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.




My book Investing In Revolution is available at a 10% discount ($18 for the paperback, $24 for the hardcover and $8.95 for the ebook edition). Introduction (free)


Become a $3/month patron of my work via patreon.com

Subscribe to my Substack for free

---

NOTE: Contributions/subscriptions are acknowledged in the order received. Your name and email remain confidential and will not be given to any other individual, company or agency.

Thank you, David M. ($75), for your marvelously generous subscription to this site -- I am greatly honored by your support and readership.		Thank you, Julie W. ($3/month), for your wondrously generous subscription to this site -- I am greatly honored by your support and readership.

Read more...

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.


My book Investing In Revolution is available at a 10% discount ($18 for the paperback, $24 for the hardcover and $8.95 for the ebook edition). Introduction (free)


Become a $3/month patron of my work via patreon.com

Subscribe to my Substack for free

---

NOTE: Contributions/subscriptions are acknowledged in the order received. Your name and email remain confidential and will not be given to any other individual, company or agency.

Thank you, David M. ($75), for your marvelously generous subscription to this site -- I am greatly honored by your support and readership.		Thank you, Julie W. ($3/month), for your wondrously generous subscription to this site -- I am greatly honored by your support and readership.

Read more...

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.




My book Investing In Revolution is available at a 10% discount ($18 for the paperback, $24 for the hardcover and $8.95 for the ebook edition). Introduction (free)


Become a $3/month patron of my work via patreon.com

Subscribe to my Substack for free

---

NOTE: Contributions/subscriptions are acknowledged in the order received. Your name and email remain confidential and will not be given to any other individual, company or agency.

Thank you, Wade P. ($70), for your marvelously generous subscription to this site -- I am greatly honored by your support and readership.		Thank you, Richard C. ($7/month), for your wondrously generous subscription to this site -- I am greatly honored by your support and readership.

Read more...

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.


My book Investing In Revolution is available at a 10% discount ($18 for the paperback, $24 for the hardcover and $8.95 for the ebook edition). Introduction (free)


Become a $3/month patron of my work via patreon.com

Subscribe to my Substack for free

---

NOTE: Contributions/subscriptions are acknowledged in the order received. Your name and email remain confidential and will not be given to any other individual, company or agency.

Thank you, Wade P. ($70), for your marvelously generous subscription to this site -- I am greatly honored by your support and readership.		Thank you, Richard C. ($7/month), for your wondrously generous subscription to this site -- I am greatly honored by your support and readership.

Read more...

Could Instability Trigger Radical Change In Your Life?

I propose that the world is upside down, that the way we live is the opposite of what we're told it is: we don't experience Progress, we experience Anti-Progress.

My five most recent essays (listed below) lay out an account of the present era that is radically different from the conventional narrative.

It's worth noting that my writing is not "validated by credentials so you should listen to this person" or by data-based claims that "he called the exact top and bottom of the market and has beaten the market indices for 27 years." The foundation of my work is the text either validates or invalidates itself by its sources and reasoning and is best read as "written by anonymous."

If you decide on the validity of the text based on the author's credentials and investment track record, there are hundreds of PhD economists to follow and thousands of accredited financial advisors to consult--or consult Warren Buffet's annual reports, as his investment track record speaks for itself.

The trust we place in these validations based on credentials and past data rests on a continuation of the conventional status quo, i.e. recency bias, the belief that the recent past is a trustworthy guide to the future because everything is stable and predictable.

And since everyone making their livelihood off the status quo has a built-in incentive to assume it's stable and predictable, there is no advantage to entertaining possibilities outside this context.

This is the basis of assessing texts and ideas on their own merits rather than trusting the author will be correct this time because they are certified experts and/or they were right about things in the past. Trusting recency bias and credentials works well if the system is indeed stable and predictable. If it's not, then letting the ideas speak for themselves becomes the way to widen our survey of potential futures.

