AI, indulgences, and the false promise of salvation

on (some of) the moral externalities in the AI economy

Welcome to The Tech Bubble. This week, another addition to the artificial intelligence series (this time playing around with Martin Luther’s criticisms of indulgences to revisit earlier arguments about AI)

My series of essays on Artificial Intelligence thus far:

• AI, life engineering, and digital hygiene - On artificial intelligence as an attack vector for eugenics & political shock therapy.

• AI, slavery, surveillance, and capitalism - On artificial intelligence for The Labor Question & the limits of surveillance capitalism and techno-feudalism.

• The Silicon Valley Consensus & AI Capex (Part 1) - On overbuilding AI infrastructure and its energy supply.

Today’s is are also a few other essays on AI that you could probably fit in there:

• Does OpenAI’s latest marketing stunt matter? - On distractions, intentions, aesthetics, and fascism.

• The phony comforts of useful idiots - On Casey Newton and the shallowness of (AI) anti-skepticism.

• Trapped in the Maw of a Stillborn God - On Vegas as a laboratory for surveillance and social control, the explosion of gambling as a sign of a degenerate culture seized by despair, AI delusions at CES, and the future.

If these essays sound interesting, consider supporting The Tech Bubble (me) with a subscription ($7 a month or $70 a year). If you're already supporting me, let me kiss that big ass cranium of yours expeditiously.

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Mondkönig by Adam Burke (nightjar), 2022

Today’s essay is about artificial intelligence (surprise), using debates about AI, some relevant news items, some reflections on real use cases, its various material and spiritual impacts, and the general degradation of our world.

Looking for an illustration to pair with the essay, Burke’s called to me from the recesses of one of my drives—it projects corrupted strength, the intervention of/observation by alien forces, evidence of violence and the promise of it, and it also just looks cool as hell. I did a reverse image search to try and credit the illustrator (and remember how I came across it), which turned up a few things. One was a May 2024 quote tweet of mine where I simply posted the picture. Another was a New Noise Magazine interview with a Cleveland, Ohio heavy metal core band called Walking Wounded that used this painting for their debut EP, Bestial Condemnation and captured better than I initially did why the picture was perfect:

“Bestial Condemnation is a fantasy story about an aging knight who makes a deal with an ancient deity to restore his former strength,” begins guitarist Steve Perrino, “However, his newfound strength comes at the price of his humanity as he gradually devolves into something pre-human and violent.” Here’s a fitting central lyrical theme if there ever was one, given the quartet’s barbaric style.

“I think many of us wish we were stronger in a wide variety of ways, whether it’s physically, mentally, or emotionally,” he continues. “I wanted to write something that asks the listener, ‘How far would you go to be the person you think you should be? What price would you pay? Will it be worth it?”

As I’ve been trying to argue in this series, it’s difficult to talk about why one might be opposed to how artificial intelligence is being designed, developed, financed, and deployed without bringing in a multitude of threads:

• the reactionary dream of prominent tech sector investors, entrepreneurs, thought leaders, and boosters to inoculate capitalism (and technological innovation) from democracy and liberalism

• the accelerationist death cult of techno-optimists who believe the creation of a sufficiently advanced artificial intelligence will roll back whatever damage its pursuit wrecks on our ecological niche, culture, economy, political order, mental health, and so on

• the origins of computation tracing back to the British empire’s hope of making industrial labor resemble plantation labor after the abolition of slavery, the extent to which reactionaries are eager to use these technologies to re-legitimize various hierarchies and forms of social control

• our tech sector’s persistently lucrative strategy: overbuilding, overvaluing, and overinvesting in various assets in hopes of realizing excessive gains, translating those into political power, and undertaking the task of restructuring society in their desired image.

It does not help that these concerns not only converge on artificial intelligence, but on a great deal of tech products foisted upon us by Silicon Valley leading up to it—namely those littering the so-called sharing economy, gig economy, metaverse, web3, and cryptoeconomy. Trillions of dollars have flowed to Wall Street and Silicon Valley to push out products seemingly designed to do nothing more than hurt as many people as possible while enriching as few as possible: sleek weapons for militaries and police forces, ubiquitous surveillance systems, vaporware, poorly designed Ponzi schemes, and elaborate conspiracies for printing out lottery tickets for distribution among a narrow group of bloodthirsty, skull-measuring, anti-social libertarians.

As Evgeny Morozov noted in 2019—more than a decade since the start of the great financial crisis—capitalists remain uneasy:

Once-alluring promises of meritocracy and social mobility ring increasingly hollow. They pine for a slicker, PowerPoint-friendly legitimation narrative—hard to concoct against a background of rising inequality, pervasive tax evasion and troubling omens about the true state of the post-crash global economy, were central bankers to withdraw their overextended support. What real-world developments could underpin such a narrative? What theme could make the idea of capitalism more morally acceptable to the latest batch of Ivy League graduates, who may risk getting drawn to notions like eco-socialism? Despite the growing ‘tech-lash’ against the FAANGS, capitalist thinkers still look to Silicon Valley and its culture with a glimmer of hope. For all its problems, the Valley remains a powerful laboratory of new—perhaps, better—market solutions. No other sector occupies such a prominent role on the horizon of the Western capitalist imaginary or offers such a promising field for regenerative mythologies.

