We Don't Need the World, We Only Need Money

The idea that modifying or replacing currency will solve problems of corrupted values, perverse incentives, destabilizing asymmetries of wealth and power and the civilizational psychosis of "growth of consumption and profits at any cost" is illusory.

An old friend summarized the mindset of much of the developed world wryly and succinctly: "We don't need the world, we only need money." In other words, we don't actually need real-world sources of life's essentials that are within our control or a functional biosphere because since we can buy everything we could possibly want or need with money. So, money is all we need.

We don't care where the stuff we want/need comes from because it will always come from somewhere and be available in whatever quantity and quality we desire, as somebody somewhere will keep our stores and fuel tanks fully stocked and our electrical grid powered 24/7.

This disconnect between the complex mechanics of real-world manufacturing, processing and transport--a world of physical materials reconfigured by productive work--is understandable in a consumer economy of transactions of money where all the work, all the materials and all the consequences are invisible to the consumer plugging in an appliance, fueling their car and buying an item off the shelf.

An economy that favors assets and financial speculation as the means to acquiring wealth is also disconnected from the role of productive work in this invisible world of production and supply chains.

These disconnects from the real world and productive work have created a make-believe mindset in which doing something with money is all we need to do to get rich and preserve our wealth. I call this make-believe world civilizational psychosis, a mindset detached from reality for it mischaracterizes the relationships of the material world, productive work and currency / money.

This make-believe world in which money is all that matters is not a sustainable society or economy.

In this make-believe world, shape-shifting money is the solution to all problems. Common sense and history both support the conclusion that a financial system that must borrow from the future and pay interest on that rising debt to fund the present is not sustainable and will be replaced with some other arrangement one way or another.

All the solutions being bandied about are money-based: stablecoins, gold-backed currencies, etc. The idea behind all of these proposals is that changing money will fix whatever's broken in a system that has lost touch with its material foundations and productive work.

This mindset explains the conventional conviction that all one has to do to live extremely well is navigate the coming collapse of the current money system (i.e. fiat currencies and credit) and emerge from the other side of the wormhole with wealth intact in some other form.

This mindset makes three implicit assumptions:

1. The real world will continue functioning perfectly despite the collapse of the current money system, ensuring fuel tanks are full, the electricity is on 24/7 and all the retail shelves are full of all the good things.

2. The majority who did not successfully navigate the collapse of the current money system and are now impoverished will passively accept their serfdom to the New Nobility who successfully emerged with wealth intact--or greatly increased (see #3).

3. Since the new form of money will be scarce--and this is the source of its value as a replacement currency--those who own it will accrue virtually all the "value" embedded in "money:" all those who held the old currency that's now worthless will have zero "money:" those who own the new form of money will own all the scarcity value of the new currency.

If history is any guide, the distribution of those who manage to convert all their "old" wealth into "new" wealth is highly asymmetric, as the vast majority lack the means to manage the conversion on a scale where the resulting wealth is consequential. In other words, the rich tend to manage the conversion and everyone else doesn't. So the rich get richer and everyone else is wiped out.

This has a corollary: since those who manage the conversion will emerge on the other side of the wormhole with wealth, "money" is no longer bound to work/labor: the wealthy have no need to generate value via work, they merely provide demand via spending their wealth.

None of these assumptions strike me as realistic, practical or desirable.

Let's examine what happens to supply chains when fiat currencies (the current form of money) crash in purchasing power (i.e. hyper-inflation or loss of trust in the currency) and the replacement currency is a gold-backed currency.

Those favoring gold-or-commodity backed currencies tend to forget that scale is a primary characteristic of "money" used in global transactions. If the gold-backed currency (or cryptocurrency) in circulation can only fund 10% of the current global volume of currency transactions--around $9 to $10 trillion dollars a day--and 90% of the new currency is locked in domestic accounts and unavailable for global transactions--then this new currency can only grease 1% of the current demand for global currency trading.

