India has the problem with farming that the US is starting to have with AI. Farming in India is still far too labor intensive by world standards. 43% of workers still work in agriculture. [1] For the US, that number is under 2%. China is at 22% as of 2023, and dropping steadily. This inefficient agricultural system is not by accident. It is supported by heavy subsidies. Attempts to cut the subsidies resulted in riots.[2] Trouble is ongoing. Comments from someone who knows more about this than I do would help here. The US and most of the EU went through that transition over several generations, and farming is still heavily subsidized in both areas. The transition happened faster in China, and a hukou system was put into place to prevent people from migrating from farms to cities faster than the cities could absorb them. Looking at how countries coped with a fast transition from labor intensive agriculture to an urban society gives hints on how an AI transition may look. All the Asian countries that went from poor to rich in a generation did this, with different approaches. How that took place may provide more useful info than philosophy. [1] https://economictimes.indiatimes.com/news/economy/indicators... [2] https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farme...
痛点分析发布于 2026/05/29
痛点为 AI 基于上游原始证据的初步提炼；未包含额外中国市场检索。
痛点
用户讨论的核心痛点是宏观层面的劳动力替代与需求萎缩循环。在Hacker News的评论中，用户指出当多个行业同时用AI替代人力时，被裁员的工人失去收入，导致整体消费需求下降，进而使企业收入停滞，形成“裁员→需求萎缩→进一步裁员”的恶性循环。这种系统性风险使得企业面临决策困境：追求短期效率提升可能破坏自身市场基础，而维持人力又面临竞争压力。用户担忧这种循环最终可能导致经济崩溃或极端解决方案（如完全非人类经济），但缺乏具体行业或工作流的直接证据，更多是理论推演和未来担忧。
External Article
External article summary
We can laugh at them but we have to take this seriously
External Article
External article source
- Article title
- The Dead Economy Theory
- Host
- www.owenmcgrann.com
§ Dossier
Selected HN comments
Animats
I know this isn't exactly related, so maybe a low value comment, but it itches in my mind. Years ago I talked with a recruiter at Facebook and they bragged about how many floors of developers they had working on Messenger in just one location (Seattle). What on earth do you do with that many devs on a project like Messenger? I mean, really? I feel like in a way, AI just adds to that weird situation of overcapacity. Maybe we were already oversupplied with talent. In which case why the heck were we still hiring more, more, more developers? Before the AI craze, Musk chopped an awful lot of headcount at Twitter, right, and proved it was overkill, has that panned out? I just struggle to imagine how the economics of SWE really work in reality, outside of the niche that I am in. I have never worked for a pure software company on products that ship directly to outside customers, I've always been an internal developer. Maybe that is why I have such a big blindspot. I won't be surprised if the net result of this wave of LLMs is ... not much. A change in tooling, but otherwise not revolutionary. On paper it should be revolutionary, but the more I use it (for both coding and non-coding tasks) the more I think it isn't anywhere near magic enough for that. It does have its moments though.
rootusrootus
There is certainly a huge problem with displacing labour in multiple industries at the same time, but the economic story told here in "three turns" is different. When productivity rises costs drop, but because of competition, almost the entire gain has to translate not to increased margins but to reduced prices. Paul Krugman recently used this to explain the large disparity between growth in GDP as normally measured in fixed prices (i.e. inflation-adjusted to consumer prices in some fixed year) and growth in GDP as measured in PPP, i.e. when adjusted to consumer prices in every year. If making computers, say, becomes much more productive, the growth in productivity in, say, 1980 prices, seems very large, but in PPP is not only smaller, but the beneficiaries aren't computer manufacturers but anyone who uses computers. Of course, lower prices don't solve your problems if you're unemployed. Demand, indeed, drops if many people are unemployed, which pushes prices further down, but this time in a way that leads to a recession.
