular classical economics, per Smith, Riccardo, and particularly George. You can find them in Wealth of Nations, Progress and Poverty. This surprises people who have been failed by our education systems. There are still many people writing about this exact topic now - the author does mention e.g Stiglitz.
The author seems to be overcome by the explanatory power of a 150-250 year-old well-established economic theory, of which fable has built a fairly general (novel? improved?) macro model for him, including the effects of certain tax policies. They present this as a new theory of economics rather than a new macro model.
It's very off-putting as a reader - you can't distinguish at a glance between what the author claims to have contributed vs merely discovered by reading about Georgism. Established concepts are not referred to be their usual names, etc.
So, like, legit pro AI tip, at least for 3rd-quarter 2026... whenever you're working on something interesting, ask the AI about prior art, or to do a scan of the scientific literature. Whether it's economics, health, or something algorithmic at work, at least the AIs I've used (as we've not all spent all the time with all the models) are still generally inclined to give you exactly what you ask for. They may do a good job at giving you what you asked for, but they won't generally do a whole lot more. Ask them to go looking around and it's like giving them a 30 point IQ boost sometimes. They all operate way better when you fill the context window with relevant information then when you're operating just in the latent space of their training, but they only rarely seek it out without being prompted on their own.
On my near-term todo list is to explore a particular crank physics theory of my own with AI... but not as a way to validate it, I know it's a crank theory that is far too simple to have been missed by pros in the relevant fields, but as a window into the literature and figure out what's wrong with it and thereby learn something. I will be framing it to the AI in pretty much precisely that way: Go get literature and reputable sources and talk through why this is already well known, probably well known to be a bad and wrong idea.
I still feel like not enough people are talking about this here on HN... AI has opened the scientific literature like never before. It's like being able to interrogate it and interview it as if it was a person, rather than just searching papers, for keywords you don't know, for lines of thought you've never heard of, in a sub-sub-sub-field you didn't even know existed, and failing before you even knew what it is you wanted. I've read more papers in the past 6 months than the past 10 years. Whatever opportunity you have to try this out, be it some question bothering you for the last 10 years, or a crank theory of your own to prove out against the literature, the foundation of some vibe-coded program informed by the literature rather than just vibing on the neural weights directly, or just asking something random about the studied effects of beavers on local ecosystems, you gotta try this. Prompt it specifically for "reputable sources and scientific papers", that helps a lot. It does not make you suddenly an expert in the field, but it does let you poke through the pile of literature far, far more effectively than you could hope to before.
And then don't forget to ask it why your summary is wrong or incomplete. Even if it doesn't convince you, you'll learn yet more.
Yup, I too am surprised this hasn't (at least by my awareness) entered the zeitgeist.
At work I'm putting together an MCP server that more easily exposes our legume data for model consumption, and part of the insane value-add has been the curatorial work that our collaborators at USDA put into the data over years. For example, genome data (i.e. nucleic acid fastas) include relevant metadata such as their DOIs, so models can fetch and read the original papers (if they're open access, of course).
This goes a long way to boosting the intelligence/usefulness of these systems for research.
Yes, exactly. Researchers will not like the fact that I refer to the literature as merely a manual, but “RTFM” applies here. Someone has likely already investigated what you’re looking at, or at least found a way to not do it. And sure it’s in the weights, but if you put papers directly in front of the LLM it’s much more impactful.
> why this is already well known, probably well known to be a bad and wrong idea.
This is still pointing the LLM in a specific direction . You might want to prompt something like “give me a summary of relevant literature” and avoid sharing your point of view. Wdyt?
'classical economics doesn't know how technology affects the wage' - ridiculous, classical economists were addressing exactly how technology was changing society and economic relationships. they didn't have accurate/useful models but they described the relationships in great detail. Sentences like this make me question the author's ability to evaluate their own paper.