I propose that the world is upside down, that the way we live is the opposite of what we're told it is: we don't experience Progress, we experience Anti-Progress. We don't live in an economy that optimizes value to compete for our dollars; we live in an economy that optimizes eliminating competition to maximize extraction. All the technologies of AI aren't additive and liberating; they're powerful tools that optimize centralized control and extraction. The claim is that AI will help us but the real goal is to use us. The system we inhabit isn't transparently fair, it's transparently corrupt, the perfection of self-service passing itself off as manifesting the noble ideals of "capitalism" and "democracy."

Rather than being victims of powers beyond our control, we accepted the erosion of fairness--the foundation of all human societies--into a rigged casino that favors the few at the expense of the many because we accepted the promise that this unfair, corrupt economy, society and political system enabled us to get ahead: who needs fairness if we have a seat in the rigged casino?

In the conventional telling, ours is a system of innovation, growth and opportunity. The reality is the opposite: the "innovation, growth and opportunity" are all concentrated in a vast credit-asset bubble that has richly rewarded those who own the assets that have skyrocketed in value and left everyone who doesn't own these assets behind.

This structure--the real world is the opposite of what we're told--is a civilizational psychosis that benefits those at the top of the wealth-power pyramid. We go along with this psychosis because denial is our defense against a reality too painful to bear: our progression from a society of systemic fairness to a society of systemic unfairness.

But denial, unfairness and credit-asset bubbles are all inherently unstable, and so once the bubble pops, denial will crack and be replaced by anger, an anger at ourselves and those we trusted that will seek expression by focusing on those who glorified the rigged casino the loudest because it enriched them so immensely.

The alternative accounts touted by many are simply different flavors of the conventional narrative.

One is that the Powers That Be are instituting a techno-financial web we cannot escape of tokens, blockchains and stable coins that will digitize every transaction and enable the Powers That Be to switch our financial lives on or off as the means of an ironclad control.

If we change our money, the narrative holds, then we can escape this perfection of Orwellian control.

The problem is that changing the money in a rigged casino doesn't unrig the casino; all it means is those in the casino start using another form of money.

Another narrative holds that technology and system dynamics can be wielded to reverse the decay and fulfill the fantasies of super-abundance and technological Progress.

Neither narrative acknowledges that humans are hard-wired to live in a moral universe, as our sensitivity to fairness--which includes transparency, integrity, truth, honesty, duty, obligation and reciprocity--is the foundation of our social skills, which are our core selective advantage as a species.

The moral universe isn't some concept that isn't "real"--we're constantly told that what's "real" is finance, money, the economy, technology, data and systems--the moral universe is the foundation of all civilization. In dismissing this innate sensitivity to fairness as inconsequential in the "real world" of systems and data, we dismiss an understanding of our civilizational psychosis and our own denial of this psychosis.

There is a place for technology, finance, systems and data, but by measuring "progress" solely by technological standards, measuring "value" solely by financial metrics and measuring "understanding" (i.e. what's being "optimized") by data and systems--all reductionist left-hemisphere functions-- we cut ourselves off from the moral universe that enables our primary selective species advantage--our social experience.

We are not social creatures like ants that self-organize by instinct and pheromone trails: we self-organize in a moral universe in which our exquisite sensitivity to fairness and unfairness in all its intuitive, right-hemisphere width and breadth has been hard-wired as the essential foundation of our primary selective species advantage.

All of which leads to a question we ask ourselves: could instability trigger radical change in our own life?

A health crisis offers an analogy many of us have experienced.

We're living our lives, doing what we always do, and suddenly we experience a health emergency that calls how we've been living into question: how did I become ill? We realize we weren't really paying attention to our diet, our fitness, our sources of stress, our conflicting goals or our doubts or anomie. We never thought of ourselves as being in denial, but we were in denial--a denial that included denial itself.

Faced with a condition that could prove fatal or debilitating, we realize our old way of living wasn't healthy, even though we made excuses and told ourselves that we were generally living a healthy life. Stripped of excuses and rationalizations, we realize we were eating out a lot and that these meals weren't necessarily healthy, even though we ordered the salad instead of the fries. The meals were optimized to trigger our dopamine receptors--this tastes good--and generate a profit for a highly competitive, cost-sensitive business.