pron
> Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers. Revenue growth stalls. The AI subscription that was supposed to be an investment in efficiency turns out to be a contribution to the destruction of its own market. If we take it to the extreme, the final solution to this problem is secessionism: a fully non-human AI economy where the customers and providers are both robots. Why fund public education or research or healthcare? Just build more data centers. A billion dollars and a bunker in the Southern Hemisphere will not save anyone. Capital is not a moat in this hypothetical non-humane world. Whence do you derive your authority? How can you trust your body guard? You and what army? An army of robots/drones? What if they get hacked? What if the AI researchers get alignment right and Claude refuses your request? It's all so obscene. Instead, why don't we try to protect human dignity and move towards a more humane future?
wcfrobert
I think when these companies IPO later this year, we’re going to see the reality of the PNL numbers and whether they are sustainable etc as all the financials will become public. Rumor mill suggests that Anthropic might be profitable (but at what magnitude), OpenAI is not profitable, Google is mostly vertically integrated and has a low cost structure as they are have pre-existing data center buildouts, their own silicon and experience that suggests they will be able to operate at a very low cost, but they still have to justify their spend. I think having to report numbers publically on a quarterly basis will bring the whole thing into reality.
daft_pink
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"excerpt": "You’re probably familiar with the dead internet theory: most of what you encounter online is now generated by bots, for bots, with humans reduced to a shrinking audience for machine-generated noise. Last year, over half of new content on the internet was AI-generated. The humans are still there, scrolling, but the thing they’re scrolling through has become a performance staged by machines for an audience that hasn’t yet realized the show isn’t for them.\n\nIt’s utterly desiccating to log onto spaces seeking a live mind to joust and think with, and find a relentless stream of slop. Promised an age of superconnectivity, we’ve let our shared physical spaces wither, only to find our promised digital commons to be one large billboard increasingly read and created by bots.\n\nThat’s bad enough. I want to talk about something worse. Call it the dead economy theory.\n\nA word of welcome to the folks who have arrived here from Hacker News and various other places. Two quick comments, given that I’ve received many messages and have seen many comments on HN on this. First, the text of this piece is entirely human-generated, including the infelicitous phrasings and penchant for two-dollar words. The",
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"text": "India has the problem with farming that the US is starting to have with AI. Farming in India is still far too labor intensive by world standards. 43% of workers still work in agriculture. [1] For the US, that number is under 2%. China is at 22% as of 2023, and dropping steadily.<p>This inefficient agricultural system is not by accident. It is supported by heavy subsidies. Attempts to cut the subsidies resulted in riots.[2] Trouble is ongoing.\nComments from someone who knows more about this than I do would help here.<p>The US and most of the EU went through that transition over several generations, and farming is still heavily subsidized in both areas. The transition happened faster in China, and a hukou system was put into place to prevent people from migrating from farms to cities faster than the cities could absorb them.<p>Looking at how countries coped with a fast transition from labor intensive agriculture to an urban society gives hints on how an AI transition may look. All the Asian countries that went from poor to rich in a generation did this, with different approaches. How that took place may provide more useful info than philosophy.<p>[1] <a href=\"https://economictimes.indiatimes.com/news/economy/indicators/india-labour-market-remodels-itself-bit-by-bit-as-agri-slowly-cedes-ground-workforce-moves-on/articleshow/130949727.cms\" rel=\"nofollow\">https://economictimes.indiatimes.com/news/economy/indicators...</a><p>[2] <a href=\"https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farmers%27_protest\" rel=\"nofollow\">https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farme...</a>",
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"body": "India has the problem with farming that the US is starting to have with AI. Farming in India is still far too labor intensive by world standards. 43% of workers still work in agriculture. [1] For the US, that number is under 2%. China is at 22% as of 2023, and dropping steadily. This inefficient agricultural system is not by accident. It is supported by heavy subsidies. Attempts to cut the subsidies resulted in riots.[2] Trouble is ongoing. Comments from someone who knows more about this than I do would help here. The US and most of the EU went through that transition over several generations, and farming is still heavily subsidized in both areas. The transition happened faster in China, and a hukou system was put into place to prevent people from migrating from farms to cities faster than the cities could absorb them. Looking at how countries coped with a fast transition from labor intensive agriculture to an urban society gives hints on how an AI transition may look. All the Asian countries that went from poor to rich in a generation did this, with different approaches. How that took place may provide more useful info than philosophy. [1] https://economictimes.indiatimes.com/news/economy/indicators... [2] https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farme...",
