michael-dean-k/

Bernie wants to pull off a 50% one-time equity tax on the top 3 AI firms (OpenAI, Anthropic, xAI). This is ripe time for a mainstream populism to ride the tailwinds of AI populism, tapping into hatred and impending doom and the whole gambit of middle class paranoia, ripe time to propose a century-defining redistribution scheme. He opens by saying that AI was stolen from us, built from our collective intelligence, and therefore it's a national utility that the people should own. To ground it in reality, he used the Alaskan sovereign wealth fund as precedent, citing how citizens get paid annually from oil sales. We'll likely see many more of these proposals leading up to our 2028 election. But after you do some napkin math, you realize that this plan is bogus: no one would agree to it, and even if they did, it wouldn't benefit the American people.

This is citizen ownership in rhetoric, but government ownership in structure—a passthrough mechanism as a Trojan Horse with Pete Hegseth and the goons inside. Realistically, I don't think this is meant to be a serious proposal; the labs won't accept it. It's more so a gesture to buy goodwill for the Democrats at a time when mass hatred for AI is cresting.

Here are the issues I see with the concept (along with some grasping for solutions):

1_We don't need government equity, but guaranteed royalty distribution:

This is not a profit tax, but a way to formalize government seizure through an equity transfer. It even comes with board seats within thees AI companies. Remember, this is the same government that tried to force Anthropic to allow unrestricted domestic mass surveillance and autonomous weapons. The equity only gets to the citizens if the stock appreciates, they convert it to cash, and then decide to write welfare checks. Does our current government seem like a voluntary patron of citizen welfare right now? Will welfare checks beat Iran and China? And even if this were intended to be a passthrough mechanism, it would be very hard to make all that equity liquid.

The Alaska fund that Bernie mentioned is structured very differently. It's anchored not in equity, not in profits, but in revenue. 25% of Alaskan oil revenue goes to a constitutionally-protected fund, which is then reinvested into the stock market; the principle is locked and the dividend is split among citizens, usually $1-3k per year. Could a similar model work for AI companies?

This would never work with profits, because AI companies aggressively reinvest. In the short-term, an AI company would resist a revenue royalty because it would slow expansion, but: (1) if all companies did it, they wouldn't be disadvantaged; (2) it beats equity because they retain full control of their company; and (3) if they believe they'll be wildly profitable, then a 10% royalty is possibly more than half of what dividends would pay from 50% equity. So what could a 10% royalty return?

By the 2040s, annual AI revenue could be $20T globally across software, hardware, data centers, and energy. If America has half the market, and 10% is distributed to a citizen fund, that's a $1T annual budget, completely liquid. So how do you use it?

2_ We shouldn't redistribute equally, but strategically:

Alaska has 738,000 residents. The US has 350,000,000, almost 500x bigger. You can do equal distributions at the state level, but at the federal level it'd ineffective. When we talk about UBI or even Elon's UHI (universal high income), we need to realize that U doesn't work at scale beyond pilots. $1T distributed to every American citizen yields $2,857/year. This matches the upper-end of Alaskan payouts, but it's nowhere near what we need to account for AI-driven automation and disruption.

And so instead we need to be strategic over how we distribute it to cover the wide range of effects. Maybe 50% of the fund is reinvested, and the dividends are redistributed based on income (with most of it going to the bottom 10-25%). The other half can be used on housing, free medical diagnosis and prescriptions, free education, New Deal style jobs concentrated in areas that can't be automated (childcare, healthcare, etc.). Who decides this breakdown?

3.Instead of a cabinet agency, this needs an independent board:

If we want citizens to own AI, then we need some form of citizen representation to guide it's growth, otherwise it all devolves into technocratic expansion and war. You could imagine some kind of tripartite board structure, where it has government reps, industry reps, and citizen reps. Any single branch has a myopic set of interests, including the citizens. The citizen branch might undervalue national security or capability improvements, but without it, there's no one representing the problems that hundreds of millions will face.

What I'm reaching at here, I think, is that it's more than just getting a check for theoretically contributing to the LLM hivemind. There's something important to me, as a citizen, to have some say in where AI royalties are redirected. Whether I participate simply as a voter, or I work hard and get anonymously elected to represent my state for a single issue within a liquid republic, who knows. And again it goes beyond just getting and allocating money, but this board should be involved in AI-related policy, especially as it relates to domestic matters.

