The only "reform" that changes our lives in a fundamentally positive way is radical decentralization via distributing centralized power. Presidents like to deal with the CEOs of corporate monopolies for self-evident reasons: Rather than engage in the tedious, contentious herding-of-cats in nimble, dynamic, competitive sectors, the Prez makes a deal with the monopoly CEO and the deal is imposed on everyone down the political, corporate, workplace hierarchy. Centralized power makes a coup--a forced swap of leadership--meet the new boss, same as the old boss--easy. Financial coups are easier, too, with one central bank and one cartel of "too big to fail, too big to care" banks. Centralized power offers many other Irresistible Temptations. Reformers love centralized power because if they can grab control of it, they can force-feed their glorious reforms (or profit-maximizing schemes) down everyone's throats whether they agree or not: it is against the law to complain about corporate/state monopolies controlling our lives, everyone must install a Flock camera in their bedroom, no one can criticize the Supreme Leader in private, everyone must wear approved Silly Hats in public, etc. Oops, those reforms sound like an authoritarian, totalitarian state gone mad. Yes, precisely. All centralized power arrangements end up manifesting authoritarian, totalitarian extremes of madness, because that's the only possible outcome of centralizing power: petty dictators are soon running the asylum, and loving every minute of it. The patients, not so much. We see this everywhere now, as monopolies are manifestations of centralized power. This is why I call the status quo Privatized Totalitarianism as privately owned and operated monopolies / cartels have the same headlock on us as state monopolies, and the two work together, as this serves the interests of both: you make the Silly Hats, and we mandate their use, and penalize anyone attempting to modify your software, app, device or Silly Hat to evade your monopoly chokehold. We both get rich exploiting the powerless peasantry, so what's not to like? Politics now boils down to a Silly Hats slugfest over who gets control of the Privatized Totalitarianism casino. The only meaningful reform is to decentralize power by demolishing every monopoly and cartel and banning the aggregation of power. But what about "efficiency"? Yes, Privatized Totalitarianism is very "efficient"-- efficient at extraction, exploitation, surveillance, repression, propaganda, PR and social control mechanisms. If the public can "vote with their feet" by moving to a different physical location but they're still living in the same cartel-monopoly economy wherever they move, their "liberty" is illusory. It's like changing cabins in the gulag: maybe this hut has fewer leaks and fewer fleas, but it's still in the gulag. Just as what we're losing by using AI is invisible because we've lost the capacity to even see what's been lost, we've lost the capacity to see the systemic decay of the quality of our lives in the invisible gulag of Privatized Totalitarianism. So even as we thrill to some new novelty or tiny discount, we've lost the capacity to see what's been lost in the slow destruction of decentralized, competitive dynamism in favor of the profit-maximizing, sclerotic gulag we're all trapped in without even being aware that we're trapped, for the key to maintaining the kingdom is to foster the illusions of choice, liberty and competition while distracting us with ceaseless hype about new technologies, novelties and meaningless discounts as "competition" and "choice." It's like looking at a row of different brand products and then reading the fine print to discover that they're all owned by the same corporation. That's Privatized Totalitarianism, well cloaked behind carefully maintained illusions of choice, liberty and competition. And if you protest, it might get worse: "I am altering the deal, pray I don't alter it any further." The only "reform" that changes our lives in a fundamentally positive way is radical decentralization via distributing centralized power. Everything else is just changing huts in the gulag and being delighted with the steady stream of absurd parodies of novelty: "New gruel, new taste, now with micro-plastics!" New podcast: Charles Hugh Smith on the End Game of Repressed Interest Rates: Stagflationary Inflation followed by "Cold Turkey" (29:25 min) New collection of five intriguing stories: Jumble Bin Stories (Kindle $6, print $12) read samples for free (PDF) My book Investing In Revolution is available ($18 for the paperback, $24 for the hardcover and $8.95 for the ebook edition). Introduction (free) 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, Frank M. 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Our naivete is being exploited so ruthlessly and with such abandon that the golden age of the Big Con is consuming itself. Naivete is interesting because it's so easily confused with confidence, native optimism, youthful enthusiasm, and a host of delusions, including mistaking idealized fantasies and fairy tales as templates for the real world. In a culture that prides itself on not being a chump, to be called naive is an accusation: don't be naive means don't be an easily conned chump. In contrast, being confident, optimistic and filled with youthful enthusiasm are praised as the core of American Practicality, Idealism and Vigor, i.e. the can-do spirit. That naivete lends itself to youthful enthusiasm, sunny optimism and can-do confidence is rarely remarked upon. So what is naivete other than credulity? It's a willingness to trust leaders, institutions and mythologies without running them through common-sensically skeptical filters, and a belief that everything will work out just