Welcome to the Theater of the Absurd

The real world no longer matters, what matters is the performance on stage. Welcome to the Theater of the Absurd.

In the present era, all the world is a stage and everything is a performance on that stage: welcome to the Theater of the Absurd, a Hollywood set fabricated of cardboard and plaster made to look like gold leaf and marble columns, where the contraptions and ropes that do the magic are hidden behind purple velvet drapery.

Every detail has been designed to create the illusion of permanence and power to rivet our attention and distract us from noticing that behind this faux fabrication, the world is on fire.

Since the entire point of the theatrics is to cloak the decay of the status quo from serving shared interests to a craven scramble of self-enrichment, no expense is spared in the theatrics, for as the gulf between the reality of who's getting richer and who's losing ground and what the performers claim--this is the best of all possible worlds because of technology and Progress--widens, it becomes necessary to pour more resources into the performances, lest the losers catch on that the performance is the con that keeps the self-serving status quo from being revealed as an extractive, exploitive arrangement favoring the few.

As the audience is no longer entranced by mere performance, the theatrics must be ramped up to absurd heights. Leaders shout continually through the megaphone of social media, every pronouncement is exaggerated to self-parody, jokers prance around as Wall Street jugglers perform tricks, and faux trials run continuously in the background, exiling star performers as part of the enthralling theatrics.

The audience soon habituates to the exaggerations, and so the absurdity is notched higher. Every outrage is played out on stage, and soon the audience is no longer outraged by anything, for every aspect of the performance is now accepted as "normal." In this jaded state, the audience becomes restive and starts booing the performers.

The Theater of the Absurd resorts to throwing money into the audience, creating frenzies as all those losing ground stampede to collect the coins as their last best change of getting rich enough to avoid the fires burning behind the stage.

While the money is being thrown into the increasingly agitated mob, audience members are invited onto the stage to perform their own theatrics. This taste of fame is electrifying, and soon the stage is a seething mass of onlookers seeking their moment in the spotlight, leaders claiming divine inspiration, and a crush of jugglers, clowns, and jokers pressing forward and being pushed off stage in the melee.



Since the performance is now the key to the survival of the status quo arrangement, nobody's paying attention to the fires burning behind the stage set. The real world no longer matters, what matters is the performance on stage. Welcome to the Theater of the Absurd, where the performance is more real than the world burning behind the flimsy simulations and facsimiles of permanence and power.


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Automating Our Dependence Will Cripple Us

The rush to monetize automation / AI is self-liquidating.

Dependence is easy but crippling. When we're children or advanced in age, we're dependent on adults for our care. This is the normal flow of human life. But when we're dependent as adults, it cripples us, for it removes the pressure to acquire problem-solving skills that strengthen our facility with both processes and results.

In my post on The Inevitability of the AI Depression, I noted the distinction between process-based work and results-based work, as standardized processes are easily automated, while generating results that can be tested / verified is much more difficult, as a standardized process might not suffice.

Problem-solving demands integrating both process and results, as being able to repeat the desired results requires assembling a process which is organized enough to generate the desired results but flexible enough to deal with novel problems.

This is the shadowy realm of experiential knowledge, the intuitive tacit knowledge that can only be gained by experience. We can attempt to distill this knowledge down to rules of thumb, i.e. heuristics, but when we turn these heuristics into algorithms, we're converting right-hemisphere integrative thinking into formal rational processes--left-hemisphere thinking. This conversion loses the essential nature of tacit / intuitive problem-solving.

When the State or parents protect adults from the pressure of problem-solve and the consequences of failure, this protection has a price: the adult has no opportunity or pressure to develop the self-confidence that can only be gained by enduring--and learning from--failure, and the uneven, no-guarantees process of experimentation and effort of problem-solving.

The adult learns not how to be independent; they learn to fail so demonstrably that they will be rescued once again.

Failure is stressful--in today's terminology, traumatic. But failure is the source of pressure to problem-solve. If some entity solves all our problems, in effect automating processes so we don't have to learn them and delivering results that we didn't have to figure out how to generate, then we learn nothing that contributes to our experiential knowledge, self-reliance or self-confidence.