The global supply chain system crashes because there is not enough currency outside the issuing entity to grease the immense daily trade in currency for trade, debt, speculation, hedging, etc.

The whole point of a currency backed by a limited commodity is that it can't expand 10-fold overnight because that would reduce the purchasing power of the currency by the same factor.

In other words, a replacement currency must provide the same scale of not only currency in circulation but the same scale of liquidity available for global settlements of trade, debt, speculation and hedging--currently trillions of dollars per day. Anything less and the entire global trade / credit network freezes up.

Consider what happens to enterprises in supply chains who continued accepting now-worthless "old" currency. They're now bankrupt, so whatever chains they were links in are now broken. Those enterprises that prudently held off accepting any orders until the situation settled down have nothing in the pipeline, so whatever chains they were part of are also broken.

Those who decide to only accept some scarce monetary substitute are sitting on their hands, as they've been outbid by more desperate dealers / traders.

In summary, if the current "money" dissolves, global supply chains immediately dissolve, too, and expecting a relatively limited volume of replacement currency with a tiny float to ramp up 10-fold while retaining its scarcity value is delusional, as the entire point of scarcity value as the basis of a currency is destroyed if the issuance jumps up 10-fold to handle global trade needs while the quantity of the underlying commodity remains unchanged.

The real world breaks down immediately, and nobody will restock the shelves that are now bare, or refill the fuel tanks that are now empty, or restart the grid.

As for #2, the impoverished and those hanging onto "middle class status" by a thread had hope in the old system because the shelves were still full. Now that the old money has dissolved and the shelves are empty, they're not just impoverished, they have lost hope and are now angry. They are unlikely to view those who emerge from the wormhole wealthy favorably. They will likely view this as the penultimate form of unfairness and inequality and take action they reckon is appropriate, rebalancing the inequality by expropriation.

Telling them that they will now be able to turn their labor into real wealth down the road as serfs in a neofeudal arrangement is unlikely to persuade them that the New Nobility deserves its wealth and dominance.

As for the connection between the material world, productive work and money, there is no sustainable economy or society possible until these bonds are restored. The road to wealth must run through being productive in the material world rather than speculation. This has been lost in the current speculative mania and the associated civilizational psychosis that we "don't need the world, only need money" and the best way to acquire that money is speculating in assets and money. (I discuss the connections of money and work in my book Money and Work Unchained.)

In summary: the idea that modifying or replacing currency / money will solve problems of corrupted values, perverse incentives, destabilizing asymmetries of wealth and power and the civilizational psychosis of "growth of consumption and profits at any cost" is illusory. We would be wise to ponder changing far more about how we live than our monetary system, which is a manifestation of corrupted values, perverse incentives, destabilizing asymmetries and civilizational psychosis rather than their source.

Reorganizing the monetary system to serve a sustainable social order is certainly part of the overall set of solutions, but that alone is not enough to fix what's broken at deeper levels than what we use as money.

Charts of interest: wealth of the top 0.1%:



Percentage of financial assets held by the top 1%--up 42% since 1990: financial assets held by the bottom 50%, down 28%.



Labor's share of the economy: all-time lows:



Non-bank assets: hyper-financialization:



TCMDO: total credit:




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AI's Insurmountable Flaw: "Mass Regurgitation of Misinformation"

These immense hidden costs will not show up in GDP until they collapse the entire house of speculative gambling cards propping up the global economy.

I approach all AI topics with several things in mind. One is the nature of problems, which implicitly define what qualifies as solutions, and the resulting incentive to define the "problem" such that the "solution" happens to be the one we own and control.

So the "problem" AI solves is "corporate profits are too low," and so the "solution" is to replace costly human labor (made costlier by SickCare insurance and taxes on labor) with "cheaper" AI (cheaper because the full costs are hidden or subsidized).

My other lens: the economic, social and cultural consequences of AI as it is and AI hype, a topic I've explored most recently in Is AI Reversing Anti-Progress or Is It Accelerating It?, AI Data Centers Are Not the Railroads of Today and Inequality, AI and Digital Life Are Undermining Society.