fine regardless of what happens if we just keep working hard and working smart. The difference between a willingness to trust leaders, institutions and mythologies, sunny optimism and youthful enthusiasm and naively mistaking self-serving fantasies and fairy tales for the real world is, well, there isn't any. Believing that an unending stream of patently transparent self-serving fairy tales accurately reflect "the real world" is the pinnacle of naivete, and that describes the entire American society, culture and economy: this is the golden age of the Big Con. Which brings us to Herman Melville's under-appreciated classic, The Confidence-Man. Why read a book from 1857 which flopped so badly as commercial literature that Melville stopped writing and ended his career as a customs official? Because this book masterfully explores the entire nature of trust, confidence and cons. Though the setting is a riverboat on the Mississippi River just before the U.S. exploded into Civil War, its insights cross cultural boundaries. This is not an easy book to read for several reasons. First, it is undoubtedly one of the first "post-modern" novels which breaks from traditional narrative storytelling. ( Another example: Dostoevsky's Notes From the Underground.) The Confidence-Man is a collection of 45 conversations between various people on the riverboat--beggars, absurdly dressed frontiersmen, sickly misers, shysters, patent medicine hucksters, veterans (of the Mexican-American War) and the "hero" in the latter part of the book, the Cosmopolitan. In typical Melville fashion, you also get asides--directly to the reader, in several cases, as if Melville felt the need to address issues of fiction outside the actual form of his novel. The lack of structure, action and conclusion make this a post-modern type book, but if you read each conversation as a separate story, then it starts to make more sense. For what ties the book together is not a story but a theme: the nature of trust and confidence. In a very sly way, Melville shows how a variety of cons are worked, as the absolutely distrustful are slowly but surely convinced to do exactly what they vowed not to do: buy the "herbal" patent medicine, buy shares in a bogus stock venture, or donate cash to a suspect "charity." In other chapters, it seems like the con artist is either stopped in his tracks or is conned himself. Since the book is mostly conversations, we are left to our own conclusions; there is no authorial voice wrapping up each chapter with a neatly stated ending. This elliptical structure conveys the ambiguous nature of trust; we don't want to be taken, but confidence is also necessary for any business to be transacted. To trust no one is to be entirely isolated. Melville also raises the question: is it always a bad thing to be conned? The sickly man seems to be improved by his purchase of the worthless herbal remedy, and the donor conned out of his cash for the bogus charity also seems to feel better about himself and life. The ornery frontiersman who's been conned by lazy helpers softens up enough to trust the smooth-talking employment agency owner. Is that a terrible thing, to trust despite a history of being burned? The ambiguous nature of the bonds of trust is also explored. We think the Cosmopolitan is a con-man, but when he convinces a fellow passenger to part with a heavy sum, he returns it, just to prove a point. Is that a continuance of the con, or is he actually trustworthy? The book is also an exploration of a peculiarly American task: sorting out who to trust in a multicultural non-traditional society of highly diverse and highly mobile citizens. In a traditional society, things operate in rote ways; young people follow in their parents' traditional roles, money is made and lent according to unchanging standards, and faith/tradition guides transactions such as marriage and business along well-worn pathways. But in America, none of this structure is available. Even in Melville's day, America was a polyglot culture on the move; you had to decide who to trust based on their dress, manner and speech/pitch. The con, of course, works on precisely this necessity to rely on one's senses and rationality rather than a traditional network of trusted people and methods. So the con man dresses well and has a good story, and an answer for every doubt. Our naivete is being exploited so ruthlessly and with such abandon that the golden age of the Big Con is consuming itself. Delusions are now the norm, as if our unhinged optimism that everything will turn out just fine as long as we believe in Technology and Finance, for that will be enough to stem the tsunami of consequences building up beneath the surface euphoria of stocks and AI making us all wealthy beyond measure. These are the joys of naivete. The tragedies are still over the horizon, a gathering storm we are unprepared for. NEW PODCAST: We Don't Have Capitalism Anymore--We Have Privatized Totalitarianism (60 minutes)(host Daniel H.) 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, Joe S. 