Yes, crack open an intro to macroeconomics textbook and it has to discuss total factor productivity (technological progress) in the Cobb-Douglas production function, and its short run and long run effects on wages, or it's quite easy to connect the dots if it doesn't discuss that relationship directly. You'll get medium run too if you go a little beyond classical. It's funny someone claims to be writing economics papers but refuses to spend 100 hours, maybe less, to learn the fundamentals of macroeconomics as understood by everyone working in a related field.
> I simply could not have written this piece. I myself have no formal economics background
No shit, me neither, I read a couple macroeconomics textbooks at the age of 30 and now I wouldn't make arrogant and obviously wrong claims like the above. And I don't have the hubris to publish a paper.
Thank you for being able to point out and articulate these issues. LLMs have a habit of laundering pre-existing concepts per the interests (or input) of any given user.
I feel bad for the humans who rediscover what we have already discovered and position it as something new. If this keeps happening soon we will be in an endless loop without gain.
I also tried to understand what they were saying. I read the website and skimmed the paper. It left me confused and unclear on what the takeaways really are.
It reminds me of the people who reinvent some basic concept of physics with an LLM (usually, but not always, incorrectly) and think it's 'revolutionary'.
Guys you realise you can just read the Journal of Economic Perspectives for free? Its articles are written for the ordinary reader, by experts who have spent big chunks of their lives studying their specialty. They don't try to sound like a teenage girl, they don't boast about being able to do High School algebra, and they contain ideas that are less than one hundred and fifty years old. Some of them might even be new!
RE sovereign wealth funds, You might find it interesting that the Norwegian approach to natural resource management is also based on the classical principles of Ricardo and George:
> And the intuitive idea for this is that the wage is set by technology and access to physically scarce things (land as an example, but tbh you can add other things you think are scarce), and then it’s scaled by how efficiently machines can make machines and how much labor you need to make machines. That’s it.
There is no term for human value here, and it is values that set prices. Scarcity is not itself a value. A particular snowflake or UUID being unique adds no demand. Wages are set in the context of every possible opportunity that the employer can imagine, as ordered by values. So a wage-predicting equation needs arguments that measure all of those value-weighted opportunities against paying a given wage, but this one doesn't. And "That's it" seems to declare them not relevant.
Human values ideally start deeper, in the creation of preferences, where economics simply takes as a primitive/preexisting part of the environment. Marketing theory is the one that focuses on manipulating human value.
Preferences come from selection pressures and needs. Taking them as a foundation leads to excessive focus on trade and obscures the fact that humans in almost all cases need essentially the same things.
My high-school economics teacher taught us Georgism is the optimal form of taxation. He gave us a bunch of dense math to back up that claim, but I can remember none of it.
There is no optimal form of taxation, only trade-offs.
There is shifting burdens from good to good or person to person.
I find it no surprise that so many of the loudest proponents for georgism are highly compensated tech workers with low physical consumption - exactly the demographic that would be favored most under that system.
Georgism makes it possible for the government to profit off the infrastructure it builds, which makes it possible to fund public transportation projects without the tax payer having to pay income tax.
Instead the people who benefit from the infrastructure have the bill for the public transportation system rolled into their land value tax.
Right now in the current system you pay both income taxes and then you pay the landlord again because to him as the monopoly owner of land, the public infrastructure is pure producer surplus.
The demographic that would be favoured under that system is people who work for a living and the people being disadvantaged are the ones sitting on land or extracting the producer surplus.
It would also help incentivize real improved use of expensive property, and less speculative investment without improvement, perhaps leading to lower prices (thus lower land value, and lower taxes), perhaps reaching some kind of equilibrium with better improved land use in expensive areas, less speculation resulting in the expensive areas being less expensive, and more equitable taxation than our current system.
I would expect that land usage favors the very rich, but not nearly as much as income.
Georgism does a excellent job of incentivising better land use, but is trivial to shelter income from.
A teacher renting a run down aprtment might have a similar land tax footprint to a tech ceo in a taller building, or maybe the ceo just teleworks from home in Wyoming.
xAI or whomever puts their next Mega server farm on undesirable land, and then operates basically tax-free.