Those words are no less true six years later—in fact, after the end of the ZIRP era it’s hard to understand the ongoing tech asset bubble, and the role it’s playing in promulgating artificial intelligence, without appreciating the legitimacy crisis plaguing capitalism.

It feels increasingly obvious that almost everything will be sacrificed to preserve the status quo, that we will be forced on an impossible path—giving birth to a superhuman artificial intelligence in hopes of improving our work lives, social lives, economies, politics, health, intelligence, and culture. Getting there just happens to require prioritizing the private financing, development, and deployment of relevant technologies, as well as giving increasingly more political and economic power to firms and entrepreneurs and financiers responsible for sabotaging our environment, social relations, politics, culture, and economy.

What will the cost end up being at the end of the day?

AI == INDULGENCE

The general thrust here is that modern AI hype cycles have a religious texture to them: one layer resembles the grounds on which Martin Luther criticized the abuse of indulgences in the 95 Theses he pinned to a church door in 1517, another resembles the folk-ritual of sin-eating—where a meal (sometimes resting on a corpse) was consumed to essentially absolve the recently deceased of their sins. The former will be the focus of this essay.

Indulgences in the Medieval Era

Medieval Church doctrine held there was an eternal and temporal dimension to sin: the former could be forgiven by confession and genuine repentance, but the later persisted and carried consequences in this life and the next (in Purgatory). Additional acts of penance (prayer, fasting, charity, good works, etc.) were required then to remit temporal punishment.

Enter indulgences: think of them as a credit or certificate given after an act of penance, representing a commuting of the debt incurred by sin and a reduction of future time in Purgatory. The Church began selling indulgences—promising that the monetary exchange was equivalent to penance, and then issuing excessive indulgences to raise funds for, well, anything they could. Here is an illuminating section from God's Bankers, Gerald Posner's exhaustive history of the Vatican's finances:

The early church's penances were often severe, including flogging, imprisonment, or even death. Although some indulgences were free, the best ones—promising the most redemption for the gravest sins—were expensive. The Vatican set prices according to the severity of the sin and they were initially available only to those who made a pilgrimage to Rome.

Indulgences helped Urban II in the eleventh century offset the church's enormous costs in subsidizing the first Crusades. He offered full absolution to anyone who volunteered to fight in 'God's army' and partial forgiveness for simply helping the Crusaders. Successive Popes became ever more creative in liberalizing the scope of indulgences and the ease with which devout Catholics could pay for them. By the early 1400s, Boniface IX—whose decadent spending kept the church under relentless financial pressure—extended indulgences to encompass sacraments, ordinations, and consecrations. A few decades later, Pope Paul II waived the need for sinners to make a pilgrimage to Rome. He authorized local bishops to collect the money and dispense the indulgences and also cleared them for sale at pilgrimage sites that had relics of saints. Sextus IV had an inspired idea: apply them to souls stuck in Purgatory. Any Catholic could pay so that souls trapped in Purgatory could get on a fast track to Heaven. The assurance that money alone could cut the afterlife in Purgatory was such a powerful inducement that many families sent their life savings to Rome. So much money flooded to Sextus that he was able to build the Sistine Chapel. Alexander VI—the Spanish Borgia whose Papacy was marked by nepotism and brutal infighting for power—created an indulgence for simply reciting the Rosary in public. The new sales pitch promised the faithful that a generous contribution multiplied the Rosary's prayer power.

Each Pontiff understood that tax revenues from the Papal States paid most of the day-to-day bills, while indulgences paid for everything else. The church overlooked the widespread corruption and graft inherent in collecting so much cash and instead grew ever more dependent on indulgences. And as they got ever easier to buy and promised more forgiveness, they became wildly popular among ordinary Catholics.

Indulgences were, however, more than a financial lifeline. They also helped medieval Roman Popes withstand challenges to their secular power. So-called antipopes—usually from other Italian cities—claimed they, rather than the pope elected in Rome, had the political or divine right to rule the Catholic Church. Although some antipopes raised their own armies and had popular backing, they never mustered the moral authority to issue indulgences. Repeated efforts over centuries by pretenders to the Papacy to package and sell forgiveness for sins failed. Few Catholics believed that anyone but the Roman Pope had the direct connection with God to offer a real Indulgence. And when the Pope's armies were called upon to sometimes crush an antipope, it was usually the flood of cash from indulgences that paid for the war.

Pope Leo X (1513-21), a Medici prince who'd been a wealthy and powerful cardinal since the age of 13, wasted no time bringing over his lavish lifestyle to the Papal Court when he ascended at 38. As Posner points out: Leo commissioned major artists for extravagant projects decorating Vatican estates, the Vatican's servants "nearly doubled to seven hundred," cardinals were soon called "Princes of the Church," and critics of his abuse of indulgences were threatened with excommunication.

Hoping to subsidize the cost of constructing St. Peter’s Basilica, Leo X issued a bull of plenary indulgence in 1515: the temporal punishment for almost any sin could now be remitted in exchange for money, and for the next 8 years all other indulgence promotion was to cease. For 8 years, this one indulgence could put you on the fast track to Heaven! Or as Luther claimed on Dominican friar, Johann Terzl, said: "“As soon as the coin in the coffer rings, the soul from purgatory springs.”