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"raw_body": "India has the problem with farming that the US is starting to have with AI. Farming in India is still far too labor intensive by world standards. 43% of workers still work in agriculture. [1] For the US, that number is under 2%. China is at 22% as of 2023, and dropping steadily.<p>This inefficient agricultural system is not by accident. It is supported by heavy subsidies. Attempts to cut the subsidies resulted in riots.[2] Trouble is ongoing.\nComments from someone who knows more about this than I do would help here.<p>The US and most of the EU went through that transition over several generations, and farming is still heavily subsidized in both areas. The transition happened faster in China, and a hukou system was put into place to prevent people from migrating from farms to cities faster than the cities could absorb them.<p>Looking at how countries coped with a fast transition from labor intensive agriculture to an urban society gives hints on how an AI transition may look. All the Asian countries that went from poor to rich in a generation did this, with different approaches. How that took place may provide more useful info than philosophy.<p>[1] <a href=\"https://economictimes.indiatimes.com/news/economy/indicators/india-labour-market-remodels-itself-bit-by-bit-as-agri-slowly-cedes-ground-workforce-moves-on/articleshow/130949727.cms\" rel=\"nofollow\">https://economictimes.indiatimes.com/news/economy/indicators...</a><p>[2] <a href=\"https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farmers%27_protest\" rel=\"nofollow\">https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farme...</a>",
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"text": "I know this isn't exactly related, so maybe a low value comment, but it itches in my mind. Years ago I talked with a recruiter at Facebook and they bragged about how many floors of developers they had working on Messenger in just one location (Seattle).<p>What on earth do you do with that many devs on a project like Messenger? I mean, really?<p>I feel like in a way, AI just adds to that weird situation of overcapacity. Maybe we were already oversupplied with talent. In which case why the heck were we still hiring more, more, more developers? Before the AI craze, Musk chopped an awful lot of headcount at Twitter, right, and proved it was overkill, has that panned out?<p>I just struggle to imagine how the economics of SWE really work in reality, outside of the niche that I am in. I have never worked for a pure software company on products that ship directly to outside customers, I've always been an internal developer. Maybe that is why I have such a big blindspot.<p>I won't be surprised if the net result of this wave of LLMs is ... not much. A change in tooling, but otherwise not revolutionary. On paper it <i>should</i> be revolutionary, but the more I use it (for both coding and non-coding tasks) the more I think it isn't anywhere near magic enough for that. It does have its moments though.",
"time": 1780079047,
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"body": "I know this isn't exactly related, so maybe a low value comment, but it itches in my mind. Years ago I talked with a recruiter at Facebook and they bragged about how many floors of developers they had working on Messenger in just one location (Seattle). What on earth do you do with that many devs on a project like Messenger? I mean, really? I feel like in a way, AI just adds to that weird situation of overcapacity. Maybe we were already oversupplied with talent. In which case why the heck were we still hiring more, more, more developers? Before the AI craze, Musk chopped an awful lot of headcount at Twitter, right, and proved it was overkill, has that panned out? I just struggle to imagine how the economics of SWE really work in reality, outside of the niche that I am in. I have never worked for a pure software company on products that ship directly to outside customers, I've always been an internal developer. Maybe that is why I have such a big blindspot. I won't be surprised if the net result of this wave of LLMs is ... not much. A change in tooling, but otherwise not revolutionary. On paper it should be revolutionary, but the more I use it (for both coding and non-coding tasks) the more I think it isn't anywhere near magic enough for that. It does have its moments though.",
"is_op": false,