The end of day problem with the Georgist theory is that we now live in a knowledge and information economy, not an industrial one governed by material inputs. Changing a 1 to a 0 on a string of bits might yeild a billion dollar profit, but requires no material overhead.
Yes? The author is very clear in the blog post about having used AI very heavily:
Up until now you have been reading the words of Anthropic’s Claude, in particular Fable 5. In part, this is because I simply could not have written this piece. ... Although it might seem strange I thought it wrong to impose too much upon the machine, changing its voice to emulate mine. Richard Sutton’s bitter lesson would likely advise as much. Instead it has its unique voice, grating to some perhaps but altogether fitting that it should be able to keep it, and I only gave it advice on what considerations during writing would bridge the gap between its understanding and that of a reader.
I don't know if putting a disclaimer at the very end of the blog, that you also disclaim, should be considered "very clear".
"Here is, for those that have read this far, the acknowledgements that used to be in the formal paper but we decided to remove it, mostly because the paper has been reworked and rewritten so many times by us."
> I never found a piece of text that pangram claims is 100% AI that to me seems like purely human written text.
Is that the level of sensitivity we're looking for? More than literally 0%? Do you know how crazy it'd be to achieve that, even if they were trying to?
It was actual work output I generated a few weeks back with Sonnet 5. Not posting here for obvious reasons, but it was nothing special or engineered for Pangram deception.
Yes, quite a bit actually. It's directly analogous to e.g. "Red sky at night, sailors' delight", i.e. a pseudo-scientific approach that probably has a better-than-random success rate.
Land value tax / citizens dividend here is different to the UBIs sometimes proposed in contemporary US politics. The idea is that you tax and redistribute the profits on the scarce inputs to the economy, rather than the redistributing the outputs like manufactured grids and AI tokens.
You say this, but if the US actually expanded nationwide fiber like we were supposed to there would have been a whole lot of ditches to dig up and refill. Public works projects don’t have to be wasteful.
You may know this already, but we did lay the fiber already like we were supposed to have. Most of it just never got used until ~20 years later. Because corporations need to milk their profits.
About 100 years ago, American capitalists drunk-drove the US economy into a ditch and the government had to jump-start it by allocating capital itself. The jobs were in national parks, schools, housing, and rural electrification. If you've ever been to a national park, chances are decent you walked by/over a plaque or stamp commemorating it.
It's reasonable to want most capital allocation to happen privately, thereby ensuring these decisions are made by people with a track record of success and skin-in-the-game. That's capitalism, it's good, and I'm a capitalist too. But the propaganda that the government is so inherently bad at this game that one should fight it even in an emergency is reductive, defeatist, and ahistorical.
This is a topic I'm interested in, but the presentation and exposition on the website leaves a lot to be desired. Yes, it does make you sound like a crank.
Almost all of the theory and predictions presented seems to be those of regular classical economics, per Smith, Riccardo, and particularly George. You can find them in Wealth of Nations, Progress and Poverty. This surprises people who have been failed by our education systems. There are still many people writing about this exact topic now - the author does mention e.g Stiglitz.
The author seems to be overcome by the explanatory power of a 150-250 year-old well-established economic theory, of which fable has built a fairly general (novel? improved?) macro model for him, including the effects of certain tax policies. They present this as a new theory of economics rather than a new macro model.
It's very off-putting as a reader - you can't distinguish at a glance between what the author claims to have contributed vs merely discovered by reading about Georgism. Established concepts are not referred to be their usual names, etc.
So, like, legit pro AI tip, at least for 3rd-quarter 2026... whenever you're working on something interesting, ask the AI about prior art, or to do a scan of the scientific literature. Whether it's economics, health, or something algorithmic at work, at least the AIs I've used (as we've not all spent all the time with all the models) are still generally inclined to give you exactly what you ask for. They may do a good job at giving you what you asked for, but they won't generally do a whole lot more. Ask them to go looking around and it's like giving them a 30 point IQ boost sometimes. They all operate way better when you fill the context window with relevant information then when you're operating just in the latent space of their training, but they only rarely seek it out without being prompted on their own.