Having processes and results automated cripples us: we know virtually nothing because we were never forced by problems / failure to develop the self-discipline, ruggedness, self-awareness and hard thinking demanded to endure failure and keep trying new approaches until we solve the problem at hand.

The harder the problem, the harder the process of solving it, the more we struggle and endure, the more we learn. Failure, doubt, anxiety and suffering are the crucible in which we gain experiential problem-solving skills which bolster our self-confidence and generate skills that can be applied to future problems.

The key to problem-solving is not just learning from the experience of failure, but the experience of joy from finding a solution and the rarely described joys of developing flexible skills and processes--the key word here being flexible.

This brings us to the automation of processes and results via artificial intelligence (AI). The basic idea here is we no longer have to learn the tediously acquired deep-knowledge of how things work, as AI does all this for us.

And we no longer have to learn to triage tasks--eliminate make-work / BS work / low-productivity processes, we simply assign our AI agents to perform all that low-value work and pat ourselves on the back for "optimizing workflows."

As for getting results, we simply prompt AI agents to generate the desired output. And since we don't actually know how to generate these results ourselves, we have to trust that the AI agent is 1) telling the truth, which is itself a problem we cannot solve, and 2) that the result isn't a hallucination or falsity generated by the homogenization of the AI's knowledge base and programming.

There is no pressure now to tediously acquire deep knowledge such as learning a foreign language or learning how to play a musical instrument proficiently, as AI translates everything and can compose music (and everything else) via prompts. There's no longer any need to learn how to write well, as AI does this for us.

All these automated processes and results are homogenized, as AI eliminates the rough edges of variability as reducing the probabilities of a result that passes the tests of accuracy.

This is why studies have found that human users of AI have homogenized thought processes even after they stop using AI.

What's lost in automating processes and results is far more profound than the mainstream can grasp. We lose the ability to think deeply, and this cripples our capacity to develop real problem-solving skills. And since it removes the pressure of having to learn difficult skills and the pressures generated by failure, we no longer have any incentive / selective pressure to learn experiential, tacit knowledge.

Writing isn't just stringing together words in a format that passes auto-correct spelling and grammar rules. Writing is the process of deep thinking.

Learning a foreign language isn't just something that facilitates being a tourist. It's a process of learning new ways of contextualizing and organizing the world, and this too is a process of deep thinking.

Here is an example of what I'm describing. This is Fragment 54 from the ancient Greek philosopher Heraclitus. Notice the range of translations into English.

"Latent structure is master of obvious structure." (quoted by Philip K. Dick)

"The unseen design of things is more harmonious than the seen." Guy Davenport

"The hidden attunement is better than the obvious one." Charles H. Kahn

"Harmony which does not appear clearly is superior to that which is clear and apparent."

"Apparent, hidden. more powerful, more desirable."

"Hidden structure is more powerful than visible structure."

I do not know the Greek language but I studied a text that placed the original Greek side-by-side with the English translation and exegesis, so I could discern the sources of the many translations.

I've found the same is true of the many translations of the Tao Te Ching. I do not know Chinese, but I am familiar with the construction and ambiguities of key ideograms. I've read many translations but prefer that of my professor, Chang Chung-yuan: Tao: A New Way of Thinking.

Here is an excerpt from Chapter 41:
Understand Tao as if you did not understand it.
Enter into Tao as if you were leaving it.

I've formally studied French and Japanese, and am not fluent in either, but I learned enough to grasp how social structures are reflected in the language itself.

None of this is visible in an AI translation. It's too easy and so we become dependent not just for the translation but in the loss of the ability to understand more than the superficial conversion.

In music, composing is now easy: just prompt AI. But in becoming dependent on AI we can never experience the frustrations of trying different chord progressions and working out a new melody, or experience the physical sonic joy of strumming the "magic E chord" (7th fret on the guitar).