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"raw_body": "I know this isn't exactly related, so maybe a low value comment, but it itches in my mind. Years ago I talked with a recruiter at Facebook and they bragged about how many floors of developers they had working on Messenger in just one location (Seattle).<p>What on earth do you do with that many devs on a project like Messenger? I mean, really?<p>I feel like in a way, AI just adds to that weird situation of overcapacity. Maybe we were already oversupplied with talent. In which case why the heck were we still hiring more, more, more developers? Before the AI craze, Musk chopped an awful lot of headcount at Twitter, right, and proved it was overkill, has that panned out?<p>I just struggle to imagine how the economics of SWE really work in reality, outside of the niche that I am in. I have never worked for a pure software company on products that ship directly to outside customers, I've always been an internal developer. Maybe that is why I have such a big blindspot.<p>I won't be surprised if the net result of this wave of LLMs is ... not much. A change in tooling, but otherwise not revolutionary. On paper it <i>should</i> be revolutionary, but the more I use it (for both coding and non-coding tasks) the more I think it isn't anywhere near magic enough for that. It does have its moments though.",
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"text": "There is certainly a huge problem with displacing labour in multiple industries at the same time, but the economic story told here in "three turns" is different. When productivity rises costs drop, but because of competition, almost the entire gain has to translate not to increased margins but to reduced prices. Paul Krugman recently used this to explain the large disparity between growth in GDP as normally measured in fixed prices (i.e. inflation-adjusted to consumer prices in some fixed year) and growth in GDP as measured in PPP, i.e. when adjusted to consumer prices in every year. If making computers, say, becomes much more productive, the growth in productivity in, say, 1980 prices, seems very large, but in PPP is not only smaller, but the beneficiaries aren't computer manufacturers but anyone who uses computers.<p>Of course, lower prices don't solve your problems if you're unemployed. Demand, indeed, drops if many people are unemployed, which pushes prices further down, but this time in a way that leads to a recession.",
"time": 1780091978,
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"body": "There is certainly a huge problem with displacing labour in multiple industries at the same time, but the economic story told here in \"three turns\" is different. When productivity rises costs drop, but because of competition, almost the entire gain has to translate not to increased margins but to reduced prices. Paul Krugman recently used this to explain the large disparity between growth in GDP as normally measured in fixed prices (i.e. inflation-adjusted to consumer prices in some fixed year) and growth in GDP as measured in PPP, i.e. when adjusted to consumer prices in every year. If making computers, say, becomes much more productive, the growth in productivity in, say, 1980 prices, seems very large, but in PPP is not only smaller, but the beneficiaries aren't computer manufacturers but anyone who uses computers. Of course, lower prices don't solve your problems if you're unemployed. Demand, indeed, drops if many people are unemployed, which pushes prices further down, but this time in a way that leads to a recession.",
"is_op": false,
"author": "pron",
"raw_body": "There is certainly a huge problem with displacing labour in multiple industries at the same time, but the economic story told here in "three turns" is different. When productivity rises costs drop, but because of competition, almost the entire gain has to translate not to increased margins but to reduced prices. Paul Krugman recently used this to explain the large disparity between growth in GDP as normally measured in fixed prices (i.e. inflation-adjusted to consumer prices in some fixed year) and growth in GDP as measured in PPP, i.e. when adjusted to consumer prices in every year. If making computers, say, becomes much more productive, the growth in productivity in, say, 1980 prices, seems very large, but in PPP is not only smaller, but the beneficiaries aren't computer manufacturers but anyone who uses computers.<p>Of course, lower prices don't solve your problems if you're unemployed. Demand, indeed, drops if many people are unemployed, which pushes prices further down, but this time in a way that leads to a recession.",
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"text": "> Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers. Revenue growth stalls. The AI subscription that was supposed to be an investment in efficiency turns out to be a contribution to the destruction of its own market.<p>If we take it to the extreme, the final solution to this problem is secessionism: a fully non-human AI economy where the customers and providers are both robots. Why fund public education or research or healthcare? Just build more data centers. A billion dollars and a bunker in the Southern Hemisphere will not save anyone. Capital is not a moat in this hypothetical non-humane world. Whence do you derive your authority? How can you trust your body guard? You and what army? An army of robots/drones? What if they get hacked? What if the AI researchers get alignment right and Claude refuses your request?<p>It's all so obscene. Instead, why don't we try to protect human dignity and move towards a more humane future?",