It's unlikely that power will just be granted to citizens, for they have no leverage next to the ones with the tanks and algorithms. But as the governors and technocrats quarrel, there's a world where a mediating party comes in, and maybe it's their role to insist that a citizen branch can help round out the dynamic.

This last point has basically veered into redesigning government itself, which is both out of scope, but also, possibly, exactly the point. Bernie's whole play is to let the people own AI, but for that to actually expand beyond populist rhetoric, citizens need a more meaningful way to engage with civic matters than to vote for a president once every four years, they need actual representation.

Something about the term “knowledge worker” doesn’t settle with me. Some people identify as one, and I’m sure they either grieve of mock the idea that AI will kill email jobs, but knowledge work is the work we should be most eager to shed.

Compared to a factory worker, one who manipulates physical materials and turns them into goods, a knowledge worker does the same with information. It’s computer work. There is a utilitarian air to the phrase, an efficiency. It serves the needs of an employer. It’s about sifting through and repackaging information to create economic value. A better term might be “information assemblers.” An information assembler can go their whole life within a particular domain of specialization and build a strong intuition for how it works, but without knowing Knowledge.

There are many ironies in the phrase. The knowledge worker is so busy setting up meetings and writing reports and filling out reviews and dealing with clients and managing products, that they never have time to touch Knowledge, the thing that matters. It’s an oxymoron. One cannot work and simultaneously gain Knowledge. It’s antithetical to technique, to markets, to legible value. Knowledge is beyond an industry, beyond a process, beyond specialization itself. Knowledge is generalizable insight: how to think or design, when to start over, who to draw from, what’s even worth pursuing, why do anything? It's an inner knowing, a model of the world, and a process for thinking. Virtues, metaphysics, epistemology—I guess I'm describing philosophy.

Knowledge can obviously help a worker be more efficient, but (1) it’s extremely slow and time-consuming to obtain, requiring study far outside of your practical workflows, and so it’s impossible to justify on the clock, and (2) once you obtain Knowledge, you care far less about efficiency because you’re questioned the whole machine. It’s not a surprise this term was coined in 1959 by Peter Drucker, the founder of management theory. I don’t know much about him or his book (The Landmarks of Tomorrow), but I imagine a midcentury worker being honored and proud to operate in the celestial fields of “knowledge.”

The reason I wrote this post is because knowledge workers are being told they need to master AI tools, when it’s precisely those same AI tools that will end information assembly jobs. I suppose there is a transition period where, while the tools are still maturing, you can 2x your efficiency and do fine. But if your job can be broken into a series of machine-legible steps, and all the context needed is documented, then even if you 10x your efficiency, are you not just expensive and now redundant middleware between you and the output your manager wants?

Middleware is part of a software stack that helps two disconnected systems talk to one another. It translates, transforms, and routes. It doesn’t produce anything original, it reformats inputs to outputs, like a knowledge worker. In the last decade, we’ve already seen middleware become automated and commoditized. Instead of custom integrations, companies now build APIs so they can directly call from each other's databases. Marketplaces like Zapier let people string together API calls through a no-code interface. If this trend continues, jobs will become zaps too.

The better move to prep for AI is to dip into humanism, design, philosophy, psychology, intellectualism—things completely outside the paradigm of technique, efficiency, and capitalism. For one, they’re fun and soul-enriching, but also they cultivate a mind more that’s more competitive across labor games. To someone in the knowledge work economy, this seems too impractical to take seriously, but specialization is a losing game. Instead, you should figure out how to give yourself a liberal art education. It’s free if you have internet. Learn to think, doubt, model, and visualize; how you rotate a problem in your own head will define how you use AI.

Universal basic income is a basic phrase. It’s only one of several approaches to reattribute wealth after our social contract nullifies.

One alternate idea is universal basic compute (UBC), which is about giving everyone free access to the most powerful AI models. Sam Altman recently said that UBI might not work, and we should try UBC instead. This is even more unlikely to work. Giving someone Claude Mythos, the killer model, doesn’t mean they can turn prompts into dinner. Access doesn’t guarantee results. It faces similar odds as entrepeneurship. But maybe it has enough agency so all you have to do is write “make me $10,000 this week”—in that case, everyone will run it, and then it’ something like a lottery, where some machines happen to beat other machines.