We realize that if we truly want to have a healthy diet, we have to prepare real, highly nutritious food at home, with very occasional exceptions. We realize that our stress levels cannot possibly decline unless we make radical changes in our employment / work lives, our home lives and perhaps in our entire understanding of what our life is actually about.

The point here is health crises force us to reassess things we were content to leave as-is prior to the crisis. We weren't actually living a very healthy life, but we told ourselves it was healthy enough because we had no symptoms of illness. That the causal chains of an unhealthy life--stress, diet, fitness, unresolved conflicts--were steadily undermining our well-being was invisible, until something snapped and we experience a health crisis.

Simply put, we avoid radical change until there is no other option left. Denial is comfortable, and we do what's comfortable until it's no longer possible to do so.

Financial matters can also force radical change on us. Our home equity is a "savings account" we can tap until the bubble pops and suddenly we have no equity at all--we only have debt. Equity comes and goes but the debt remains unchanged: that's the problem with debt.

The system we inhabit is inherently unstable because it rests on artifice, not authenticity, on financial bubbles, not value, and Anti-Progress, not Progress. Denial is comfortable and facing all that undermines the quality of our lives and our well-being is not just uncomfortable, it's extremely troubling, for we sense that once we strip away our denial, excuses and rationalizations, we'll be forced to make radical changes in our lives, changes we're not prepared to make until there is no other option left.

If what I've laid out in these five essays is an accurate account of what's really going on, the intrinsic instability of a system that depends on our acceptance of civilizational psychosis for its continuity and coherence will crack wide open. And when that happens, our denial will crack wide open, and many of us will become angry that the rigged casino didn't work out for us as promised.

Many are confident that any crisis is 10 or 15 years away, and so we'll all have plenty of time to prepare. Their forecast may prove to be correct, but their confidence is a form of denial of what an unstable state means: an unstable state is unpredictable and prone to sudden phase changes.

To be confident that any crisis is 10 years away is akin to gazing at an unstable mountainside and declaring that an avalanche is safely in the future. Any confidence in a prediction about an unstable system is a tacit denial of the way that instability is hidden beneath a surface stability that is reassuring due to recency bias but misleading.

When the latest polls find that only 18% of Gen Z see AI as a positive development, this is the equivalent of a tremor shaking an unstable mountainside. Is assuming we'll all have decades to prepare for instability reality-based, or is it denial dressed up in data?

Many of us will be forced to make radical changes in our own lives once the unstable system we inhabit cracks wide open. Those who recognized the fragility of our civilizational psychosis and acted before the avalanche will do better than those who waited until it was too late. My point here is: asking ourselves what it will take to make radical changes in our own lives now, not in some distant future, is a worthwhile exercise.

Anticipating that we might be thirsty in the future is a motivation to start digging a well now, as "once we're thirsty, it's too late to dig a well."

From the point of view of stability, any radical change is needlessly risky. When a crisis takes away stability and predictability, then everything reverses: clinging on to what caused the crisis is what's risky and making radical changes is what offers hope for solutions.

Even when we're in a situation that's undermining our well-being, we cling to the status quo. When we're finally forced to undertake radical changes, it's a kind of relief, for we are forced to jettison what wasn't working but was working just well enough to keep us frozen in place.



Please read these essays as if they are anonymous and therefore must be judged on their own merits.

>When Unfairness Is Systemic, the Consequences Are Flight, Resistance, Revolt

We've Optimized Fragility, Failure, Denial--and Rage

Inequality, AI and Digital Life Are Undermining Society

Remember: In a Crisis, Everyone Will Consider Themselves 'The Good Guys'

Chaos Unleashed: When "Irrational" Makes Perfect Sense

New short video: Could Instability Trigger Radical Change In Your Life? (2:16 min)

Read more...