Correspondent Mike Fasano recently submitted a succinct and telling summary of AI's insurmountable structural flaw: AI's inability to discern the difference between truth and falsehood, be it intentional misdirection / misinformation or errors generated by AI hallucinations, a systemic flaw which he summarized as mass regurgitation of misinformation:

*           *           *

"I read you post on AI and railroads. Here is another observation.

So far, AI has only regurgitative intelligence. It--at best--can collate and respond to queries on masses of acquired data.

But what if that data is wrong?

Who now believes the inflation or unemployment statistics? Virtually every human knows that those statistics are false.

Does AI know that?

And the problem goes much deeper.

The former editor of the New England Journal of Medicine, Marcia Angell, noted:

'It is simply no longer possible to believe much of the clinical research that is published, or to rely on the judgment of trusted physicians or authoritative medical guidelines. I take no pleasure in this conclusion, which I reached slowly and reluctantly over my two decades as an editor of the New England Journal of Medicine.'

That being the case, can we rely up AI medical advice?

And that problem goes beyond medicine. It is now generally conceded that the inability to replicate scientific studies of any type has give rise to a 'replicability crisis' in science. Can we trust 'science' that cannot be proven to be accurate?

Any adult past the age of 40 knows that the above listing of questionable information sources is just the tip of the iceberg. We live in a sea of 'official' but false data.

Railroads could transport grain to cities, minerals to factories, manufactured goods to those needing those goods. That served a public purpose.

But what is the use of the mass regurgitation of misinformation? And is anyone subtracting the losses engendered by the utilization of inaccurate information from GDP?"

*           *           *

Thank you, Mike, for clarifying an essential point: the foundation of all "value" is fact, truth, accuracy and the transparency, replicability and accountability of the processes validating fact, truth, accuracy. If AI is incapable by its nature of validating all these, it's worse than useless--it's destructive on a system-wide scale.

The evidence of the systemic destruction is already overwhelming. Bogus "scientific papers" are already proliferating at an accelerating rate, making the task of identifying incorrect and fabricated (i.e. hallucinated by AI) data, processes and conclusions impossible due to the scale of the misinformation and the difficulty of identifying the misinformation buried inside superficially legitimate papers.

With both scientific and economic data and analysis now untrustworthy without exceedingly expensive, time-consuming vetting by human experts, where does this leave the "AI will automatically generate superabundance" hype? What's already clear--but inconvenient--is the mass adoption of inherently flawed AI is undermining the foundations of "value," however we wish to define it.

And as Mike also points out, this undermining of value has a financial consequence. We all know Gross Domestic Product (GDP) is a superficial, distorting measure of "prosperity," and the structural distortions of GDP (Waste Is Growth) are amplified by the hidden destruction of transparency, replicability and accountability by AI slop, whether intentional (malicious, deceptive, fraudulent) or as the unavoidable consequence of AI's core flaw.

These immense hidden costs will not show up in GDP until they collapse the entire house of speculative gambling cards propping up the global economy. Only then will the structural damage being wrought by our increasing reliance on tools that cannot discern the difference between fact and fantasy / fabrication / hallucination become visible.



And by then, of course, the damage will be irreversible without extraordinary costs and sacrifices, sacrifices few will volunteer to bear.

Remember that AI isn't "thinking," "understanding" or "making judgments": AI tools are engines of linguistic automation, not engines of understanding. The simulation is not the thing simulated. AI is not a "mind," it is a prompt and a probability distribution.

AI and human intelligence are drastically different--here's how.




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Is AI Reversing Anti-Progress or Is It Accelerating It?

Perhaps it's time to admit that AI hype is self-serving propaganda, and that we're actually living in a Philip K. Dick-type dystopia.

Consider the depth and consequences of the widening gap between these headlines. One the one hand, we're awash in articles proclaiming the immense value being generated by AI and the promise of future value that's beyond our imagination. But if we set aside the sci-fi promises of AI discovering miracle drugs that cure every disease and focus on what AI is actually being used for, it boils down to 1) increasing corporate revenues and 2) increasing corporate profits by reducing costs.