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The possibility that AI will end up unleashing waves of 'Anti-Progress'--malicious uses, untrustworthy output and uncontrollable floods of slop--also doesn't occur to those confined in the current belief construct. A funny thing happens on the way to understanding risk: we discover it's tricky. We think we see all the risks, and think we can mitigate or hedge those risks, but by its very nature, risk evades such simplistic filters and metrics. Risk remains hidden, offscreen, invisible, building up out of sight, awaiting a catalyst that's equally undetectable until it manifests, and after the fact, we look back and ask, why didn't we see that coming? Risk is tricky like that. It can lay dormant for decades and then erupt with little warning. Risk is tricky in other ways. In our hubris, we see the power and might of our technologies, systems and foresight, and reckon these are so robust they will easily survive any tectonic shift, as we've planned for emergencies. But our faith in the might of our civilization is itself a source of risk because the risk of Model Collapse--the breakdown not of a supply chain or technology but of our entire conceptual construct of how the world works--goes unrecognized because our confidence that our model maps the real world is so high that we are incapable of recognizing its drift into hallucination and civilizational psychosis. In other words, our confidence that our conceptual mythologies are accurately mapping the real world is itself a source of civilizational risk because this confidence makes it inevitable that we do more of what's failing, as the alternative--recognizing our conceptual models and mythologies are self-serving rationalizations that substitute artifice for realistic appraisals--is conceptually and emotionally impossible. Put another way: Emperor Norton's delusions of power and grandeur were harmless as long as he was recognized as delusional. But should Emperor Norton actually be given the power he believed was his to wield, then risk rises accordingly. Consider the bet being made globally that the current iteration of AI will be 1) immensely profitable (the most important thing in the Universe) and 2) immensely productive (secondary to immensely profitable but necessary as a motivation for everyone to throw trillions of dollars at purveyors of AI). The risk that this bet--and the assumptions that make it not only rational but pressing--is the equivalent of handing Emperor Norton the keys to the kingdom with little evidence he will be a wise leader, is unimaginable in the current model / mythology, and so therefore it doesn't exist. The worst that could possibly happen in the current model / mythology is a brief spot of bother in the stock market as euphoric overvaluations come down to Earth, and then the immense profits start flowing and markets rocket higher in a multi-decade Bull Market of AI Productivity. The possibility that the current iteration of AI is innately incapable of metaphorically boiling away the seas is not on the screen, any more than a stock market crash or social upheaval is on the screen. Yet if the fantasy of vast, unstoppable floods of profits driven by vast increases in productivity fail to materialize on a very short timeline, then both a stock market crash and social upheaval move from "impossible" straight through "unlikely" to "happening now," leaving everyone who thought they understood risk and were properly hedged against unwelcome change in a state of disbelief and wonderment. Risk is tricky that way. What's "impossible" in our current belief construct--a construct we mistakenly believe maps the real world perfectly--is a source of system-breaking risk that is invisible within the confines of this self-congratulatory belief construct. The possibility that AI will end up unleashing waves of Anti-Progress--malicious uses, untrustworthy output and uncontrollable floods of slop--also doesn't occur to those confined in the current belief construct. The risk may be of a magnitude and scale that switching AI vendors or platforms and approving policy tweaks won't fix the problem. 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. 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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. Go to my main site at www.oftwominds.com/blog.html for the full posts and archives.

Only then do we realize that by optimizing profit and efficiency, we've also optimized systemic failure. In my essay AI, Money, Human Nature and the Problem with Problems, I refer to boundary conditions but didn't offer a thorough explanation of the role this concept plays in understanding not just how the world works but more importantly, how things break down. Boundary conditions define what the system needs to function. The more complex the machine / system, the greater the number of conditions. For example, a car needs a source of power, fuel, tires, control mechanisms, seats, and so on--hundreds of components are required for the car to function optimally. Some boundary conditions are narrow--there's little or no wiggle-room in what the system needs to function. Everything has to function perfectly or the system breaks down. We can call these tight systems as there's very little leeway in what they need to function. In contrast, loose systems have boundary conditions with leeway: some components can fail or function poorly and the system will degrade--i.e. not operate optimally--but it will still function. Consider a tire. A tire is a fairly loose system. If the optimal tire pressure is 32 pounds, the tire will still function if pressure falls to 28 or is overinflated to 34 pounds. Now imagine a tire that fails if pressure exceeds 32.5 pounds or falls below 31.5 pounds. Those are unforgiving, tight boundary conditions with very little wiggle room. If tire pressure declines even slightly, it fails. Which tire do you want--the one optimized for price/efficiency or the one with looser boundary conditions? Our entire way of life is dominated by systems optimized for price/efficiency, not survivability when the system veers outside its boundary conditions. If a critical semiconductor chip fails in a modern vehicle, the vehicle breaks down and ceases to function. The chip controlled an essential subsystem, and once the chip failed, the subsystem failed, and the vehicle rolls to a stop: complete breakdown. Certain characteristics of systems create tight boundary conditions that we don't see