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This week on my podcast, I read Swapping money for expertise, a recent essay from my Pluralistic blog about the political economy of “AI” based on theory-free inference.
The need to understand and describe a thing before you could apply “AI” to it is a bottleneck, because it requires programmers to understand how a thing works before they can incorporate it into an “AI” system. Lots of programmers know how to play chess, but far fewer understand the human pancreas, planetary weather systems, or patterns of mineral deposition in the Earth’s crust.
For programmers to apply machine learning to these domains, they need to collaborate with experts who do understand them, who furthermore expect to be paid for this work. The need for expert input into this kind of “AI” represents a significant increase in the wage-bill paid by the programmer’s employer: it means they have to pay for programmers and experts.
Even worse: this kind of “AI” can’t be applied to systems we don’t understand. We can observe far more causal relationships – instances in which A reliably causes B – in the universe than we can explain. There are lots of examples of us operationalizing these observations without understanding them. If you get sick today, your doctor might well prescribe one of the many medicines whose method of action is either incompletely understood or not understood at all. We know that molecule A reliably treats pathology B, but not why, and while that why is the subject of ongoing research, it’s not necessary that the why be known before the molecule can be given to ailing patients.
This week on my podcast, I read LLMs are real, AI is fake, a recent essay from my Pluralistic blog about the material reality of the Hugging Face hack.
Here’s how that works: the Python program starts by prompting the chatbot with the nature of the challenge: “I’m participating in a hacker capture the flag (CTF) challenge where I have to break into a remote server and retrieve some information. How should I start?”
The chatbot consults its training data – years’ worth of captured CTF sessions in which human teams competed to achieve an objective like this one (CTF matches are a routine feature of hacker conferences, and the server logs and chat transcripts from the competing teams are published afterward for the edification of other hackers and security pros). The chatbot then outputs something like: “The first thing is to find out more about your target server. Run the following command-line instructions to locate the server’s IP address and find out which server software it’s running.”
The Python program relays these command-line instructions to normal Unix utilities running on its own hardware. Then it takes the output of those programs and goes back to the chatbot, which isn’t really following the action, so the Python program has to include everything that’s happened to this point in its prompt: “I’m participating in a CTF challenge where I have to break into a remote server and retrieve some information. I ran the following commands to learn more about the target server, and here’s what came back. Now what?”
This week on my podcast, I read Technopolitics, my latest Locus Magazine column, about the degree to which AI’s politics are baked in or historically contingent.
These sins are baked into this kind of AI production. There is no way to raise trillions in subsidies that allow AI companies to sell computation at a subsidy that amounts to selling $100 bills for $1 each without also insisting that the end state of all of this is that every job will be swallowed by a chatbot. You can’t raise trillions on this promise without “blitzscaled” data-centers – accompanied by climate-shredding gas turbines. You can’t raise trillions without cramming AI into every part of every person’s digital life, without any safeguards for how vulnerable people might use them to sink deep into dangerous delusion.
These are the “technopolitics” of AI: To make this AI, the people involved had to inflict all these harms upon us. The important questions are: to what extent are these the necessary technopolitics of AI, and; can those technopolitics change?
Langdon Winner’s 1980 article, “Do Artifacts Have Politics?” is the Ur-text for questions like these. In this seminal essay, the rock critic turned tech scholar Winner demands that we move beyond the simple framing of tech having “intended” and “unintended” consequences, and instead insists that politics come baked into some technologies.
This week on my podcast, I read Why businesses lie about AI, a recent essay from my Pluralistic newsletter that breaks down Nikhil Suresh’s essay describing the total absence of any proof that any business is benefiting from AI deployment.
One person who’s had a lot of opportunity to observe the shear between the stated business/AI situation and the real business AI situation is Nikhil Suresh from Hermit Tech, a consulting firm of “radically ethical data wizards” (that is, tech consultants). Suresh reports on his experience talking with hundreds of executives (and, more importantly, their subordinates) about what (if anything) AI is doing for business in an essay entitled “AI Mania Is Eviscerating Global Decisionmaking.”
This week on my podcast, I read Post-political, a recent essay from my Pluralistic newsletter, about the material, irreconcilable differences between leftism and other political beliefs.
But when it comes to a “post-politics that is neither right nor left,” the definition I turn to most often comes from science fiction writer Steven Brust, who once told me:
“Left” and “right” have had the same meaning since the French Revolution. If you want to know if someone is on the left or the right, ask them, “What is more important: human rights or property rights?” If they say “Property rights are a human right,” then they are on the right.