That's it. There is nothing else except clickbait headlines intended to create a PR-propaganda illusion that fantastic advances are just around the corner, just you wait.

But in the real world, AI is solely focused on increasing corporate profits via streamlining workflows and increasing productivity. There are hundreds of headlines along these lines: How AI is reshaping workflows and redefining jobs (mitsloan.mit.edu)

Here's the short version: Corporations are in a frenzy to use AI to jack up revenues via extraction rather than creating value, and boosting profits by slashing payrolls and costs. This is evident in headlines such as this:

Why are US consumers so angry? It's not just high prices. (theguardian.com)
First, her longtime vet, now part of a national chain, overcharged her $500 for her dog's teeth cleaning and didn't issue a promised refund. Then, her big box supermarket promoted a coupon on its app that wasn't applied at the checkout, costing her $30 and a trip back to the store. Finally, her health insurance company rejected her son's $1100 dental bill that she had been told would be 50% covered, despite protracted haggling.

"It's like Whac-A-Mole," the mother of two said. "You finish one and up pops another one."

"It feels like a war on consumers," said Sally Greenberg, the executive director of the National Consumers League, a 125-year-old consumer advocacy group. "Households are being hit by "a tsunami of fees and hidden charges and tricks and traps," she said.

Peter Fader, a Wharton School marketing professor, said, "But not only does service just suck, consumers are starting to realize that a lot of the cool data and technology is being used against them."

This isn't the FantasyLand story of corporations "creating value," it's the ugly real-world story of corporations increasing profits by controlling markets to extract more revenues while reducing value. In my book Investing In Revolution I explain that once companies eliminate real competition via monopoly, cartels or regulatory capture (deceptively called "market forces"), they become privatized totalitarian structures that corral consumers so they can be exploited to maximize extraction / profits without pushback from either the consumers or a controlled-by-the-highest-bidder state that enables privatized totalitarianism because a trickle of the trillions in profits flows to state insiders.

The ceaseless reduction of value and the expansion of data collection technologies to maximize extractive profiteering has a name: Anti-Progress, for declining quality and value coupled with higher costs and reduced alternatives (i.e. real competition) is not Progress, though it's ceaselessly touted as "Progress" by the corporations feasting on Anti-Progress to maximize profits by any means available.

Streamlining workflows and increasing productivity are not devoted to improving the quality of life of the populace or benefiting the shared interests of society; the single-minded goal is using AI to maximize profits via extraction. The difference between a totalitarian state (no competition) and totalitarian monopolies and cartels (no competition) is, well, the difference between privatized extraction and state extraction.

In the US, we have the worst of both worlds: an extractive state that funds and enables extractive privately owned corporations. Ask yourself an honest question--yes, that's difficult in a system that incentivizes artifice and self-serving deception: what exactly has AI done to improve real-world life in terms of quality and cost?

Even what's touted turns out to be extractive, distorting Anti-Progress. That AI is now our new best friend is not Progress, and neither is the core impossibility of trusting AI "answers" to be useful.

The core problem isn't just the illusion of "Progress" used to cover exploitive extraction; it's that AI is deceptive by its very nature, as it implicitly presents a probability distribution as fact, truth, judgment, thinking and understanding, when it cannot possibly be any of these.

This article explains this clearly and succinctly:

AI and human intelligence are drastically different--here's how. (scientificamerican.com)
The deeper issue is that the model cannot know when it is "hallucinating" because it cannot represent truth in the first place. It cannot form beliefs, revise them or check its output against the world. It cannot distinguish a reliable claim from an unreliable one except by analogy to prior linguistic patterns. In short, it cannot do what judgment is fundamentally for.

People are already using these systems in contexts in which it is necessary to distinguish between plausibility and truth, such as law, medicine and psychology. A model can generate a paragraph that sounds like a diagnosis, a legal analysis or a moral argument. But sound is not substance. The simulation is not the thing simulated.