I spent hours working out a double-lead for guitar that lasts all of nine seconds on the recording. The process was painstaking but fun, in the way that only painstaking experimentation can be fun. You learn by stretching yourself, not by repeating what you already know or having AI do it for you.

I only have my own life experiences as examples, and so these may not be great examples but they're all I can vouch for because I lived them.

Just the other day I was working on an old structure constructed of steel pipes. One of the joints was rusted and needed to be strengthened. The conventional approach would be to replace the whole thing, at significant expense, or replace (at great expense of labor) the rusting lengths and connectors. Neither was worth the time or money in this situation, so I rummaged through the workshop and found a steel plate that's used to cover copper piping running inside stud walls so drywall nails or screws don't puncture the water lines.

I bent the plate into a curve using a few tricks and drilled holes through the steel pipe and connected the plate with through-bolts left over from another project. Is it a thing of beauty? Not by a long shot. Does it do the job at zero cost and a few minutes of my time? Absolutely. Did it solve the problem with minimal investment? Yes.



The problem wasn't a deficiency of beauty. The problem was strengthening a weak connection and time pressure (daylight ending). Quick-and-dirty was the optimal solution.

I doubt a robot could have replaced my processes. They're too extemporaneous, too contingent, too unpredictable (using what's laying around, etc.) and require multiple tactile skills of applying just the right amount of force, but not too much. They're based on 53 years of experience with tools, metal, connectors, and the physical knowingness that can only be gained from long, wide-ranging experience. Everyone with similar experience knows what I mean.

Growing food isn't easy. We look at mechanized equipment guided by AI and we think it's easy, but it is intrinsically difficult due to Nature's variability. Learning how to grow food takes a high tolerance for failure and experimentation, careful observation and the discipline to record what was tried and how it fared. I use six kinds of fertilizer, in various combinations depending on the tree / plant. Others have developed their own mixes and stratagems depending on their terroir and experiences.

Once again, there is no algorithmic shortcut. The only process that yields problem-solving on the fly is experiential.

People occasionally suggest I "monetize" our produce, selling it at a farmer's market, etc. This misses the point via a fatally flawed reduction of everything to money. The point is self-reliance, the acquisition of priceless skills and experience, and the sharing of our produce with others to strengthen a social network. Selling our produce would be a catastrophic waste of a precious resource. Not everything of value can be priced in money.

When we were building our house in our 20s, with no loan and minimal savings / income, we moved into the shell with Visqueen (sheet plastic) over the window openings as soon as we had a working tub and toilet. A two-burner camp stove was the kitchen. We did the dishes in the tub. Under pressure, you improvise. It wasn't that hard; we were sheltered from the weather and had everything we needed.

Many people misunderstand athletics. They think it's about talent or winning. It's actually about training, not to hit some metric (weight lifted, miles run, etc.) but integrated physicality: agility, strength, speed, endurance and the capacity to endure while avoiding needless injury brought on by prideful excess.

Despite a complete lack of talent, I played team basketball for five years and one season of football. I learned about training, self-discipline, unit cohesion and much more. Training is tedious and maintaining agility, strength, speed, endurance and the capacity to endure is demanding. But once again, there is no substitute for experience.

(If you want a metric, choose one that reflects overall health: the triglycerides-HDL cholesterol ratio: triglycerides divided by HDL. Under 2 is good; even lower is better. Mine is 74/61 probably because I work stupidly hard physically instead of buying a robot.)

When everything is given to you or done for you, you learn nothing, have nothing to be proud of and no experience of the joys of hardship met and sacrifices made that paid off. And if they didn't pay off, you learned something valuable that could be usefully applied later.

What looks easy when watching a cooking video is tricky in real life. Consider a basic skill like making a roux--cooking flour in butter. It's easy to undercook it or burn it. You really only learn by making both mistakes.

So buy food out and learn nothing or learn to cook the hard way, which is the only way.

This is the fatal consequence of becoming dependent on automation / AI to "optimize everything." We're actually optimizing failure.