On my near-term todo list is to explore a particular crank physics theory of my own with AI... but not as a way to validate it, I know it's a crank theory that is far too simple to have been missed by pros in the relevant fields, but as a window into the literature and figure out what's wrong with it and thereby learn something. I will be framing it to the AI in pretty much precisely that way: Go get literature and reputable sources and talk through why this is already well known, probably well known to be a bad and wrong idea.
I still feel like not enough people are talking about this here on HN... AI has opened the scientific literature like never before. It's like being able to interrogate it and interview it as if it was a person, rather than just searching papers, for keywords you don't know, for lines of thought you've never heard of, in a sub-sub-sub-field you didn't even know existed, and failing before you even knew what it is you wanted. I've read more papers in the past 6 months than the past 10 years. Whatever opportunity you have to try this out, be it some question bothering you for the last 10 years, or a crank theory of your own to prove out against the literature, the foundation of some vibe-coded program informed by the literature rather than just vibing on the neural weights directly, or just asking something random about the studied effects of beavers on local ecosystems, you gotta try this. Prompt it specifically for "reputable sources and scientific papers", that helps a lot. It does not make you suddenly an expert in the field, but it does let you poke through the pile of literature far, far more effectively than you could hope to before.
And then don't forget to ask it why your summary is wrong or incomplete. Even if it doesn't convince you, you'll learn yet more.
Yup, I too am surprised this hasn't (at least by my awareness) entered the zeitgeist.
At work I'm putting together an MCP server that more easily exposes our legume data for model consumption, and part of the insane value-add has been the curatorial work that our collaborators at USDA put into the data over years. For example, genome data (i.e. nucleic acid fastas) include relevant metadata such as their DOIs, so models can fetch and read the original papers (if they're open access, of course).
This goes a long way to boosting the intelligence/usefulness of these systems for research.
Yeah, you have to do the lateral thinking yourself. But the LLMs can do the work of going into a single-focus rabbit hole quite quickly.
Yes, exactly. Researchers will not like the fact that I refer to the literature as merely a manual, but “RTFM” applies here. Someone has likely already investigated what you’re looking at, or at least found a way to not do it. And sure it’s in the weights, but if you put papers directly in front of the LLM it’s much more impactful.
> why this is already well known, probably well known to be a bad and wrong idea.
This is still pointing the LLM in a specific direction . You might want to prompt something like “give me a summary of relevant literature” and avoid sharing your point of view. Wdyt?
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'classical economics doesn't know how technology affects the wage' - ridiculous, classical economists were addressing exactly how technology was changing society and economic relationships. they didn't have accurate/useful models but they described the relationships in great detail. Sentences like this make me question the author's ability to evaluate their own paper.
Yes, crack open an intro to macroeconomics textbook and it has to discuss total factor productivity (technological progress) in the Cobb-Douglas production function, and its short run and long run effects on wages, or it's quite easy to connect the dots if it doesn't discuss that relationship directly. You'll get medium run too if you go a little beyond classical. It's funny someone claims to be writing economics papers but refuses to spend 100 hours, maybe less, to learn the fundamentals of macroeconomics as understood by everyone working in a related field.
> I simply could not have written this piece. I myself have no formal economics background
No shit, me neither, I read a couple macroeconomics textbooks at the age of 30 and now I wouldn't make arrogant and obviously wrong claims like the above. And I don't have the hubris to publish a paper.
Thank you for being able to point out and articulate these issues. LLMs have a habit of laundering pre-existing concepts per the interests (or input) of any given user.
To be fair, human scientists also frequently launder small modifications to pre-existing work as if it's completely novel.
That's why I don't trust 'em neither!
I feel bad for the humans who rediscover what we have already discovered and position it as something new. If this keeps happening soon we will be in an endless loop without gain.
Ah well.
I also tried to understand what they were saying. I read the website and skimmed the paper. It left me confused and unclear on what the takeaways really are.