They are engines of linguistic automation, not engines of understanding. They excel at drafting, summarizing, recombining and exploring ideas. But when we ask them to judge, we unintentionally redefine judgment--shifting it from a relation between a mind and the world to one between a prompt and a probability distribution.

Remember that smoothness is not insight, and eloquence is not evidence of understanding.

Here's a short list of the many examples of AI generating Anti-Progress on multiple fronts, including but not limited to extractive exploitation:

In the USA, the level of vigilance the average person has to maintain to avoid getting ripped off extracts its own kind of price -- one most analysis of dynamic pricing doesn't pay any attention to. (Tim Wu)

I think the Boomer/Gen Z discourse boils down to one thing and one thing alone: The America that Boomers grew up in put American families and American workers first. The America that Gen Z is growing up in puts literally everything else first.

We need a new regulatory paradigm to contain AI and prevent institutional collapse. A quick explanation.

The Record Divide Between Corporate Profits and Worker Pay: Labor's share of economic output just hit an all-time low, while the profit share hit a near record. It helps explain why consumers feel so glum. (wsj.com)

'It's never enough': young Americans struggle to build financial independence as cost of living spikes/ A difficult job market and rising costs are making it harder for young adults to enter adulthood.

Lastly, consider this question: How can we tell good AI from bad? (ft.com)

Short answer: we can't, and the gap between being able to ascertain the good from the bad is widening at an accelerating pace.

This is what we've been seeing with every company we work with. Try justifying spending 100k on token spend when only 18k even makes it to a stable product feature. Very interesting data across 2,444 companies. 82% of tokens are spent on AI-generated bugs, rework and review friction.



Please note what's missing from this list of AI concerns: "AI is improving my quality of life, reducing complexity and costs, and eliminating AI slop and extractive corporate exploitation at such a dizzying pace I wish it would slow down the vast improvements in my life so I can catch my breath."

Is AI Reversing Anti-Progress or Is It Accelerating It? The answer is it's accelerating Anti-Progress in every nook and cranny of the economy, society and culture. Perhaps it's time to admit that AI hype is self-serving propaganda, and that we're actually living in a Philip K. Dick-type dystopia in which we're constantly told AI will cure the diseases it's creating at some point in the future, while it generates more diseases at an ever-accelerating pace.


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Choose One: Housing Is Shelter, or Housing Is Just Another Asset in a Bubble Economy

Those seeking housing as shelter cannot compete with wealthy households and entities seeking places to park credit-generated capital for income and/or appreciation.

This will get massive pushback because it's true: either Housing Is Shelter, or Housing Is Just Another Asset in a Bubble Economy--it can't be both. This reality gets pushback because the conversion of housing from shelter into just another asset bubbling higher in a bubble-dependent economy has been so profitable for those inflating the bubble.

The basic pushback goes like this: housing has always been an investment, nothing has changed. This is classic misdirection. This is like saying "stock market options have always been a way to hedge positions" to justify the transition from hedging to extremes of gambling, i.e. zero-day expiration options (ODTE).

Whenever I suggest that housing is being hoarded by the wealthy and corporations as a low-risk asset to park credit-generated capital, I get pushback: no, I'm told, the percentage of housing that's empty most or all of the year owned by the wealthy and corporations is tiny, as is the percentage of housing owned as short-term vacation rentals (STVRs).

The problem with these claims is they're based on completely fraudulent / inaccurate statistics. There is no regulatory system that audits whether owners who obtained "owner occupied" mortgages actually live in the dwelling, or whether owners (especially those hidden behind LLCs and other cloaking mechanisms) are "owner occupants" as claimed.

Owner-Occupancy Fraud and Mortgage Performance (Philadelphia Federal Reserve) Occupancy fraud has been suggested as a contributor to the housing bubble. We show it was pervasive and remains present.