The more likely route is universal basic services (UBS), where a government or company provides you, for free, all the things you used to need money for: healthcare, education, housing, transportation, food. The engineering elite will harness their superintelligence to achieve such radical efficiencies that the cost of everything will crater. Maybe it's cheap enough to become a trivial expense. This is a nice idea, one where I can imagine myself focused completely on my art, with no need to slave away for a wage anymore. It’s also science fiction. I don’t doubt that this can happen in 20 or 30 years, but labor shock is coming a lot faster (in less than 5), meaning there will be a transition generation of turbulence.

Then there’s universal basic dividends (UBD) and universal basic equity (UBE), in which citizens get shares of collectively-owned assets, like shares in a frontier AI lab or robotics company. OpenAI was originally set up for something like this, until it weaseled out of it’s non-profit entity.

All of these have the same critical flaw, the U. Whether it’s a government or company, you can’t meaningfully redistribute to 7 billion people without destroying the parent entity. Instead, we may be looking down the barrel of a new definition of labor, less focused on productive output, and unfortunately, more so on data and attention, what a citizen truly has to offer in the eyes of a state. We'll find something to exchange for the money and services to flow down, but it won’t be unconditional. I suppose a contract, by definition, is never unconditional, and so neither should a social contract.

Anti-AI sentiment is escalating: the Pause AI movement, state-level data center bans, molotov cocktails at Sam Altman's house, artists going to dumb phones, witch hunts for AI prose. Protesting and boycotting AI, at a personal level, is the exact wrong approach. It misunderstands the Luddites. They were not against the machines in principle, they were against the factory owners not sharing the profits of the factory. This is possibly about to play out a grand scale: AI and robotics labs could capture nearly all economic value, and there will be a plea to nationalize these companies and redistribute the profits.

While the scope and effects here are way bigger, the workers of the Industrial Revolution were far more disempowered. You couldn't "just do things." You could operate someone else's machine, but you couldn't just spin up a competing factory; that required land, resources, labor, none of which you had. There was just a certain amount of capital needed to compete, and it wasn't possible. Workers were limited to being workers, so they had no choice but to revolt with violence.

The difference today is that the worker and artist suddenly have access to build-your-own-factory tooling. A single person for $100/month can compete with companies valued in the millions and billions. It's asymmetric labor. Regular people can build civilization scale infrastructure, distribution labels, social media engines, software, etc. Never before has there been a democratic opportunity for people to self-organize into their own collectives, tribes, governments, and whatnot.

At least to me, this kind of optimism—principled, delirious, ambitious, but still careful and skeptical—is better than the cynicism of the "resist" factions. There is nothing you or your circles gain by putting your head in the sand; it brings a distanced, crabby, virtue-signaled posture that does nothing to change the actual situation. You gain nothing by staying on the ChatGPT free plan on default settings and complaining no how it's an ineffective, incapable, sycophant. It requires an ounce of nuance, to be critical of how the labs act, but to then use that lab's best tools towards your own sovereignty and vision.

I think what I'm trying to get at here is that the Luddites of the 21st-century will not be reverting back to typewriters and flip phones, they will be wielding AI tools in ways to foster human connection, and the kind of pro-human cultural that the Internet originally promised, but was never realized under capitalism.

Why am I so engaged with the news these days? I think it’s part of a deeper desire to update my world model. There is no doubt, massive change. Geopolitical, economic, technological. And as abstract as those things usually are, it feels like some sort of shift that, in 2-3 years time, wil have an effect on my life. Of course, for many people in the world, it’s hitting them now. But similar to how COVID spared no one, it feels like your model of where things are going will directly effect your preparedness.

But this feels more existential; safety/security are actually on the line. And so that’s an anxious kind of thought, that the tectonic plates under your reality are shifting, and it’s not some recreational yearning to re-skill and recalibrate, but a mandatory thing.