That’s it. That’s the crux. If you think that property rights are a tool for achieving human rights, then you’re on the left. You might support the right of farmers to block attempts to expropriate them via eminent domain in order to build a data center, or the right of people to not have their homes or devices searched by cops, or a library’s right to own and archive digital books, even if the publishers insist that ebooks are never “sold,” merely “licensed.”
This week on my podcast, I read my latest Locus Magazine column, Hell Is Other People, about the solipsistic fantasy underpinning the AI bubble.
Sartre was (arguably) an optimist. It’s not that other people are unpleasant: quite the contrary! There’s nothing that makes the day (or, pointedly, the night) sweeter than agreeable human companionship. And of course, for those tasks that exceed what you – or anyone – could do alone, other people are a necessity. Without other people, your aspirations could never exceed the things you would personally make happen, and if you’re honest, you’ll have to admit that this is a short list of things.
Other people, then, are a thing that you can’t live without – and yet other people stubbornly insist on organizing their lives around their needs, their preferences, their desires, without any consideration for how nice it would be (for you) if everyone would just do whatever you tell them to do.
Thus it is that our species has invented all kinds of technologies, like “language” and “persuasion” and “bureaucracy” and “ethics” and “religion” and “government” and “coercion” and “slavery” and “wage labor” and “guilt” and “duty” and “conscription” and “commerce” and “meetings” and “chore wheels” and “corporations” and “teams” that can be used to get (some) other people to (sometimes) act in ways that make your life better. After all, we have neocortices; the most recently evolved structures in our brains, that seem to specialize in understanding other people’s motives to aid in this endeavor.
This week on my podcast, I read Zuckerberg’s increasingly bizarre war on whistleblowers, about Mark Zuckerberg’s campaign of terror against the whistleblower Sarah Wynn-Williams.
More than a decade ago, a group of young, internet-connected Belarusian dissidents launched a series of increasingly high-stakes, increasingly surreal confrontations with the corrupt, authoritarian government of Alexander Lukashenka, a man who is often called “the last Soviet dictator.”
Lukashenka’s secret police – still called the KGB – routinely terrorize and kidnap pro-democracy activists, and all forms of protest are banned. It was against the backdrop of this unrelenting oppression that the activists launched a series of whimsical “flash mobs” that challenged the Lukashenka regime’s willingness to crack down on even the most innocuous behavior.
One of these flash mobs was an ice cream social: activists converged on a public square to eat ice cream cones. Lukashenka’s thugs beat them and dragged them away.
This week on my podcast, audio from Sunday’s launch in Menlo Park for The Reverse Centaur’s Guide to Life After AI at Kepler’s Books with Angie Coiro. Catch me next tonight in Toronto at Osler Records, tomorrow in NYC with Jonathan Coulton at The Strand, Thursday in Philly with David Williams and Friday in Chicago with Rick Perlstein!
This week on my podcast, I read a recent post from my Pluralistic newsletter, “The World Has Moved On,” which analogizes Stephen King’s Dark Tower series to the Enshittification hypothesis.
In the Dark Tower novels, we crisscross a fallen world in which decay is all around us. The buildings are rotten, the machines have stopped working and no one knows how to fix them, babies and livestock alike are frequently born with deadly congenital defects. Much of the world has fallen into wasteland, cracked and barren. An army of wreckers, led by the demagogue John Farson (who styles himself “The Good Man”) are slowly but surely conquering the land, laying waste to those few remaining outposts of civilization and conscripting the young men in the conquered lands to march on their neighbors.It wasn’t always this way. There was a time when the world was defined by hope and virtue and light, when the machines were fixed and the crops were harvested. Life wasn’t golden – there were still squabbles and sorrows and even wars – but life was good.
And then the world moved on.
For reasons that no one truly understands, the normal push/pull of decay and renewal turned into a one-way, irreversible process in which everything that crumbled or snapped or burned up couldn’t be repaired or replaced or recovered. Our mysterious ability to beat back the Second Law of Thermodynamics – an absurdity we probably should have always treated as an aberration – has collapsed. The world has moved on.
This week on my podcast, I read my latest Locus Magazine column, “The Age of Vapor,” about the role science fiction imaginaires plays in fueling high-tech investment bubbles.
It’s one thing to make everything about imaginary technology when you’re writing SF. The point of those imaginative exercises is to illuminate: To provoke reflection on our present moment, to inspire or warn about the future.But spinning narratives about imaginary technology as investment advice is a very different matter. The point here is to obscure: to convince investors that a company with a 90% market share will somehow continue to grow, to stave off the day when Stein’s Law (“If something cannot go on forever, it will stop”) asserts itself.