In other words, even the most cursory audits find significant percentages of "owner occupied" housing is vacant most or all of the time or is an unregistered short-term vacation rental. Anecdotally, many upper-middle class households own not just vacation / second homes in rural locales but "investment" homes that are empty or they use occasionally in urban areas, which due to high demand / valuations are hoarded because selling them in a bubble economy means the sellers will be unable to buy back into the market in the future.

The "monetize your empty room" AirBnB idea that began the short-term vacation rental market has transmogrified into a monster consuming the housing market in resort locales. Surveys have found that 15% or more of all available housing in resort locales is now absentee-owner short-term vacation rentals, and two-thirds of condominium buyers are out-of-state.
STVRs Have Destroyed America's Resort Towns

Some argue this doesn't matter because resort housing tends to be in rural regions with few jobs. It matters to local residents who are priced out. But "investment" housing isn't limited to resorts; there are an unknown but consequential number of vacant / STVR "investment" housing units in urban areas with jobs and strong demand for permanent housing.

Cities with rent control such as San Francisco and New York have renters who keep their low-cost flat vacant while living abroad. Since the rent-controlled apartment cannot be replaced once it's surrendered, it makes sense to hoard the rental for future or occasional use. Again, there is no system of auditing who actually lives in a dwelling as a permanent resident, as this is viewed in the US as an invasion of privacy.

(In Japan, local authorities keep close tabs on who is actually living in every dwelling as a matter of course. When we stayed in a friend's temporarily vacant flat for a few days, officials came to the door to check on who we were.)

The monetary policies of suppressing interest rates and expanding credit have favored the wealthy who have the income to support additional mortgages and the need to park their expanding capital somewhere. Housing is attractive because it's less volatile than the stock market and offers higher appreciation in a bubble economy than bonds.

Those seeking housing as shelter cannot compete with wealthy households and entities seeking places to park credit-generated capital for income and/or appreciation. In a bubble-dependent economy, there's no need to go through all the trouble of renting an empty dwelling, as the appreciation alone makes the investment worthwhile. Renting out an "investment" incurs risks and costs that are best avoided--unless the property generates a hefty profit as a remotely managed unregistered short-term vacation rental.

Once again, the pushback is pushback against inconvenient truths that threaten the ownership class that has reaped gains from housing as an asset class in a bubble economy. It's now evident that large corporate owners of thousands of rental units have used predatory pricing--oops, I mean dynamic pricing--to jack up rents in markets they are dominant players in; once the price point is set higher, small landlords push up their rents to the new "market price."

In a non-bubble economy, credit is scarce and expensive, and so asset bubbles can't be inflated as credit inflates. As credit inflates, the pool of money sloshing around seeking a low-risk home for safety and appreciation expands, and this pool sloshes into housing, driving home prices and rents out of reach of those whose income is wages, not wages plus capital-generated income.

Bubbles in housing generate artificial scarcity, scarcity not in the total number of dwellings but in the number of dwellings available and within reach for those seeking shelter, i.e. whatever is left after wealthy households and corporations with access to credit snap up housing as a low-risk place to park capital that offers tax benefits and appreciation.

Housing affordability has reached historic lows.



Housing payments have reached historic highs.



The wealthiest 10% have used their income and credit to bid up assets which bubble higher in bubble-dependent economies.



So here's the truth: we can choose housing as shelter or housing as an asset in a bubble economy, but we can't choose both. Housing as an asset in a bubble economy pushes housing out of reach of those seeking shelter.

And of course there's pushback against the truth that ours is a bubble-dependent economy. For a definitive answer, let's see how well the economy is doing after all the credit-asset-speculative bubbles pop and decline back to their starting point.




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AI Data Centers Are Not the Railroads of Today

The AI boom shares all the risk profiles of previous speculative manias but lacks society-wide benefits while generating fast-metastasizing negative consequences and costs.

The idea that the current bubble in AI data centers is an echo of the railroad-construction bubble of the 1870s is appealing--but only half-right. The completion of the first transcontinental railroad in late 1869 sparked a speculative mania of raising capital to build railroads, which were seen as "can't lose" investments in a technology that lowered transport costs from $1 to ten cents.