And so to make sense, what do you do, go on X? That’s a total cesspool. New media is worse than the old gatekept media. And so, where I think I want to take this, is to build my own systems to sift through and aggregate information, and to build my own UI to do this. Even a simple Claude prompt, “what happened in Iran in the last 4 hours” is so much better than X. It’s stripped of sensationalism, and reading is just a less triggering medium. Bias aside, it’s at least free from people who are intentionally trying to deceive you for virality. There is a clout-chasing incentive, paired with actually turbulent times, which makes algorithmic news something like a schizophrenia filter.

And so what are these questions, these underlying uncertainties that are triggering a model change? How will anyone make income with the rise of AGI-3 and eventually ASI? How do I exist online and avoid hyper-surveillance and cyber-sabotage? Where in the world can I live to build a better future for my daughter, one where colleges doesn’t exist, jobs don’t exist, and where quality of life actually depends on nationalized social systems? A weird future. And weird to consider the fall of America, a kind of reverse migration, where, because of a confluence events, it might not be a place to raise a family in 1-2 generations down the line.

And so practically, this is resulting in things like: (a) applying for EU citizenship, (b) setting up AI agents for my business, and (c) considering cybersecurity, new ways to protect, share, and collaborate on writing (ie: how do you build an audience if the commons are polluted?). This is all very disorienting; it's hard to continue with business as usual when you become open to this scale of change.

The AI takeoff hysteria is hard to avoid these days, and I'm realizing we don't have clear distinctions between AGI/ASI. I wanted to revisit an old framework of mine to see if anyone finds it helpful (and if it's worth developing). There are some existing classification frameworks, but they're low-resolution. My basic idea is to break AI into three eras: ANI (narrow intelligence), AGI (general intelligence), ASI (superintelligence). Then, you can break each era into 3 tiers. You only shift from one tier to the next when you make breakthroughs across different criteria (let's say, (a) generality, (b) transfer, (c) autonomy, (d) learning, (e) self-modeling). I think the last few weeks are the collective hype of us all realizing we're shifting from AGI-1 to AGI-2. It's exciting/scary, but I think the paranoia mostly comes from not realizing how big the gap is between AGI-2 and ASI-1. (Spoiler: ASI might arrive slower than we think.)

ANI-1 is scripted logic, the lowest form of "artificial intelligence," basically Goombas. ANI-2 might cover Google Maps or AlphaGo, intelligences that excel in a single function, traffic or chess. Siri is ANI-3; even though it feels broad, it really uses voice to route you to 20 or so pre-defined tricks. The chasm between Goomba and Siri is similar to the chasm between early-AGI and late-AGI. ChatGPT and the multi-modal models that followed, capture AGI-1, a single neural network that can do basically anything, even if it sucks: essays, songs, video, code. The newest models (and their agentic harnesses) are feeling like AGI-2. They're significantly better at coding, can run for hours at a time, and are starting to make contributions to machine learning itself.

AGI-2 could last a couple years. As agentic AI matures, I'm sure there will be a few "takeoff" scares, but they'll probably feel more like a flood of a trillion midwits than real ASI (still, that could be enough to break the economy/internet). While we went from AGI-1 to AGI-2 through data, scale, and engineering, it seems like we'll need research breakthroughs to get to AGI-3. It won't be through scaling alone. Whenever and however we get to "human complete" intelligence, the apex of AGI is a single agent that is a master of all human domains, a Nobel Prize winner in every field at once, seamlessly transferring knowledge between them, unlocking a cascade of civilization-altering inventions.

As crazy as AGI-3 could be, it still isn't superintelligence. That has its own era, and the chasm between early ASI and late ASI will be as big a gap between the chatbots who can't count the R's in strawberry and the agents that cure cancer. We can only really speculate on ASI (because it would be truly alien), but we can imagine it as step changes in recursion, scope, and complexity. Imagine ASI-1 as an agent that, as it's working, can infer its own limits, and self-modify its learning paradigms in ways we can't understand. Imagine ASI-3 as something that can monitor reality in real-time, and, reconfigure its hardware in real-time (some hydra of graphics cards, quantum computers, and neuromorphic wetware) to run simulations at unfathomable scales in unimaginable fields, running on a hardware stack so big we have to put it in space and run it on fusion. This goes far beyond my ability to not bullshit, but I think something as insane as this, thankfully, is still far away, which points to the real question nested in my framework:

Could the rise of AGI/ASI be linear? People gravitate towards "AI will plateau" or "the singularity is imminent," but the conservative middle ground is more boring: linear progress. Maybe the exponential advances are real, but so are the extreme frictions of research, infrastructure, and social effects. If AGI-1 arrived in 2022, and AGI-2 arrived in 2026, maybe we'll keep ascending tiers in 4-year intervals: AGI-3 in 2030, the first true "superintelligence" by 2034, and ASI-3 by 2042. This shift from AGI-1 to ASI-1 (12 years), is considered a "slow takeoff" scenario, even though the ANI era took around 70 years. If we zoom out to the scale of a human, linear progress will still feel like centuries of change all in a single turning of generations.