There are a few key areas of Luther’s critique that I’ll hone in and map onto artificial intelligence and we’ll develop them more in the next section:

1. Salvation through transaction. Indulgences shouldn’t be presented as a shortcut to salvation you can take instead of faith in God, genuine repentance, or good works motivated by the previous two. Luther's Theses don't oppose indulgences so much as the idea that the living (specifically the Papacy) can know whether sin can be remitted, especially when this remission is via a financial transaction and not a good work or genuine repentance.

   1. “That power which the pope has in general over purgatory corresponds to the power which any bishop or curate has in a particular way in his own diocese and parish. The pope does very well when he grants remission to souls in purgatory, not by the power of the keys, which he does not have, but by way of intercession for them.” (Theses 25-26)

2. Centralizing and codifying unjustified power. To suggest indulgences could be granted to the living on behalf of souls in Purgatory represented a massive overreach on the part of the Church, which was now suggesting it had authority over Purgatory. Introducing a commercial dimension to indulgences added perverse incentives that distorted the Church's mission and prioritized a host of needs which had nothing to do with Christendom.

   1. “They preach only human doctrines who say that as soon as the money clinks into the money chest, the soul flies out of purgatory. It is certain that when money clinks in the money chest, greed and avarice can be increased; but when the church intercedes, the result is in the hands of God alone.” (Theses 27-28)

Indulgences in the Modern Era

One place to start is with “solutionism” which was first proposed by Morozov as the zealous belief that the application of technology can solve humanity's problems given the right algorithm, product, or private-public partnership. The degree to which various technologies cause disruption is the degree to which we are working through the inefficiency of its uneven adoption, a stratagem that conveniently reinforces the urgency of pursuing political programs prioritizing the uncritical adoption of new products, business models, asset classes, and regulatory frameworks (i.e. on-demand platforms, fintech, crypto, web3, metaverse, artificial intelligence). As Morozov puts it in “To Save Everything, Click Here”:

Recasting all complex social situations either as neatly defined problems with definite, computable solutions or as transparent and self-evident processes that can be easily optimized—if only the right algorithms are in place!—this quest is likely to have unexpected consequences that could eventually cause more damage than the problems they seek to address.

On a basic level, the drive to push for universal fixes through the application of breakthrough technologies may be offered as a shortcut that bypasses the onerous hard work of enacting structural reforms, imposing ethical limitations, or adopting restrictive regulations that trade endless growth or progress for intentional development. It insists social problems are just market opportunities waiting for a bold entrepreneur. Public goods and services are mismanaged assets that should be made private, expediently.

Over the years, Morozov’s articulation of solutionism has evolved along with the focus of his analysis. In a 2023 New York Times op-ed, Morozov warned that solutionism had re-emerged as "digital neoliberalism" and was finding even more zealous adherents thanks to the invocation of artificial general intelligence, or A.G.I. This technology, its boosters hold, is inevitable, will likely be beneficial, and is really the only way to solve humanity's problems.

Unbeknown to its proponents, A.G.I.-ism is just a bastard child of a much grander ideology, one preaching that, as Margaret Thatcher memorably put it, there is no alternative, not to the market.

Rather than breaking capitalism, as Mr. Altman has hinted it could do, A.G.I. — or at least the rush to build it — is more likely to create a powerful (and much hipper) ally for capitalism’s most destructive creed: neoliberalism.

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[N]eoliberalism is far from dead. Worse, it has found an ally in A.G.I.-ism, which stands to reinforce and replicate its main biases: that private actors outperform public ones (the market bias), that adapting to reality beats transforming it (the adaptation bias) and that efficiency trumps social concerns (the efficiency bias).

These biases turn the alluring promise behind A.G.I. on its head: Instead of saving the world, the quest to build it will make things only worse.

The market bias compels two phases in any technology rollout, but especially A.G.I.'s: a first phase where heavily subsidized services offered, then a second where prices are hiked and "overdependent users and agencies" are bled dry to make the venture generate profits (and reshape consumer behavior, regulatory frameworks, market dynamics, and political orders into forms more hospitable to profits and rents)

This plank can be understood as vulgar solutionism, which was on full display with the wave of frothy Silicon Valley startups that thrived during the zero-interest rate period, but has now been supercharged with the rise of the A.G.I.-ism cult. As Ed Zitron has spent newsletter after newsletter after newsletter detailing, there is a fundamental profitability issue at the heart of the generative AI business model—which is the sector actively pursuing A.G.I. Firms that have yet to turn a profit are burning through tens of billions, interested in raising hundreds of billions, and forecasting they will need trillions—who is going to fork up all that cash? Well, you (and me):

Thus, the ugly retrenchment phase, with aggressive price hikes to make an A.G.I. service profitable, might arrive before “abundance” and “flourishing.” But how many public institutions would mistake fickle markets for affordable technologies and become dependent on OpenAI’s expensive offerings by then?

And if you dislike your town outsourcing public transportation to a fragile start-up, would you want it farming out welfare services, waste management and public safety to the possibly even more volatile A.G.I. firms?

Then there's the adaptation bias, the idea that technological fixes can make us more self-reliant and resilient. Technology is not here to fix your city’s ailing infrastructure or to improve its social programs, but it can help you navigate their perpetual decline and evisceration!

The message is clear: gear up, enhance your human capital and chart your course like a start-up. And A.G.I.-ism echoes this tune. Bill Gates has trumpeted that A.I. can “help people everywhere improve their lives.”