It reminds me of the people who reinvent some basic concept of physics with an LLM (usually, but not always, incorrectly) and think it's 'revolutionary'.
Your discomfort may be understated - this phenomena seems to be a slippery slope towards a kind of Dunning-Kruger accidental plagiarism via LLM?
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Guys you realise you can just read the Journal of Economic Perspectives for free? Its articles are written for the ordinary reader, by experts who have spent big chunks of their lives studying their specialty. They don't try to sound like a teenage girl, they don't boast about being able to do High School algebra, and they contain ideas that are less than one hundred and fifty years old. Some of them might even be new!
Sheesh.
As a Georgist I'm naturally very sympathetic to anything in this vein, but as you say: dense!
What do you believe are the most important contributions here over standard Georgism or Ricardo's theory of rents?
RE sovereign wealth funds, You might find it interesting that the Norwegian approach to natural resource management is also based on the classical principles of Ricardo and George:
https://blog.landeconomics.org/p/book-review-the-natural-div...
> And the intuitive idea for this is that the wage is set by technology and access to physically scarce things (land as an example, but tbh you can add other things you think are scarce), and then it’s scaled by how efficiently machines can make machines and how much labor you need to make machines. That’s it.
There is no term for human value here, and it is values that set prices. Scarcity is not itself a value. A particular snowflake or UUID being unique adds no demand. Wages are set in the context of every possible opportunity that the employer can imagine, as ordered by values. So a wage-predicting equation needs arguments that measure all of those value-weighted opportunities against paying a given wage, but this one doesn't. And "That's it" seems to declare them not relevant.
Human values ideally start deeper, in the creation of preferences, where economics simply takes as a primitive/preexisting part of the environment. Marketing theory is the one that focuses on manipulating human value.
Preferences come from selection pressures and needs. Taking them as a foundation leads to excessive focus on trade and obscures the fact that humans in almost all cases need essentially the same things.
My high-school economics teacher taught us Georgism is the optimal form of taxation. He gave us a bunch of dense math to back up that claim, but I can remember none of it.
The optimal form of taxation is none
Coincidentally, that's also the optimal number of libertarians.
Coincidentally, that’s how much you contribute to the discussion
Most libertarians think government institutions and their services are essential for society to function. They aren't anarchists after all.
There is no optimal form of taxation, only trade-offs.
There is shifting burdens from good to good or person to person.
I find it no surprise that so many of the loudest proponents for georgism are highly compensated tech workers with low physical consumption - exactly the demographic that would be favored most under that system.
Georgism makes it possible for the government to profit off the infrastructure it builds, which makes it possible to fund public transportation projects without the tax payer having to pay income tax.
Instead the people who benefit from the infrastructure have the bill for the public transportation system rolled into their land value tax.
Right now in the current system you pay both income taxes and then you pay the landlord again because to him as the monopoly owner of land, the public infrastructure is pure producer surplus.
The demographic that would be favoured under that system is people who work for a living and the people being disadvantaged are the ones sitting on land or extracting the producer surplus.
We tend to own property in places where land is expensive, we'd be paying hefty taxes in a Georgist system.
It would also help incentivize real improved use of expensive property, and less speculative investment without improvement, perhaps leading to lower prices (thus lower land value, and lower taxes), perhaps reaching some kind of equilibrium with better improved land use in expensive areas, less speculation resulting in the expensive areas being less expensive, and more equitable taxation than our current system.
I would expect that land usage favors the very rich, but not nearly as much as income.
Georgism does a excellent job of incentivising better land use, but is trivial to shelter income from.
A teacher renting a run down aprtment might have a similar land tax footprint to a tech ceo in a taller building, or maybe the ceo just teleworks from home in Wyoming.
xAI or whomever puts their next Mega server farm on undesirable land, and then operates basically tax-free.