A few months ago I saw a YouTube video titled something like, “A child born in 2025 is more likely to get killed by AI than graduate college.” What a ridiculous claim. I assumed it was clickbait and didn’t click, but it has jingled around my head enough to the point where I think I can make sense of it’s argument:

• The average p(doom) of an AI engineer is 16%, meaning there’s a 1 in 6 chance of human extinction (put another way, companies have morally rationalized the need to play Russian Roulette—if we don’t do it the bad guys will—, without acknowledging that if they survive and win, they get the consolation prize of comandeering the whole economy).

• 40% of US adults, age 25-34, today, have a bachelor’s degree. If there’s massive job automation and employment, a college degree would be both unaffordable and an unreasonable cost if it were. It’s not unthinkable that <15% of next generation gets a college degree, which makes that sensational claim, weirdly, plausible.

I still think it’s a shaky comparison, confusing two different types of probability, and assuming extreme ASI turbulence. But as someone with a daughter born in 2025, it has gotten me to think about how the societal backdrop to her upbringing could be especially weird. Our circumstance already gets slightly weirder with each generation. Except, maybe next loop will be an unavoidable and disorienting flurry of change that will confuse parents and rewrite all of the conditions for the typical coming of age moment (all the teen movies will be sci-fi, the popular memoirs could be written by transhumanists who have upgraded in unimaginable ways, like they no longer need to sleep because of a new pill, or they can control the genitals of their peers with an app, who knows).

And so now, I find myself drawn to a 2045 forecasting project. Trying to predict the future is typically a huge waste of time (unless you’re gambling and win), which is why I’m going to have AI write the whole thing. This is a rare exception where a writing project makes little sense for a human to do. All I’m going to write are the upfront origin documents, and then Claude Opus 4.5 will read 25,000 sources, write a million words or so, and then organize it all into an interactive, oatmeal-looking website called 2045predictions.com (got it).

Before I run it, here’s something I’m currently thinking through:

What is the omega state? When I look at the popular AI forecasts from 2025, it reads to me like they have a pre-determined end state, only to then use detailed forecasting to make it seem convincing. The AI-2027 forecast seems like they came to their conclusion from very detailed calculations on how a hivemind of 200,000 autonomous coders would evolve month-by-month, but I also suspect that they picked the year 2027 because the following year, 2028, is a US election year, and they want the next administration to take AI safety far more seriously (instead of just insisting we have to beat China). I don’t think there’s anything wrong with this. You kind of have to start with an omega state. The future is so boundless that you need to begin with a guess, a bold outline on the general direction of things.

Here’s my omega: let’s assume humanity survives, and let’s assume technology does unlock hyperabundance that leads to a post-scarcity world, HOWEVER, it’s not utopian because it simultaneously unlocks a new cascade of moral, social, and spiritual crises, dilemmas that will test the timeless primitives of humanity (sex, life, death, consciousness, religion, home, etc.). This omega state makes sense for me because (1) we already know that ethical dilemmas scale with technology, and (2) according to the Strauss-Howe generational theory (from the same guys who coined “milennalis,” “Gen-Z,” etc.), this already tends to happen every 80 years (the length of a human lifespan). A new techno-political order creates a spiritual crises that generates an Awakening, a new value system that shapes society for the next century or so. You know what’s 80 years before Kurzweil’s “singularity” of 2045? The counter-cultural revolutions of the 1960s. What I’m getting at is that the 2040s might have echos of the 1960s, where demographics are divided on core issues and LSD is replaced with consciousness-altering machines (Terence McKenna said that computers are drugs, you just can’t swallow them yet).