"time": 1780081115,
"type": "comment",
"parent": 48324712
},
"body": "> Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers. Revenue growth stalls. The AI subscription that was supposed to be an investment in efficiency turns out to be a contribution to the destruction of its own market. If we take it to the extreme, the final solution to this problem is secessionism: a fully non-human AI economy where the customers and providers are both robots. Why fund public education or research or healthcare? Just build more data centers. A billion dollars and a bunker in the Southern Hemisphere will not save anyone. Capital is not a moat in this hypothetical non-humane world. Whence do you derive your authority? How can you trust your body guard? You and what army? An army of robots/drones? What if they get hacked? What if the AI researchers get alignment right and Claude refuses your request? It's all so obscene. Instead, why don't we try to protect human dignity and move towards a more humane future?",
"is_op": false,
"author": "wcfrobert",
"raw_body": "> Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers. Revenue growth stalls. The AI subscription that was supposed to be an investment in efficiency turns out to be a contribution to the destruction of its own market.<p>If we take it to the extreme, the final solution to this problem is secessionism: a fully non-human AI economy where the customers and providers are both robots. Why fund public education or research or healthcare? Just build more data centers. A billion dollars and a bunker in the Southern Hemisphere will not save anyone. Capital is not a moat in this hypothetical non-humane world. Whence do you derive your authority? How can you trust your body guard? You and what army? An army of robots/drones? What if they get hacked? What if the AI researchers get alignment right and Claude refuses your request?<p>It's all so obscene. Instead, why don't we try to protect human dignity and move towards a more humane future?",
"created_at": 1780081115,
"reply_count": 5
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"text": "I think when these companies IPO later this year, we’re going to see the reality of the PNL numbers and whether they are sustainable etc as all the financials will become public.<p>Rumor mill suggests that Anthropic might be profitable (but at what magnitude), OpenAI is not profitable, Google is mostly vertically integrated and has a low cost structure as they are have pre-existing data center buildouts, their own silicon and experience that suggests they will be able to operate at a very low cost, but they still have to justify their spend.<p>I think having to report numbers publically on a quarterly basis will bring the whole thing into reality.",
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"body": "I think when these companies IPO later this year, we’re going to see the reality of the PNL numbers and whether they are sustainable etc as all the financials will become public. Rumor mill suggests that Anthropic might be profitable (but at what magnitude), OpenAI is not profitable, Google is mostly vertically integrated and has a low cost structure as they are have pre-existing data center buildouts, their own silicon and experience that suggests they will be able to operate at a very low cost, but they still have to justify their spend. I think having to report numbers publically on a quarterly basis will bring the whole thing into reality.",
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"raw_body": "I think when these companies IPO later this year, we’re going to see the reality of the PNL numbers and whether they are sustainable etc as all the financials will become public.<p>Rumor mill suggests that Anthropic might be profitable (but at what magnitude), OpenAI is not profitable, Google is mostly vertically integrated and has a low cost structure as they are have pre-existing data center buildouts, their own silicon and experience that suggests they will be able to operate at a very low cost, but they still have to justify their spend.<p>I think having to report numbers publically on a quarterly basis will bring the whole thing into reality.",