The solutionist feast is only getting started: Whether it’s fighting the next pandemic, the loneliness epidemic or inflation, A.I. is already pitched as an all-purpose hammer for many real and imaginary nails. However, the decade lost to the solutionist folly reveals the limits of such technological fixes.

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There’s a difference between nudging us to follow our walking routines — a solution that favors individual adaptation — and understanding why our towns have no public spaces to walk on — a prerequisite for a politics-friendly solution that favors collective and institutional transformation.

But A.G.I.-ism, like neoliberalism, sees public institutions as unimaginative and not particularly productive. They should just adapt to A.G.I., at least according to Mr. Altman, who recently said he was nervous about “the speed with which our institutions can adapt” — part of the reason, he added, “of why we want to start deploying these systems really early, while they’re really weak, so that people have as much time as possible to do this.”

This brings us to the effiency bias, or the idea that complexity (i.e. morality, social good, justice, etc.) gets in the way of optimal market outcomes.

This fixation on efficiency is how we arrived at “solving” climate change by letting the worst offenders continue as before. The way to avoid the shackles of regulation is to devise a scheme — in this case, taxing carbon — that lets polluters buy credits to match the extra carbon they emit.

This culture of efficiency, in which markets measure the worth of things and substitute for justice, inevitably corrodes civic virtues.

And the problems this creates are visible everywhere. Academics fret that, under neoliberalism, research and teaching have become commodities. Doctors lament that hospitals prioritize more profitable services such as elective surgery over emergency care. Journalists hate that the worth of their articles is measured in eyeballs.

Now imagine unleashing A.G.I. on these esteemed institutions — the university, the hospital, the newspaper — with the noble mission of “fixing” them. Their implicit civic missions would remain invisible to A.G.I., for those missions are rarely quantified even in their annual reports — the sort of materials that go into training the models behind A.G.I.

After all, who likes to boast that his class on Renaissance history got only a handful of students? Or that her article on corruption in some faraway land got only a dozen page views? Inefficient and unprofitable, such outliers miraculously survive even in the current system. The rest of the institution quietly subsidizes them, prioritizing values other than profit-driven “efficiency.”

In defense of A.G.I. and the fundraising various firms have undertaken to realize it (or to finally see a return, whether or not A.G.I. ever happens), this ideology’s zealots have constructed a variety of artifices that obscure the real costs of their activity as well as the extent to which it’s solely self-interested and far removed from anything resembling the public interest.

As I’ve laid out before, Silicon Valley’s race to build as many data centers as possible (AI capital expenditures, or AI capex) necessitates that the sector and its financiers overbuild, overvalue, and overinvest in compute and energy infrastructure.

AI infrastructure is downstream of cloud compute infrastructure, which is dominated by a few monopolistic firms that embrace deeply exploitative business practices to leverage “hyperscale” to extract rents, steal ideas, deter competitors, trap clients, and enter new-markets with built-in advantages. This infrastructure is overbuilt, overvalued, and overinvested in because of the opportunity to create a new market that resembles cloud’s ability to deliver rents, generate anti-competitive market intelligence, and realize juicy profit margins—to realize levels of growth and profit only possible when a market is rigged.

When it comes to energy infrastructure, there are a few concerns that emerge. First and foremost is that the fossil fuel industry wants to power AI infrastructure and be powered by it. Major tech firms have made it clear that they view sustainability commitments as limitations and fossil fuel firms are scrambling to help them curtail them. To this end, AI firms have committed to worsening the climate crisis by selling tools that boost fossil fuel extraction, exponentially build out energy-intensive compute, and give fossil fuel firms alongside utilities new excuses to overbuild infrastructure that will be subsidized by ratepayers (you and me).

The ways in which compute and energy infrastructure overbuilding, overvaluation, and overinvesting are rationalized, then, are what we should be worried about. I’m going to quote Zitron at length for a bit since he’s been great on the costs, externalities, illusions, and delusions at play here.

In July 2024, Zitron raises a few questions about the mechanism by which OpenAI’s valuation

As part of this deal, Microsoft has effectively purchased the rights to OpenAI's "pre-AGI" technology, and licensed all of its technology in a way that extends past any partnership or, I imagine, future deals. Microsoft also "invested" in cloud credits at an indeterminate valuation, both in how OpenAI was valued and the credits themselves.

Ask yourself, what is a dollar of "cloud compute credits," and what do they gain you access to? Microsoft's Azure cloud has many, many products, and it's unclear if OpenAI would receive preferential pricing on them, what products they'd be using, and the terms under which OpenAI receives them. Microsoft effectively created its own currency to invest in OpenAI, which OpenAI would then pay Microsoft in, which Microsoft would, in turn, receive as revenue.

In September, he expresses concern that the issue is not just OpenAI's valuation, but a "subprime AI crisis" borne out of countless companies integrating generative AI priced at unsustainably low prices. (Recall Morozov’s argument that the A.G.I. cult, succumbing to neoliberalism's market bias, would roll out their products in two phases: heavy subsidies to undercut competition and cultivate user dependency, then price hikes to extract rents, generate first profits, and reshape users/markets/regulatory regimes/governance to be a more pliant (profitable) host body.)