But not all routes had the potential to become profitable, and the resulting collapse of the railroad bubble devastated the developed-world economies, triggering a deep economic downturn from 1873 to 1879 that was called "The Great Depression" at the time (or "The Long Depression").

The term for speculative frenzies channeling vast sums into investments with difficult-to-assess risk profiles is mal-investment, and mal-investment on a large scale triggers financial panics and economic depressions in a well-understood feedback loop.

Money invested in digging a mine that doesn't yield any gold can't be recovered. That capital is gone. There is an opportunity cost to every investment: that capital could have been invested in something else that was more productive than the speculative bet on something with unclear risks and payback.

As the scale of losses become apparent, credit tightens and the pool of capital available shrinks. Short-term loans that can't be rolled over into longer duration loans trigger bankruptcies which quickly lead to bank runs (financial panics) and layoffs as businesses close. This decline in wages, revenues and the velocity of money is self-reinforcing, and the recovery process--being both financial and psychological--takes years.

The parallels with the AI speculative investment mania are obvious. Just as any railroad was viewed as guaranteed to be immensely profitable because railroads generated enormous efficiencies that reduced costs, all AI is guaranteed to be immensely profitable because AI generates enormous efficiencies that reduced costs. But in the real world, use cases for specific railroads and AI applications are stretched along a spectrum which isn't visible in the early stages of a speculative boom.

Individual use cases don't automatically guarantee an entire class of use cases will be successful. That one railroad--or application of AI--profitably reduced costs does not necessarily extend to all railroads or AI applications.

Nobody wants to wait around for the long process of sorting which use cases are actually beneficial and which are mal-investments, as the big money is made by making big bets in the early days. Human greed is a remarkable force, especially when combined with self-serving hype and the euphoria of the herd running.

In the current confluence of greed, hype and euphoria, the possibility that the inevitable aftermath of vast mal-investment is a Great Depression doesn't exactly resonate. AI isn't a railroad, it's the most amazing force in the Universe, etc. This is Wetware 1.0 in action: the psychology of speculative frenzies doesn't change, and so here we are--again.

Those are the parallels of the railroad mania of the 1870s and the current AI mania. But that's only half the story. Railroads did dramatically lower costs, turning unprofitable ventures into profitable ventures not by reducing production costs but by reducing transport costs, which prior to railroads might equal production costs.

The differences between railroads and LLM / generative AI are significant. While many railroads went bankrupt when the bubble burst, those that actually served expanding markets were eventually put to use as the tracks were still useful many years after being laid. A new locomotive type might enter service decades later, but the tracks remained useful and valuable for decades--with proper maintenance. The rails were not obsoleted every few years, nor did the the entire rail lines have to be replaced every few years.

AI is not permanent. It is constantly being obsoleted. A new class of lower-power consumption chips could obsolete the current class of AI chips, requiring a mass replacement of the entire processing foundation of AI. Innovations in software could reduce the processing demands, turning existing data centers into expenses rather than profit generators. AI software that users download onto their own computers negates the need for "renting" data centers (i.e. buying processing power with tokens) by generating models from the user's own data. These are just a few potential forces undermining the utility, lifespan and profitability of the current build-out of data centers.

While the cost structure of railroads were relatively straightforward, the costs of AI are complex and difficult to assess as initial costs are not total ownership costs, as maintenance expenses are still unfolding and future costs of resources and energy are trending higher.

While the cost reduction and efficiency benefits of depending on AI are as yet unclear, the costs of sorting "good AI" from "bad AI" are already mounting as real-world expenses. The market continues to underestimate the AI slop problem and what it means for enterprise adoption and spending.


Create enough hallucinated legal arguments, flawed engineering calculations and backdoor-ridden code, and the slop vats fill faster than our capacity to tell good work from bad, writes Tim Harford. How can we tell good AI from bad? (Financial Times)

Cedar Owl recently published a comprehensive overview of the Total Costs of Ownership of AI / Robotics and concluded they may exceed the costs of human employees. Will the cost of an AI Robot be higher than the salary of a Human Employee? AI Robot vs. Human Worker Total Cost of Ownership (cedarowl.substack.com)
"AI didn't remove cost--it changed where the cost lives."