The fatal consequences are scale-invariant. New research suggests the vast, immensely successful Khmer civilization in southeast Asia succumbed not just to environmental changes (drought) but to the decay / loss of the social / institutional know-how needed to maintain the complex system of waterways and irrigation that enabled food production at scale.

No human remains were found in the abandoned cities. There were no mass die-offs; the residents just left. Since they retained the basic skills needed to make a living off the land, life went on.

As our horrendously complex systems become dependent on automation / AI, without being aware of it we're generating dependencies that carry grave risks: once the number of humans who truly understand how to build systems from scratch or reconfigure them on the fly dwindle, when novel conditions cause the automated systems to fail, recovery will be out of reach.

Right now, this sounds farfetched because there are still enough people around who have deep experiential knowledge and tacit problem-solving skills. But since these skills cannot truly be taught, they must be learned the hard way, by tedious experience of failure and experimentation, then once those people retire, the entire civilization is vulnerable to cascading failure.

This is why I say that the rush to monetize automation / AI is self-liquidating: in optimizing both low-value workflows and essential systems, we're becoming fatally dependent on systems we no longer have the experience to fix on our own.

This post was first distributed to paid subscribers; how to subscribe to OTM. Thank you for supporting my work.


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Our Post-Truth, Post-Trust World

A system that comes to depend on synthetic signaling for its "information" is doomed to Model Collapse, as its signaling has completely detached from the real world.

That we inhabit a post-truth world seems to accepted wisdom. But that's only half of it. We also live in a post-trust world. In a post-truth world, everything is shaped by the implicit goals of the entity claiming to state the "truth," as the entire point of claiming to state the "truth" is to persuade the target populace to agree to something favorable to the issuer of the claimed "truth."

In other words, the "truth" as something that has no intentional spin of self-interest no longer exists. What is passed off as "truth" is spin intended / designed to serve the interests of those doing the spinning.

This is the definition of propaganda and marketing, which are pure expressions of self-interest, and they've been around since the dawn of civilization, as persuading others to do what serves your private interests is much lower cost / more profitable than having to modify their behaviors with force.

The first step in the con of propaganda and marketing is to win the trust of the mark. This is a fascinating process, as some people are willing believers and others are skeptical, and so the trust campaign must speak to both the skeptics and those primed to embrace the message for reasons that have less to do with the entity issuing the message and more to do with their internal beliefs.

The trick with skeptics is to present persuasive evidence--the "facts." These can be first-person accounts, scientific studies, or something presented as self-evident. The con artist presents the facts as if they are objective and the mark is invited to "decide for yourself:" the con artist claims he has no intent to persuade.

This is humorously illustrated in Melville's classic novel The Confidence-Man.

The rise of the collection of data and the scientific method introduced the idea of "objective truth" that was based on facts collected from observations that were repeatable by anyone able to isolate the same variables. In other words, these truths could be verified by anyone using the same tools to collect data that isolated the same variables, so it wasn't a private truth, it was a public truth everyone had to accept as fact.

The power of "objective fact" was too good to pass up, and so manipulating the metrics of data collection and analysis became the new territory of developing trust and establishing "truth" to serve private interests. Sample sizes were kept small, subjects were selected for their likelihood of yielding the desired data, and analytic tools weeded out outliers that undermined or contradicted the pre-selected "results."

As McLuhan observed, The medium is both the message and the massage, and so the synthetic media that broadcast the human voice and visual images captured our attention and imagination in ways the written word could not. Now we have AI, which mimics human speech so engagingly that we attribute it with human characteristics: intelligence, emotions, empathy, etc.

With social media and smartphones, these media/ AI technologies have scalable visibility and virulence: they are ubiquitous (everywhere) and extremely contagious / virulent, spreading quickly through vast populations.

Few would claim to trust the "truthiness" of social media content or its sources, but that no longer matters. what matters is the signal embedded in the content that triggers a dopamine cascade in the "consumer" of content--what Big Tech calls engagement and others call addiction.