Back to Zitron and the subprime AI crisis:

Almost every "AI-powered" startup that uses LLM features is based on some combination of GPT or Claude. These models are built by two companies that are deeply unprofitable (Anthropic is on course to lose $2.7 billion this year), and that have pricing designed to get more customers rather than make any kind of profit. OpenAI, as mentioned, is subsidized by Microsoft — both in the "cloud credits" it received and the preferential pricing Microsoft offers — and its pricing is entirely dependent on Microsoft's continued support, both as an investor and a services provider, a problem that Anthropic faces with its deals with Amazon and Google.

Based on how unprofitable they are, I hypothesize that if OpenAI or Anthropic charged prices closer to their actual costs, there would be a ten-to-a-hundred-times increase in the price of API calls, though it's impossible to say how much without the actual numbers. However, let's consider for a fact that the numbers reported by The Information estimate that OpenAI's server costs with Microsoft will be $4 billion in 2024 — which, I add, are over two-and-a-half-times cheaper than what Microsoft charges others — and then consider that OpenAI still loses over five billion dollars a year.

OpenAI is more than likely charging only a small percentage of what it likely costs to run its models, and can only continue to do so if it is able to continually raise more venture funding than has ever been raised and continue to receive preferential pricing from Microsoft, a company that recently mentioned that it considers OpenAI a competitor. While I can't say for certain, I would think it's reasonable to believe that Anthropic receives similarly-preferential pricing from both Amazon Web Services and Google Cloud.

Assuming that Microsoft gave OpenAI $10 billion of cloud credits, and it spent $4 billion on server costs and, let's say, $2 billion on training — costs that are both sure to increase with the new o1 and “Orion” models — OpenAI will either need more credits or will have to start paying actual cash to Microsoft sometime in 2025.

Later that month, Zitron wrote about another potential red flag in the tech sector, cloud compute—specifically, the centrality of “software as a service service” (“SaaS”) to the business models of multiple tech companies, the stagnating growth of a business unit that usually prints money for firms, and the desperation which has driven these firms to overbuild, overvalue, and overinvest in generative AI:

As I hinted earlier, I see the enterprise and the SaaS market as the commercial real estate arm of the Subprime AI Crisis — an industry desperate for growth attaching itself to an unprofitable, unsustainable technology that they invested in in the hopes that it would fuel a decade or more of revenue growth.

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At some point, the putrid margins around generative AI will begin to eat into the already-tenuous profitability of these companies, leading to some, I imagine, having to either vastly increase prices or drop the tools altogether, assuming that the competitive landscape doesn't mean that keeping them is a necessity to compete with others.

If that's the case, many SaaS companies may have added the equivalent of an adjustable-rate mortgage to their tech stacks, all to offer features that are at best sort of cool and at worst actively harmful to a company. And based on the fact that most of these companies have to effectively double prices to offer AI, it's hard to imagine that these features aren't already problematically-expensive to maintain.

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Another deeply-worrying eventuality could be a race to the bottom, where growth-hungry SaaS companies either deeply discount or don't charge for AI, pushing their competitors to lower the price on their already-unprofitable products. Much like the feared commercial real estate bubble, SaaS may see its own series of dramatic price cuts to its AI tools as a means of competing and showing growth to the markets...despite the costs staying the same, or possibly increasing.

And, again, much like commercial real estate, AI has locked-in costs, and service providers have little incentive to drop them. Especially in the case of Microsoft, which will likely only ever make money from AI by selling compute.

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It's hard to overstate the significance of a collapse of growth in the SaaS market, as is it hard to overstate how dangerous generative AI is to its fortunes. While these companies had costs before, generative AI is multitudes higher than regular cloud compute costs, meaning that any new revenue growth from this software will be burdened by leveraging an increasingly-expensive solution to a problem that most of them have trouble describing.

In February of this year, Zitron wrote a great essay breaking down the ways in which people used contrived metrics to insist "generative AI is a sustainable or real industry at the trillion-dollar scale" which justified externalized costs to various parts of our society that A.G.I. cultists were eager to subject to neoliberal dogma (e.g. privatization, adaptation, and efficiency maximization):

Generative AI is a financial, ecological and social time bomb, and I believe that it's fundamentally damaging the relationship between the tech industry and society, while also shining a glaring, blinding light on the disconnection between the powerful and regular people. The fact that Sam Altman can ship such mediocre software and get more coverage and attention than every meaningful scientific breakthrough of the last five years combined is a sign that our society is sick, our media is broken, and that the tech industry thinks we're all fucking morons.

This entire bubble has been inflated by hype, and by outright lies by people like Sam Altman and Dario Amodei, their lies perpetuated by a tech media that's incapable of writing down what's happening in front of their faces. Altman and Amodei are raising billions and burning our planet based on the idea that their mediocre cloud software products will somehow wake up and automate our entire lives.

The truth is that generative AI is as mediocre as it is destructive, and those pushing it as "the future" that "will change everything" are showing how much contempt they have for the average person. They believe that they can shovel shit into our mouths and tell us it's prime rib, that these half-assed products will change the world and that as a result they need billions of dollars and to damage our power grid.

Now, at last, we can begin to make our connections to Martin Luther’s critiques of indulgences.

Salvation Through Transaction

As we’ve gone over, tech firms present artificial intelligence as a universal solution to a vast array of social and political problems, even as these firms create or exacerbate them.