We currently define the singularity as “the moment when a computer is smarter than all humans combined,” but that effectively means nothing, and it’s far more useful to have some guesses on how we all might freak out about that happening.

A new formulation: how do we design civic structures (treaties, institutions, protocols, ethics, and laws) for exponential technologies to avoid a “wake-up incident” that might be too late to contain. 

This goes beyond AI safety, because superintelligence effectively unlocks every other industry (intelligence unlocks energy and material science, and those three are the bottleneck to VR, crypto, everything). We can’t be developing hard technology without innovating on our civic technology. A “dominance” mindset is the last sin of a species, the mistake that most intelligent lifeforms likely make as they begin to unlock sources of intelligence, energy, and science. 

This is a neat little formulation, but the really question is how can you dedicate your life to this without getting stopped by hopelessness? Who has the power to make geopolitical decisions like this? What would it take to form the 21st century equivalent of America? Is that even possible today? Even though the pinnacle of 18th century power (England) was able to be disrupted, I wonder if 21st century power is so totalizing and tyrannical and transnational that the ability to rally around a principle (one that works against capital and power), even if augmented with new decentralizing technologies, is fickle.

Will was surprised to learn that I think machine writing could soon surpass the best human writers. As the head of Essay Architecture, he thought my position would just be “no matter what, humans will always be better at writing essays than machines.” I actually have some pretty extreme predictions on the trajectory of technology (I guess you could say I'm an ambivalent accelerationist), but I guess I believe that AI progress is irrelevant to the fact that I will always enjoy writing and see writing through the chaos as an opportunity. So yes, I think machines will make essays that are history-defining, that are good to degrees that are unimaginable to us today.

This will, unfortunately, make it even harder for writers to have economic value; but realistically, it's already too hard. The Creator Economy is a game of power laws, and AI might shift the chance of success from 2% to 1%. But could the same technology help artists go from 1x potential to 20x potential? If AI kills the market for commoditized creative work, will it let humans focus on the right things?

In "wicked domains," the only solutions are paradoxes.. It requires you to sleep with the enemy. If a problem is wicked, it means no single solution can unfuck a problem. It's an imbroglio. In every solution, everyone dies (in the extreme). Politically, the solution to wickedness is to somehow become all sides at once. We need to become far more authoritarian than is comfortable, AND simultaneously, far more libertarian than comfortable (these are opposites on the Nolan chart). It’s the paradox of being both far left and far right. We can longer exist at any one point on the Nolan chart, we need to straddle the entire diamond. We need unexpected fusions to solve the hardest problems; harnessing the best parts of each extreme, while, somehow, devising incredibly nuanced architectures to prevent the known and likely abuses.

Instead of a diamond, visualize it as a ring around the “radical center” that aims to synthesize all opposites.

Let’s assume authoritarianism and libertarianism are opposites. We have kings, and we have markets. How do you subsume a free market within a benevolent tyrant? I know the K-word (king) has a charge now, and so by even bringing this up, I assume you assume I’m a Trump apologist or something. But actually no. Rather, this comes from the fear of acceleration and Nick Land’s conclusions on capitalism. A free-market pushed to the extremes of automation creates an inhuman and pulverizing force. Alternatively, as we approach AGI/ASI, it’s possible for someone to create an open-source machine God to follow their whims. In this paradigm, decentralization might actually be more dangerous than tyranny, and so we’ll all need to unite under some centralized system that has an antibodies that can protect against the worst possible viruses (please bear the oversimplifications here...).

The general gist comes in this question: can we recreate a free-market economy within a one-world-government system, and design it in a way to prevent abuses from both ends of the spectrum? Obviously, not an ideal situation, but I think accepting paradox is the only way through.

Another problem: How do we fix the debt? Extreme taxation. But then how do we make it worthwhile to pay taxes? The rich gain formal power in government (via equity?) and the ability to control the budget (after base expenses are paid). But then how do you prevent abuses from the wealthy? You could have citizens operate as a check, to vote on and weight final allocations.

If it were ever possible to rebuild political system from scratch, I suppose it would look something like this. Paradoxical. Extreme on both poles. Obvious downsides, but then complex architecture to mitigate. This is the nature of how our species will have to respond to wicker problems and mitigate the abuses of power in the age of exponential tech.