Signals are symbolic short-cuts that bypass rational filters by firing dopamine receptors. This makes them ideal on two counts: they don't require the lengthy processes required to nurture trust or establish the "truth," processes which require some connection between the real world and the claim being made.

Signals are small in size and easy to replicate, in effect cognitive/emotional viruses that bypass our cognitive/emotional immune system of skeptical wariness of anything that smacks of self-interest, i.e sure things, guarantees of immense gains and grandiose claims.

Signals bypass the process of connecting a claim to the real world. This is their unmatched power. In the ancient world, pageantry and public displays acted as signals of power, status and victory. The power and status were symbolically on display, as only those with wealth and power could afford such performances.

The importance of these symbolic displays reinforcing the legitimacy and power of elites should not be underestimated. This is why Leonardo Da Vinci was hired to design and engineer lavish parades of movement and color, extravaganzas designed to impress and entrance onlookers.

Such symbolic signaling was enormously costly, and so they reflected real wealth and power, for only those possessing those resources could manage such expense.

Now digital synthetic signaling is virtually free. When Leonardo's pageantry came to life, it was unmistakably authentic, for it demanded real world resources and labor. Digital synthetic signals require nothing but visibility and virulence--no connections to the real world are required.

So AI's mastery of natural language signals intelligence, money signals wealth, technology signals Progress, a diploma signals "hire me, I'm a valuable worker," and so on. Signaling replaces persuasion that is still connected to the real world with dopamine cascades.

Synthetic signaling is inherently self-referential: it's "trustworthy" and "plausible" because we've already seen it elsewhere, and ubiquity is itself a signal of plausibility and trustworthiness, because could so many others be completely wrong?

"Breaking news" must be real, right? Words, images, speech are all easily turned into symbolic signals that carry implicit claims of retaining some connection to the real world when in fact there is none.

Signaling is easily gamed, falsified, curated, edited, cosmetically enhanced and generated by automation, while the real world it supposedly symbolizes / reflects is not so pliable. The Late Western Roman Empire can be viewed as a system that retained sufficient resources to stage signals of continuity and power that had lost all connections to the real world beyond Imperial enclaves.

But this expenditure of scarce resources on signaling is self-liquidating: the costs of issuing symbolic representations of power consumes the resources needed to sustain the system's core structures, which then collapse even as the signals continue engaging us.

In summary: the post-truth / post-trust world is self-liquidating, as its synthetic claims of connection to the real world are fake, and the hollowness of its self-referential nature and its rampant overuse exhausts the dopamine cascades' effectiveness. Drained of authentic cognition and emotion by the ceaseless onslaught of synthetic digital signaling, our engagement withers. We lose interest, become detached, unresponsive, or hyper-aggressive, in either case stripped of the capacity for independent thought or action, just like the mice trapped in Mouse Utopia.

A system that comes to depend on synthetic signaling for its "information" is doomed to Model Collapse, as its signaling has completely detached from the real world.






New Podcast: Self-Liquidating Systems, Parallel Worlds, and AI Doesn't Live In A Moral Universe (Leafbox)
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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)


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Oil, Inflation and Recession

It's not the price of oil per se that triggers recession, it's the underlying vulnerabilities that have been cloaked with happy story narratives to keep the game going.

Recessions don't require a spike in the price of oil/gasoline, but spikes in energy prices trigger recessions. This makes sense, as hydrocarbons are the foundation of every industry, from the so-called "green" industries to all the high-tech industries (SpaceX, AI data centers etc.) to transport, plastics and everything else.

Recessions have other causes, of course: the business cycle of over-indebtedness and speculative excesses leading to defaults and the contraction of credit and spending, the collapse of speculative asset bubbles, the inflationary spiral of overborrowing to fund "guns and butter," and disruptive events such as plagues and wars.

Inflation reduces discretionary income as a larger share of earnings must be devoted to essentials. In a consumer economy, this reduction of discretionary income leads to households borrowing more to fill the widening gap between what they reckon is their rightful lifestyle and the purchasing power of their earnings.