Venture capitalists enjoyed well over a decade of low interest rates that let them borrow huge sums of money at little cost, what did they do with it? The vast majority (around 90 percent) of their unicorns (firms valued at $1 billion or more) proved to be fundamentally unprofitable. We are all familiar with the basic formula: give me money to bleed everyone else dry and scrounge together a return for you.

In the case of Uber: give us tens of billions, secure us a valuation in excess of $100 billion, we replace very taxi driver with misclassified gig workers paid starvation wages or flying robot taxis paid no wages, and you will realize a lucrative return—it will just cost consumers immensely as use algorithmic discrimination to hike prices and suppress wages, as we massively increasing pollution and traffic congestion, and as we undermine public transit systems in our major markets, but along the way the public will forget about our initial act of arson and clamor to buy our fire insurance.

In the case of OpenAI et. al: give us tens of billions, secure us a valuation in excess of $100 billion, we replace every worker with, as premiere VC fund a16z puts it, “an AI assistant/coach/mentor/trainer/advisor/therapist that is infinitely patient, infinitely compassionate, infinitely knowledgeable, and infinitely helpful,” and you will realize a lucrative return—it will just cost consumers immensely as we enrich and sustain the fossil fuel sector, empower utilities to overbuild energy infrastructure, inflate user traffic metrics for our products to overbuild compute infrastructure, flood the digital world with sophisticated deepfakes and endless content slop, and bolster Silicon Valley’s ongoing effort to transmute speculative gains into real wealth into political autonomy that undermines democracy in the name of this desperate scramble for excessive returns, profits, rents, and greater power still.

As Karen Hao recently wrote in a New York Times op-ed:

The leading A.I. giants are no longer merely multinational corporations; they are growing into modern-day empires. With the full support of the federal government, soon they will be able to reshape most spheres of society as they please, from the political to the economic to the production of science.

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Their influence now extends well beyond the realm of business. We are now closer than ever to a world in which tech companies can seize land, operate their own currencies, reorder the economy and remake our politics with little consequence. That comes at a cost — when companies rule supreme, people lose their ability to assert their voice in the political process and democracy cannot hold.

It is relatively easy (read: lazy) to delegate technological innovation to a sector that purports to be single-mindedly dedicated to it. But as Hao muses, you wouldn’t go along with this if fossil fuel firms said “we alone should be allowed to look into climate change.” (Well, some people would and do.) This surrender of control over our technology has been made easier still by the ease with which Silicon Valley and a persistently obsequious tech media have accepted and promulgated talking points that affirm this self-serving status quo.

In the past, fear of God worked as a key pillar in rationalizing the sale of indulgences so that one could sidestep it—today, firms like OpenAI have embraced a similar marketing strategy: fear of our stillborn god, AGI. Promising to revolutionize human civilization and solve all our ills, Altman traveled the globe searching for $7 trillion in investments to kickoff humanity’s salvation. The fever dream has moderated significantly since then, now anticipating AGI at a date ranging from this year to soon!

Today’s indulgences take a variety of forms, but at their core feature artifices deployed to sustain this unsustainable enterprise.

Why reduce your own emissions when you can utilize renewable energy credits, a creative accounting scheme that allows you to secure certificates that show you’ve bought renewable-energy generated electricity produced off-site, even though you don’t have to actually consume it. A September 2024 Guardian analysis found that data center emissions from Google, Microsoft, Meta, and Apple are likely 662 percent higher than officially reported. Buy a literal certificate to avoid doing the hard structural reform and carry on with business as usual!

Maybe you want to help other firms claim they’re reducing emissions? Follow Microsoft's lead: last year, Hao reported on how Microsoft claimed it was reducing the emissions of fossil fuel companies by selling them AI tools that allowed them to more efficiently find and develop oil and gas reserves, maximizing production at those sites. Yes, we must stop doing this if we are interested in preserving our ecological niche, but the only way we can actually do so is by developing AI tools that generate revenues and profits as well as demand for renewable energy infrastructure which can power greater and greater levels of compute which can then eventually give rise to a breakthrough technology that will save us.

Perhaps you are more interested in the compute infrastructure side? Want to structure investments linked to cloud compute & preferential prices to keep major firms afloat (OpenAI—Microsoft/Google—Anthropic—Amazon) while they figure out how to fix unprofitable business models and unsustainable unit economics? Or maybe you would like to gin up demand along each node of the generative AI supply chain by pursuing a specific vision of artificial intelligence that requires more GPUs, more clusters, larger and more compute-intensive models, more data, more data centers, more, more, more, until somewhere along the way you can grow your way into your first profits? Concerned that you won’t be able to secure larger and larger infusions of capital to justify larger and larger valuations as you prognosticate about larger and larger ambitions for your increasingly unprofitable enterprise? In each instance, the solution clearly is to just deploy more capital, to spend more money plodding along in the same direction until you are saved.

The indulgence economy for artificial intelligence is a simple one. Artificial intelligence will save the world. The firms advancing artificial intelligence will save the world. They will need as much water, land, coal, natural gas, electricity, talent, and money as possible to do this. They will need unimpeded access to as much personal data as possible, as much intellectual property as possible, as much freedom to control and reshape markets and consumer behavior as possible, as much debt as possible, as much investor capital and as much government treasuries as possible.

If artificial intelligence is contributing to mass illiteracy and cheating, it is because you dragged your feet on adopting it (or adapting to it) in the classroom. Close your eyes and fork over some cash to fix this with artificial intelligence.