As for profitable use cases, it's too soon to tell. Individual cases don't necessarily scale to the entire sector or economy. The hype is AI is scalable and applicable everywhere, but this isn't what real-world experience is finding.

Unlike railroads, whose cost-reduction benefits were immediate and measurable, the sum total of AI benefits is not just unclear but potentially negative. The negative effects of AI slop and malicious applications are already visible but the full consequences of their expansion cannot yet be determined.

Recent polls reveal a profound skepticism in the younger generations whose lives will be most impacted by AI. Gen Z Is Using A.I., but Doesn't Feel Great About It. Only 15 percent said they saw A.I. as a net benefit.



The structural limits of AI are equally visible but the full consequences of these multi-factor limitations cannot yet be determined. A recent article in Scientific American summarized one key limitation: the illusion that AI is "thinking," "understanding" and "reasoning": AI and human intelligence are drastically different--here's how:
"They are extraordinarily powerful tools when used as what they are: engines of linguistic automation, not engines of understanding. They excel at drafting, summarizing, recombining and exploring ideas. But when we ask them to judge, we unintentionally redefine judgment--shifting it from a relation between a mind and the world to one between a prompt and a probability distribution."

There are many other structural limitations whose nature limits "quick fixes." "To grow skills, people need to go through hardship. They need to develop the muscle to think through problems," he said. "How would someone question if AI is accurate if they don't have critical thinking?"

"This is the contradiction that has many AI boosters talking out of both sides of their mouths: The use of coding agents is actively diminishing the very skills needed to effectively manage the coding agents." (via Manoj S.)

CEOs are quietly realizing the AI replacement plan has a problem. Two problems, actually.
"One: the token costs for running AI agents are now exceeding what they were paying the employees they fired.

Two: when the tokens run out, the AI stops. Just stops. No continuity. No workaround. Just a spinning wheel where your workforce used to be."

AI coding frontloads one form of productivity by backloading the entire system with higher maintenance costs down the line. These costs are not visible in the initial phase, and by the time they're piling up, it's too late to reverse these structural costs.



The sums invested in AI data centers--and committed to planned data centers--are on a large enough scale that even the most robust economy is vulnerable to disruption when the revenues needed to justify these extraordinary sums fail to materialize and the total operational costs and costs of ownership become measurable.



Matt Stoller offered an apt analogy of AI data center capital investments:

But in a sense, the entire AI narrative is a bit like selling huge amounts of picks and shovels as everyone rushes to the mines, and then betting there will be gold when they all start digging. Much of the stock market is made up of investor speculation that pick and shovel companies are about to hit the motherlode. But we don't actually know how much gold there is, or even if there is any gold at all. So far, every powerful and rich person has insisted that there's so much gold we can't imagine it all, and anyone who thinks otherwise is a Luddite Marxist loser."

Perhaps most importantly, once we subtract the hype, there is no evidence-based answer to the question: will our society / the public benefit from AI? Or are all the proposed benefits of reducing costs and generating innovations concentrated in the hands of AI's owners and corporate users?

Cui bono--to whose benefit? What's being touted as beneficial to all--equivalent to railroads--is at this point only beneficial to owners and monopolistic-cartel corporations, the very asymmetry that is fast undermining the foundations of our social and economic systems.

Put another way: is AI actually solving the core problems undermining our society and economy--systemic asymmetries of costs, wealth, power, agency and opportunity--or is AI adding new problems--brain rot, dependence on black box systems owned by a handful of tech corporations, AI slop, deepfakes, and a tsunami of malicious AI?

For all these structural reasons, AI data centers are not the railroads of today. The AI boom shares all the risk profiles of previous speculative manias but lacks society-wide benefits while generating fast-metastasizing negative consequences and costs.


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