This increase in debt leads to a higher percentage of net earnings being devoted to interest and principal, further reducing discretionary income. The eventual retrenchment--reducing debt by reducing spending and default--leads to a contraction in consumption, i.e. recession.

Recessions occur when a happy story about the economy that doesn't reflect reality encounters reality. Before recessions, the happy story is always the same: corporate profits are solid and rising, consumer spending is rock-solid, employment is strong, unemployment is low, the household balance sheet is healthy, technology is increasing productivity, and so on.

According to the happy story, a recession is impossible, so borrow and buy, buy, buy--stocks, houses, experiences, cruises, buy it all because the good times are permanent.

The vulnerabilities generated by over-reliance on borrowing to fund spending and the corrosive effects of inflation are buried beneath statistical trickery: add all the wealthy households to the mix and then take the average, and voila: look how rich the average household is. All is well, borrow and buy to your heart's content. Mix in hedonic adjustments and pixie-dust and voila, 8% inflation is magically reduced to 2.5%.

The suspension of disbelief / confidence is the magic of the happy story narrative. As long as people are complacent and confident, they act on the belief that their income and wealth will continue rising, enabling more borrowing and spending.

That this is not necessarily in their best interests in the long term is what must be hidden, lest they curtail borrowing and spending because the whole point of the economy is to maximize profits and this is only possible if people who don't earn enough money to spend freely borrow to spend freely.

This is where the other magic in the happy story becomes essential: the wealth effect generated by credit-asset bubbles. If people see their house and stock portfolios rising in value, they feel wealthier and are more confident in borrowing and spending because they have this wealth piling up in the background.

It's like a savings account that increases without the sacrifice of deferring consumption: in credit-asset bubbles, we get to have our cake and eat it, too.

The problem that must be hidden by the happy story is that excessive debt and speculation are self-liquidating: the machinery that makes them work self-destructs by its very nature. Debt accrues interest which reduces discretionary income which sets up contraction of credit and consumption, and all credit-asset bubbles pop, regardless of the intensity of the propaganda / happy story that this isn't a bubble, it's "capitalism" or "technology" or "animal spirits."

It's not a specific price point or metric that causes recession: it's the decay of confidence and discretionary income that leads to recession. Confidence is fragile by its very nature. We've been selected to be wary of surplus suddenly becoming scarcity, and rising prices of energy cascading through the entire economy activates a reappraisal of our complacent confidence.

Every business is hammered by rising costs for literally everything they buy to operate, and since the discretionary income of the bottom 80% is already under pressure, they can't raise prices much without losing sales.

Households feel the pinch of rising utilities and fuel immediately, and for both enterprises and households, confidence in the future is at risk of eroding like a sand castle in a rising tide.

Here is a chart of the average price of gasoline in the US from 1976 to February 2026. I've added the recent spike to the current average price of $4.11 / gallon. Interestingly, this is pretty close to the inflation-adjusted price of gasoline in the 1973-74 Gas Crisis, and the nominal price in July 2008. Adjusted for inflation, $4.11 in July 2008 is $6.11 in today's dollars.



The point I want to make here is that there is no price trigger for recession, as it depends on the underlying fragilities and vulnerabilities of the economy. Put another way, it depends on the width of the gap between the happy story narrative intended to keep confidence and complacency high and the realities of higher costs and rising debt service reducing discretionary income.

Credit-asset bubbles pop for many reasons, but what we experience is a collapse of confidence that the bubble will continue inflating, making us richer every day, in every way. The core fragility of today's economy is the expansion of consumption now depends on the spending of the top 10%, who just so happen to own the lion's share of income-producing assets such as real estate, stocks, corporate bonds and enterprises.

Once the Everything Bubble pops, the confidence of the top earners and spenders will collapse, leading to a decline in their borrowing and spending.



Oil doesn't need to hit $147/barrel and gasoline doesn't need to reach $6/gallon to trigger a recession. (Gasoline is over $6/gallon in California and over $5/gallon in states with high fuel taxes.) There is no specific price-point, any more than there is some specific metric that enables us to predict an avalanche. It all depends on the underlying vulnerabilities and excesses of the economy at that moment in time.