If artificial intelligence is contributing to an information environment saturated by nonconsensual porn, child sexual abuse material, scams and fraud that utilize realtime deepfakes generated by AI deep learning, or an abundance of AI-generated slop, it is because you dragged your feet on adopting it (or adapting to it) in your information environment. Close your eyes and fork over some cash to fix this with artificial intelligence.

If artificial intelligence is threatening the livelihood of your creative workers, it is because you dragged your feet on adopting it (or adapting to it) in cultural production. Close your eyes and fork over some cash to fix this with artificial intelligence.

If artificial intelligence is threatening to bolster the fossil fuel industry at the precise moment that sector must be put down for the sake of humanity’s survival, if there is an unimaginable amount of opacity around how much energy infrastructure artificial intelligence will actually need, if data centers are sucking up water everywhere they can manage from deserts to areas gripped by high levels of water stress, it is because you dragged your feet on adopting it (or adapting to it) in energy policy. Close your eyes and fork over some cash to fix this with artificial intelligence.

And so on, and so on.

Change, it goes, can only be realized by exchanging some coin in the direction of our saboteurs. It’s hard to break out of the brain-dead political imaginations that tell us the financing, design, development, and deployment of technology should be left in the hands of an insular network of libertarians and reactionaries more interested in surveillance, force projection, and social control than anything resembling the public good. Harder still when those preserving such a broken political order have figured out there is money to be made, even when there are no profits to be made. So long as you can convince people that it’s worth externalizing the moral costs (onto everyone else) and eschewing accountability (for harms visited on everyone else), then you can maximize returns, wealth, and power. What else matters?

Centralizing and codifying unjustified power

It is abundantly clear by now that the variety of firms interested in artificial intelligence and spending billions on it (e.g. OpenAI, Meta, Google, Anthropic, Amazon) have aligned the development of artificial intelligence in the direction of not just profit-seeking, but a wide-ranging ecosystem of delusions, distractions, detours, accounting tricks, speculative endeavors, political projects, and (de)regulatory overhauls that are about, repeat it after me, turning speculative gains into real wealth into political power that can make repeating this alchemical transmutation that much easier.

Building on his A.G.I.-ism thesis, Morozov offers "Panglossian neoliberalism" as a term aimed at capturing how Big Tech has captured our institutional and infrastructural imagination:

Championed by venture capitalists, tech CEOs, and startup founders, this credo asserts that we already live in the best of all possible worlds (reflecting its Panglossian aspects) and that there is no alternative to the market-driven provision of our tech infrastructures (reflecting its neoliberal aspect). The essence of this ideology is distilled in the recent Techno-Optimist Manifesto by Marc Andreessen, the prominent venture capitalist, who flatly states: “free markets are the most effective way to organize a technological economy.”

As history, the dogmas of Panglossian neoliberalism are at best naïve, ignoring the significant Cold War–era public spending, much of it military, that created Silicon Valley. ARPANET, Global Positioning System (GPS), the integrated circuit, and the computer mouse all stem from government funding, not free markets. But the damage doesn’t stop with bad history. Politically, this ideology often results in paralysis, hindering the search for local, experimental, and democratic alternatives to the market-driven paradigm that dominates our technology stack.

Silicon Valley has spent a long while now insisting that our analyses should focus only on markets, but through incredibly ahistorical narratives that have less to do with understanding reality than they do with manipulating it. As I’ve laid out before, Silicon Valley’s origin story is one steeped in eugenics and environmental decay, with dreams of global domination fed by blood and soil, conquest and genocide, surveillance and control, war and insurgency. It has always been about power.

As I’ve written elsewhere:

The bounties of farmlands and the underworld mines grew and grew. The sciences that developed both helped those industries metastasize larger swaths of the land. A few individuals generated dynastic fortunes that helped build newspaper empires, propaganda campaigns, monuments and memorials, all aimed at inspiring and sustaining the waves of bodies feeding into the megamachine. More fortunes still were used to fund efforts to develop the knowledge, tools, and techniques to better dominate nature. Universities, laboratories, and corporations innovated tools of remote control to administer California’s depleted ecology and corral the populace. These forces shaped San Francisco’s development, and they never completely vanished.

The problem is that San Francisco’s contado is now the world—there are always more mines, more bodies, more forests, and more wealth to be extracted; and there will always be a need for tools and techniques to subordinate everything outside the city for some Great Work.

…

There’s a dark side to nearly every tech venture. Amazon giveth same-day delivery; Amazon taketh the physical and mental health of workers hidden away in its sprawling logistics empire. Apple divines that we need $3,500 goggles, and overlooks the sacrifice zones around the mines for precious metals powering its products and the suicides at factories assembling them. Microsoft agrees to labor neutrality against efforts to unionize its various subsidiaries, and joins the other tech giants in becoming a military contractor while helping police departments across the world find sleeker tools to terrorize their communities. Google/Alphabet promises to revitalize its ailing search engine operations with generative AI, while pursuing military cloud-computing contracts. Facebook/Meta may flail around legless in a $100 billion metaverse prison while its social media platforms stumble along, but just out of view lie an army of exploited and tortured content moderators beside an ever-growing pile of corpses from the mob violence, ethnic cleansing, and genocide its products incite.