The end of day problem with the Georgist theory is that we now live in a knowledge and information economy, not an industrial one governed by material inputs. Changing a 1 to a 0 on a string of bits might yeild a billion dollar profit, but requires no material overhead.
https://www.bgnes.com/technology/chatgpt-convinced-canadian-...
the paper abstract is generated by ai: https://www.pangram.com/history/c480c94f-2d19-4cc3-95e0-c4fa...
Yes? The author is very clear in the blog post about having used AI very heavily:
Up until now you have been reading the words of Anthropic’s Claude, in particular Fable 5. In part, this is because I simply could not have written this piece. ... Although it might seem strange I thought it wrong to impose too much upon the machine, changing its voice to emulate mine. Richard Sutton’s bitter lesson would likely advise as much. Instead it has its unique voice, grating to some perhaps but altogether fitting that it should be able to keep it, and I only gave it advice on what considerations during writing would bridge the gap between its understanding and that of a reader.
I don't know if putting a disclaimer at the very end of the blog, that you also disclaim, should be considered "very clear".
"Here is, for those that have read this far, the acknowledgements that used to be in the formal paper but we decided to remove it, mostly because the paper has been reworked and rewritten so many times by us."
It may well be, but also Pangram is ridiculously transparent pseudoscience. Let's not play pretend that it's authoritative, please.
Edit: Just for fun I just defeated it with AI-generated text that it reported as 100% human-written. Great stuff. Truly genius scam.
I never found a piece of text that pangram claims is 100% AI that to me seems like purely human written text.
The only counter example is when a human composed a piece deliberately trying to mimic AI slop.
So call it an AI slop detector if you want, but either way it accurately identifies stuff I don't wan't to read.
> I never found a piece of text that pangram claims is 100% AI that to me seems like purely human written text.
Is that the level of sensitivity we're looking for? More than literally 0%? Do you know how crazy it'd be to achieve that, even if they were trying to?
What were the text, your prompt, and model?
It was actual work output I generated a few weeks back with Sonnet 5. Not posting here for obvious reasons, but it was nothing special or engineered for Pangram deception.
The real reason being that it doesn't exist?
Pangram 4?
It is not pseudoscience. Have you read about how it works?
Yes, quite a bit actually. It's directly analogous to e.g. "Red sky at night, sailors' delight", i.e. a pseudo-scientific approach that probably has a better-than-random success rate.
So it’s a heuristic. Lots of very valuable heuristics exist.
None of which is authoritative, per my initial comment.
And I'd agree if that's what GP said.
What name do you use for an approach that probably gets a better than random success rate (without guaranteeing that)?
I’m leaving out the ‘pseudo-scientific’ part of GP’s description, since it doesn’t entail anything technically.
Are there other alternatives to UBI in solving this problem?
Land value tax / citizens dividend here is different to the UBIs sometimes proposed in contemporary US politics. The idea is that you tax and redistribute the profits on the scarce inputs to the economy, rather than the redistributing the outputs like manufactured grids and AI tokens.
UBI is not a solution because it will drive up land rents and be eaten by landowners.
MMT job guarantee
Boy I sure love my ditch digging job for the government! My friend also loves his ditch filling job too!
You say this, but if the US actually expanded nationwide fiber like we were supposed to there would have been a whole lot of ditches to dig up and refill. Public works projects don’t have to be wasteful.
You may know this already, but we did lay the fiber already like we were supposed to have. Most of it just never got used until ~20 years later. Because corporations need to milk their profits.
About 100 years ago, American capitalists drunk-drove the US economy into a ditch and the government had to jump-start it by allocating capital itself. The jobs were in national parks, schools, housing, and rural electrification. If you've ever been to a national park, chances are decent you walked by/over a plaque or stamp commemorating it.
It's reasonable to want most capital allocation to happen privately, thereby ensuring these decisions are made by people with a track record of success and skin-in-the-game. That's capitalism, it's good, and I'm a capitalist too. But the propaganda that the government is so inherently bad at this game that one should fight it even in an emergency is reductive, defeatist, and ahistorical.
I think the answer to the last question is obvious. That we are standing on the shoulders or something completely new.
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It's a liiiiiiittle more than that...