When he's confident, Wile can walk on air. It's when he suddenly discerns reality that his confidence vanishes. Recessions always catch conventional economists by surprise because the collapse of confidence triggers a sudden rise in unemployment and defaults and a sharp decline of credit and spending.



It's not the price of oil per se that causes a recession, it's the underlying vulnerabilities that have been cloaked with happy story narratives to keep the game going.


New Podcast: Self-Liquidating Systems, Parallel Worlds, and AI Doesn't Live In A Moral Universe (Leafbox)
Apple podcast


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)


Check out my updated Books and Films.

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

Subscribe to my Substack for free

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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, Smooth Ryda ($70), for your monumentally generous subscription to this site -- I am greatly honored by your support and readership.		Thank you, Benjamin B. ($7/month), for your marvelously generous subscription to this site -- I am greatly honored by your support and readership.

Thank you, David C. ($7/month) for your superbly generous subscription to this site -- I am greatly honored by your support and readership.

Thank you, Anthony R. ($3/month) for your most generous subscription to this site -- I am greatly honored by your support and readership.

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The Inevitability of the AI Depression

The collision of hype and euphoric hallucinations with the real world will manifest across the entire socio-economic-political-legal spectrum.

The conventional narrative views AI dominance as inevitable. What's actually inevitable is the AI Depression, the economic fallout of unrealistic but oh-so-profitable hype, malinvestment, unprecedented legal liabilities and the second-order effects of AI replacing workers while generating dysfunction in core systems.

Correspondent SValleyBoy responded to my post The AI Depression, (3/24/26) with these comments:

"Totally agree. I am not a luddite by any stretch of the imagination AND indeed have built two companies that have 2-3X the productivity of VLSI designers AND biology experts.

Most productivity TOOLS over the last 30 years have put humans in the driver seat and allowed them to create more 'stuff' faster. SW (software) to automate the design of chips allowed designers to focus on architectural and coding design rather than manually connecting lego blocks and having to change it manually every time a process change happened. They could therefore design more chips.

Railroads took workers/humans to other geographies where they could produce more things thus enabling the economy to grow. Electricity did the same, it allowed humans to work easier irrespective of the Sun being up and do more motors to help humans do things faster, same with communication devices. TV/Media arguably spawned an entertainment industry which went hand in hand with workers who were engaged in the transportation industry, making-buying cars. Railroads/Cars displaced horses/local ships.

AI-ML (machine learning)is very different because it can/will dis/replace the bottom 10-25% of knowledge focused service workers. i.e., phone support across industries. 24 million workers in the US in these industries. if you displace 1 in 4 that is 6*10**6 * 50*10**3 = 300 * 10**9 = $300 Billion of earned income gone.

AI-ML in terms of coding will enable older programmers to easily create simpler code which earlier would have been coded by newer, fresh grads without sucking the time of the experienced programmers who were working on more senior projects. It is not really getting to help the creation of more products because if Humans are the consumers of products there is some rate at which they can adopt newer products. Shorter product lives also means that there is less you can charge and less profit to make and fewer people to buy/spend.

Money going to corporations means it is now funneled to shareholders so in effect the money in circulation will drop and thats not good for the economy. More money to shareholders means less money in circulation and more misallocation of investments, more chasing of the same investment because the wealth owning class have very similar backgrounds and very tight networks.

Do a little bit more of this across other industries and you are really putting $1 Trillion in earned income that is circulating at speed out of the picture, no bueno. If you reduce the velocity of money you will reduce the economy as a multiple of the income that you are subsuming. All in all, this is not sustainable and definitely not one in which private corporations can own the AI-ML utilities that can/should be used by everyone.

These utilities should be thought of as Libraries which held the knowledge of the world and were accessible by everyone, not just people who could afford books. Imagine the world if there were no libraries and only people with money could afford to gain knowledge."