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"text": "India has the problem with farming that the US is starting to have with AI. Farming in India is still far too labor intensive by world standards. 43% of workers still work in agriculture. [1] For the US, that number is under 2%. China is at 22% as of 2023, and dropping steadily.<p>This inefficient agricultural system is not by accident. It is supported by heavy subsidies. Attempts to cut the subsidies resulted in riots.[2] Trouble is ongoing.\nComments from someone who knows more about this than I do would help here.<p>The US and most of the EU went through that transition over several generations, and farming is still heavily subsidized in both areas. The transition happened faster in China, and a hukou system was put into place to prevent people from migrating from farms to cities faster than the cities could absorb them.<p>Looking at how countries coped with a fast transition from labor intensive agriculture to an urban society gives hints on how an AI transition may look. All the Asian countries that went from poor to rich in a generation did this, with different approaches. How that took place may provide more useful info than philosophy.<p>[1] <a href=\"https://economictimes.indiatimes.com/news/economy/indicators/india-labour-market-remodels-itself-bit-by-bit-as-agri-slowly-cedes-ground-workforce-moves-on/articleshow/130949727.cms\" rel=\"nofollow\">https://economictimes.indiatimes.com/news/economy/indicators...</a><p>[2] <a href=\"https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farmers%27_protest\" rel=\"nofollow\">https://en.wikipedia.org/wiki/2024%E2%80%942025_Indian_farme...</a>",
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"text": "I know this isn't exactly related, so maybe a low value comment, but it itches in my mind. Years ago I talked with a recruiter at Facebook and they bragged about how many floors of developers they had working on Messenger in just one location (Seattle).<p>What on earth do you do with that many devs on a project like Messenger? I mean, really?<p>I feel like in a way, AI just adds to that weird situation of overcapacity. Maybe we were already oversupplied with talent. In which case why the heck were we still hiring more, more, more developers? Before the AI craze, Musk chopped an awful lot of headcount at Twitter, right, and proved it was overkill, has that panned out?<p>I just struggle to imagine how the economics of SWE really work in reality, outside of the niche that I am in. I have never worked for a pure software company on products that ship directly to outside customers, I've always been an internal developer. Maybe that is why I have such a big blindspot.<p>I won't be surprised if the net result of this wave of LLMs is ... not much. A change in tooling, but otherwise not revolutionary. On paper it <i>should</i> be revolutionary, but the more I use it (for both coding and non-coding tasks) the more I think it isn't anywhere near magic enough for that. It does have its moments though.",
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"text": "There is certainly a huge problem with displacing labour in multiple industries at the same time, but the economic story told here in "three turns" is different. When productivity rises costs drop, but because of competition, almost the entire gain has to translate not to increased margins but to reduced prices. Paul Krugman recently used this to explain the large disparity between growth in GDP as normally measured in fixed prices (i.e. inflation-adjusted to consumer prices in some fixed year) and growth in GDP as measured in PPP, i.e. when adjusted to consumer prices in every year. If making computers, say, becomes much more productive, the growth in productivity in, say, 1980 prices, seems very large, but in PPP is not only smaller, but the beneficiaries aren't computer manufacturers but anyone who uses computers.<p>Of course, lower prices don't solve your problems if you're unemployed. Demand, indeed, drops if many people are unemployed, which pushes prices further down, but this time in a way that leads to a recession.",
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"text": "> Turn three: the company that fired its workers to save money discovers that its customers were, in aggregate, other companies’ workers. Revenue growth stalls. The AI subscription that was supposed to be an investment in efficiency turns out to be a contribution to the destruction of its own market.<p>If we take it to the extreme, the final solution to this problem is secessionism: a fully non-human AI economy where the customers and providers are both robots. Why fund public education or research or healthcare? Just build more data centers. A billion dollars and a bunker in the Southern Hemisphere will not save anyone. Capital is not a moat in this hypothetical non-humane world. Whence do you derive your authority? How can you trust your body guard? You and what army? An army of robots/drones? What if they get hacked? What if the AI researchers get alignment right and Claude refuses your request?<p>It's all so obscene. Instead, why don't we try to protect human dignity and move towards a more humane future?",
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"text": "I think when these companies IPO later this year, we’re going to see the reality of the PNL numbers and whether they are sustainable etc as all the financials will become public.<p>Rumor mill suggests that Anthropic might be profitable (but at what magnitude), OpenAI is not profitable, Google is mostly vertically integrated and has a low cost structure as they are have pre-existing data center buildouts, their own silicon and experience that suggests they will be able to operate at a very low cost, but they still have to justify their spend.<p>I think having to report numbers publically on a quarterly basis will bring the whole thing into reality.",
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