As Silicon Valley metamorphosed from stolen land to a pioneer backwater to an imagined new Rome, as mines and oil wells puncturing the earth were connected by railroads, as the Stanford colony evolved into the American empire’s armament and laboratory during the Cold War, as one tech startup bubble deflated then gave way to an even hardier one, the Palo Alto System keeps living on like a hydra sprouting newer, hungrier heads from decapitated stumps.

Generative artificial intelligence (and the A.G.I. its boosters believe will follow) is less a product of free markets than the latest in a long line of products borne out of the Palo Alto system, which has grown increasingly effective at commercializing public research into consumer products that carry noxious social costs. Whether it’s cryptocurrency, web3, the metaverse, or on-demand platforms, Silicon Valley has tried (and failed) to insist their latest product is inevitable, revolutionary, and so transformative that they must be given an inordinate subsidies to see it through as well as as much autonomy as possible to control it unmolested by democratic oversight.

And yet, as Morozov points out, it is painfully obvious that the private provision of generative artificial intelligence has left us with the worst possible form on multiple counts:

• Inefficiency and waste: OpenAI, Anthropic, Google, Mistral, Meta, and a host of other firms are "duplicating efforts, building nearly identical resources with minor differences" that will require the same data sets, labor to treat them, and sprawling data centers that consume water and electricity. OpenAI once claimed it needed $7 trillion, in what world does it make sense to let each one of these firms independently burn trillions?

• Subpar quality of services: Hyper-competition incentivizes firms to "bypass adequate oversight" and push through products that frequently hallucinate, fail on simple tasks, and cover up significant security and privacy breaches.

• Inadequate compensation for those who helped train the models: There is no hope for fairly compensating those who create original content used to train models under the current regime. AI boosters regularly claim that such compensation would destroy their enterprise completely, not that this stops firms developing AI from stealing as much as they can without compensation. The few institutions that can secure deals (such as media organizations) are doing so for the company itself, not for every single worker involved in creating the original work that's part of these licensing deals. The insistence that the solution must benefit these AI firms first and foremost is not a natural one, and Morozov points out how we could easily empower a public entity to implement "differentiated access rules based on public policy priorities" that fleece AI firms while providing free/low-cost access to everyone else.

• Exclusion of non-corporate players from R&D: Even the one goal articulated by generative AI firms—building our stillborn A.G.I. god—is just a fancy way of saying "serving the interests of its investors." Generative AI's development will be profit, not experimentation, not innovation, and often at the cost of our social relations, political sphere, privacy, cultural works, and environment. Without the inevitable birth of A.G.I., it is harder to pretend the debate is about stalling the creation of an epoch-defining technology and it becomes easier to see this is a distraction from considering alternatives to development solely by market forces. "In fields like education, healthcare, and transportation," Morozov writes, "we've recognized the market model's limitations and its tendency to erode cherished ideals. Shouldn'w we apply the same scrutiny to generative AI.”

• Lack of transparency about true costs: I've used Zitron's writings to repeatedly invoke this, it has come up in my own, and it has come up in Morozov's—a key part of AI's indulgence economy is obscuring the real cost of these products so that it is easier to make the pitch that salvation is cheaper and easier than the much harder task of pursuing alternatives. We do not know the sustainability of what these firms are offering is, only that they insist it will pay for itself one day.

• Increased technological dependency of the Global South on the Global North: Silicon Valley, our military, and our federal government have all said in one way or another that pursuing AI development is also about pursuing additional leverage over other countries—specifically China. Slowing AI development, breaking up the firms driving it, applying basic regulatory or democratic oversight, these are anathema as they would reduce American primacy in this field instead of deepending foreign dependence on our tech offerings. Is there any interest in a multi-polar global tech regime, with institutions interested in bolstering tech development in the Global South at the expense of the Global North? Likely not. And so the march continues on.

• The conservative bias inherent in these systems, which favor stability and predictability over novelty and variety: Corporate-driven generative AI is primarily concerned with profit-seeking, utilitarian efficiency, surveillance, social control, and the like. What would what Morozov calls "ecologically sophisticated generative intelligence" look like? Morozov imagines it being advanced by "institutions that genuinely value more than just predictability and efficiency, however monetizable those qualities may be." Will this require new institutions? Will we go back to the well and bolster those embedded in the welfare state, like libraries and museums (educational and cultural ones)?

There is no hope of any of this to turn over within the “neoliberal straitjacket” that Silicon Valley has foisted upon us in its bid to consolidate its private control of computational infrastructure and the vast ecosystem needed to swell it. What is lost and what is gained when we prioritize a vision that aligns with centralizing private control of our technology?

We are left with voluntary AI ethics frameworks that lack any teeth, performative decrees that purport to govern and regulate the industry but are better understood as medieval papal bulls insisting on immaterial authority on tenuous grounds! We are left with AI ethicists who assume the inevitability of a far-flung possibility (AGI) and spill miles of ink crying out for guardrails and alignment safety protocols to ensure our science-fiction scenario arrives amicably, but who have nothing to say about a genocide going on right now where Israel is using AI tools to explicitly kill as many civilians as possible as it tries to ethnically cleanse Palestinians in Gaza. We are left with AI ethics boards that are quickly dissolved, ethics researchers that are censored and fired, and alignment that purports to avoid runaway AGI, but advances the proliferation of present AI to augment discrimination, surveillance, immiseration, exploitation, and extermination.

Is all of this worth it?