Even if techno-feudalism is coming, we’re not trapped in a system of digital kings and serfs. I wonder, if we look back to the 10th-13th centuries, could we understand the different archetypes of autonomy to imagine how they might be reforged in the future?

• The hermits (the anchorites) fled society and were bound to no king. They lived in nature (or in a basement cell) but had control over their time / spiritual practice.
• The troubadours were the artists, and while commissioned by kings, they moved town to town and generally had no allegiances. (Traveling scholars and clerics, known as “goliards,” are similar—intellectuals with mobility.)
• The bandits operated in free zones between manors and would spread anti-feudal sentiment (think Robin Hood, or maybe also the “knight errant”).

To reinterpret these medieval roles for the 2030s, you could simplify to a triad of “ascetic, artist, outlaw.” You can (1) reject new technology and live an off-feed, off-grid, no-robot, analog life, (2) master tools and make things to gain independence in the emerging system, (3) revolt against the king(s).

I’m sure there are more options than this. Also pretty sure you can blend tendencies from each. I’m just trying to think through (and think against) the “bound to be a luxurious serf on UBI” mentality that comes up when talking about the future. Not sure about the economic realities of these modes (ie: the serf had stability, while the other 3 often had malnourished, brutal lives); but I wonder if/how technology evolves them.

I have gaps in medieval history and sociology, so please poke holes, ask questions, share sources, etc. I figured I’d share a fuzzy idea that bugs me to see if it gives me energy to turn it into something.

Not UBI, but ABI (attention-based income):

1. AI is not a bubble; the core bottlenecks around any technology is science, energy, and intelligence. Of those 3, intelligence is the most likely to boost science/energy. Meaning exponential AI is something like an acceleration of every other field to their maximum degree. It is not only not a bubble, it is the dead bubble resurrector.
2. People say not to worry about AI job loss (“people have always adapt to new tools!”) but this revolution is different because the invention is not just a tool, but labor itself. Agents will eventually create a supply shock. Sure, new jobs will be created, but they’ll be very specialized around AI research and systems design.
3. Maybe we all lose our jobs, but we also each get access to a 20-100 person digital labor force, probably at very low cost. So while traditional jobs might go away, everyone is suddenly able to be an entrepreneur with a personal labor force at the size of a Series A or Series B funded company.
4. In hindsight, it will seem like Silicon Valley used AI to make their startup culture the prominent culture. The problem is, 99% of startups fail. So even though it will marketed that so many people will be empowered, most might not be able to convert it into financial stability.
5. This means that unemployment could be historically high, and that causes unrest that the ruling class has to deal with. In our case it’s the technocrats, not the politicians in charge.
6. UBI will be shaky to implement. Some countries will have none, some a bit, and a few will give a living wage.
7. Social media companies, will 1) realize attention is the last scarce resource, and 2) populations are rioting, and so a few will start paying users to scroll. It’s a kind of UBI, but conditional on the value you provide on a specific platform.

Harari refers to AI agents as “digital immigrants” that “move at the speed of light.” Feels like a metaphor that has the potential to seep into psyche of the American right (or even, the current administration). It taps into what’s wrong about the “we always evolve and find new jobs” defense; in this revolution, the invention is labor itself, infinite and cheap.

The narrative of 'new jobs will be created' is bullshit. It won’t be 1-for-1. Past technological revolutions created new machines that still required operators. In this revolution, the invention is automated labor itself. The new jobs will be for people monitoring 300k agent hiveminds, and there won’t be many of them. I think the more realistic narrative is “everyone gets a piece of the hive mind.” You get a cluster, you get a cluster. For cheap, you’ll have your own 20-50 person workforce. The question is, can the average person use that to create economic value? I think the shift actually underway isn’t about “some jobs die and new jobs get made.” I think it’s much more fundamental. Everyone will be thrusted from employee to an employer (of agents). I can imagine these big AI companies arguing against UBI, because they’ll claim they’re giving 7-figures of economic velocity to every person for free, each year (ie: equivalent of a 30 person, $4.5 million payroll). They’re not wrong, but it’s a deceptive frame, because labor doesn’t easily convert to value. In most cases, it will turn out like an army of idiots working on problems that aren’t worth solving. Startup culture will become the dominant culture. If only 1% tap into the right problem and execute on it, WANGMI.