until they break down. During the pandemic in the early 2020s, the supply chain of some semiconductors broke down, and as a result the production of cars and trucks that needed those chips broke down. Supply chains with single-source suppliers within long dependency chains (this part needs this part which needs this part) have exacting boundary conditions: since the supply chain depends on a single source for a critical part, if that supplier is disrupted, the entire chain breaks down. Since the economy is optimized to maximize profit, it's maximized for efficiencies which demand tight boundary conditions and lengthy dependency chains: the system only works if every component works perfectly and every condition is met. Centralization generates tight boundary conditions. Consider a mega-farm growing a single crop--a mono-crop that the region depends on. This centralized mega-system is optimized to maximize yield of a single crop via optimized subsystems: specific seeds, fertilizers, mechanized equipment, soil sensors, irrigation, harvesting and transport, and at the end, a market price for the crop that covers all the costs and yields a profit. Financially, this is an optimized system. In the real world, it is a system prone to failure due to its tight boundary conditions. A pest or plague that evades the genetically modified seeds' defenses can wipe out the crop, a sudden bout of extreme weather at the wrong time can wipe out the harvest, and a drop in the market value of the crop can make it unprofitable to even harvest, so it's left to rot or plowed under. Contrast this with a system of 100 independent, decentralized farms. Financially, this system is inefficient and not optimized to maximize profit, so it's anathema in a financial system that demands optimizing everything to optimize profits. Some of the farms will grow crops with low profit margins or non-optimal yields, and some will be inefficient due to raising a variety of crops instead of one financially optimized crop. When the pest, plague or price collapse wipes out the mega-farm, the system of 100 farms growing a variety of crops continues to function, albeit at a reduced yield as some farms will suffer lower yields and incomes while many will be unaffected. When a centralized system / mono-crop fails, everyone depending on that system / mono-crop starves. Once the system veered outside the boundary conditions, it broke down. Here's a graphic illustrating tight and loose boundary conditions: Analog - physical systems tend to be more forgiving than digital-dependent systems. When a bracket on a home appliance breaks, it's typically possible to substitute a non-optimized part to fix it. In other words, the manufacturer's bracket is nice to have but not essential, as some other piece of metal can be worked to serve the same function. When the digital motherboard on the modern appliance fails, there is no replacement except that exact board. Some other mix of semiconductors and circuitry can't be substituted. The appliance--or vehicle, digital device, etc.--is now a brick. And if that one component is no longer available, the appliance is unrepairable. In an old analog auto engine, if one of the four cylinders was no longer functioning optimally--the gasket was leaking, valves clogged, etc.--the engine would still function, albeit generating lower horsepower and dirtier exhaust. The majority of systems we rely on for life's essentials--water, power, food, transport, banking, healthcare, etc.--are now digitally dependent systems with tight boundary conditions. They work perfectly until some critical component in a dependency chain fails, and then the entire system fails. There are no replacements or substitutes for what failed, and so the entire system ceases to function. All the features of systems that optimize efficiency and profits tighten boundary conditions. Everything that widens boundary conditions--i.e. everything that increases survivability and flexibility--increases costs and reduces profits and optimization of efficiency: redundancy, warehousing of spare parts, constant training of personnel to deal with unlikely emergencies, etc. The vulnerabilities of our optimized way of life are hidden until systems veer outside their boundary conditions and break down. We've witnessed many such breakdowns as every system is optimized for efficiency and profit by stripping out redundancies, second suppliers, spare parts, analog backups in favor of digital efficiencies, etc. This is why we're surprised--and helpless--when they break down. We think they're robust because they work so well within their boundary conditions, but the narrowness of their boundary conditions makes them extremely sensitive to failures in critical components. This fragility is invisible until the system breaks down. Only then do we realize that by optimizing profit and efficiency, we've also optimized systemic failure. Go ahead and hold control-alt-delete, but the system won't reboot or repair itself, for it's been optimized to break down. 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 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, Simons C. ($32.40), for your wondrously generous subscription to this site -- I am greatly honored by your support and readership.   Thank you, Ferrema S. ($7/month), for your marvelously generous subscription to this site -- I am greatly honored by your support and readership. Thank you, Scott T. ($300) for your beyond-outrageously generous subscription to this site -- I am greatly honored by your support and readership.   Thank you, Don A. ($70) for your enormously generous subscription to this site -- I am greatly honored by your support and readership. Go to my main site at www.oftwominds.com/blog.html for the full posts and archives.