Thank you, SValleyBoy, for the insightful overview. The key takeaways here in my view are:

1. There are limits on what functions can be wholly replaced by AI.

2. SValleyBoy raises the key question few ask: should these utilities be viewed not merely as private property, i.e. shares of stocks of a tiny handful of private corporations, or should they be available to all as a library of knowledge like public libraries of books, music and video recordings?

3. The channeling of earned income from the workforce to the investor class will simply accelerate the trend of the past 50 years of income being diverted from the workforce (labor) to the investor class (capital), which is highly asymmetric in distribution, as the top 0.1% own the lion's share of this wealth and the rest is distributed in descending quantities to the top 10%.

Here we see the percentage of the economy going to labor is in a long-term slide--a slide that AI will accelerate as it replaces the lower tranche of cognitive labor employees.



Here is the distribution of net personal wealth: the top 1%'s share has skyrocketed, the top 10% (dominated by the top 0.1% and the top 1%) has gained ground while the bottom 90% has lost ground.



Here's a chart of financial assets held by the top 1% (up 42%), the next 9% (90% to 99%, down 3%) and the bottom 50% (down 28%)



Beneath the self-serving hype, the limits and perverse consequences of AI are being elucidated in studies. Consider the implications of this selection of recent papers:

Agents of Chaos
Focusing on failures emerging from the integration of language models with autonomy, tool use, and multi-party communication, we document eleven representative case studies. Observed behaviors include unauthorized compliance with non-owners, disclosure of sensitive information, execution of destructive system-level actions, denial-of-service conditions, uncontrolled resource consumption, identity spoofing vulnerabilities, cross-agent propagation of unsafe practices, and partial system takeover. In several cases, agents reported task completion while the underlying system state contradicted those reports. We also report on some of the failed attempts. Our findings establish the existence of security-, privacy-, and governance-relevant vulnerabilities in realistic deployment settings. These behaviors raise unresolved questions regarding accountability, delegated authority, and responsibility for downstream harms, and warrant urgent attention from legal scholars, policymakers, and researchers across disciplines.

AI, Human Cognition and Knowledge Collapse (economics.mit.edu)

Social media is harming adolescents at a scale large enough to cause changes at the population level

Sycophantic AI decreases prosocial intentions and promotes dependence

Who's in charge? Disempowerment patterns in real-world LLM usage

Marriage over, 100,000 down the drain: the AI users whose lives were wrecked by delusion

Artificial Intelligence, Real Misallocation

A deepfake can ruin you before breakfast: Digital forensics pioneer Hany Farid explains what it will take to rebuild trust in the deepfake era.

ARC-AGI-3: A New Challenge for Frontier Agentic Intelligence (via Tom D.)
Like its predecessors ARC-AGI-1 and 2, ARC-AGI-3 focuses entirely on evaluating fluid adaptive efficiency on novel tasks, while avoiding language and external knowledge. Our testing shows humans can solve 100% of the environments, in contrast to frontier AI systems which, as of March 2026, score below 1%.

To summarize: No AGI (Artificial General Intelligence) for you, Big Tech.

The collision of hype and euphoric hallucinations with the real world will manifest across the entire socio-economic-political-legal spectrum. All new technologies go through this cycle of extremes of hype, greed and claims of inevitability substituting for financial realities leading to a crash of extreme overvaluations.

What's different this time is our economy is larded with cognitive-labor busy-work that isn't actually productive, and this is the tranche of workers that AI can replace because this work can largely be automated as it's process-based rather than results-based. That's a critical distinction that's lost in all the hype.

What we get when we add these up--the limits of AI, extremes of hype and malinvestment, a bubble of overvaluation that bursts, extremely asymmetric distributions of wealth and income and the replacement of workers who cannot be redeployed in a shrinking economy--is a Depression, not a recession.

As I've repeatedly noted here, when tools become commoditized, their profitability vanishes, and if there's one thing that's inevitable about AI, it's the commodification of every AI utility. AI will not be profitable, it will be just another expense, one with legal liabilities that have yet to be defined.

And if we ask AI to resolve this for us, we run into the intrinsic limits of all AI models:




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