Gabriel

Billy Donovan explains the Bulls cutting Jaden Ivey after the guard posted a homophobic video today. “Organizationally, there’s certain standards I think we want to have as an organization and live up to those each and every day.”

🚨 Disgusting: A San Francisco judge admitted she released a violent thug from prison, who then went on to kill an elderly man, because she was worried prison would be “too hard on him.” Time to hold judges accountable.

Here are some questions I wish "Pause" and "Stop" advocates would address: 1. Assuming we achieve the desired policy goal through a bilateral US/China agreement, what would be the specific metric or objective we would say needs to be satisfied in advance? Who decides whether we have satisfied them? What if one one party believes we have satisfied them but the other does not? 2. If the goal is achieved through a bilateral US/China agreement, would we need capital controls to ensure that U.S. investors cannot fund semiconductor fabs, data centers, or AI research labs in countries other than the U.S. and China? 3. Would we need to revoke the passports of U.S.-based AI researchers and semiconductor engineers to prevent them leaving America to join AI-related ventures elsewhere? How else would the U.S. and China keep researchers within their borders? 4. How should we grapple with the fact that (2) and (3) are common features of autocratic regimes? 5. Do the above questions mean that this really should be a global agreement, signed by all countries on Earth, or at least those with the theoretical ability to host large-scale data centers (probably Vanuatu doesn't need to be on board)?

Pause AI rhetoric is predicated on the notion that the AI companies are recklessly racing toward dangerous tech and that a government controlled pause button is therefore necessary, but this seems really hard to reconcile with the fact that government is attempting to destroy an AI company because *the government* is racing toward plausibly dangerous AI uses (Sec. Hegseth has stated in official directives that he wants to deploy AI into critical systems regardless of whether it is aligned, for example) and *the company* is pushing back. The roles are totally reversed from the logic that Pause AI and frankly other AI safety advocates confidently assumed for years. It is *industry* that is in favor of alignment and at least somewhat measured deployment risks, and government whose actions seem much closer to reckless. I predicted this for years. I said, in particular, that pauses and bans and licensing regimes gave government a dangerously high degree of control over AI, and that the incentives of government are much more dangerous than those of private industry with competitive market incentives. I believe the events of the last month are good evidence in favor of my view. At this point if you are an AI safety advocate whose policy proposals do not wrestle seriously with the brutal political economic reality of the state and AI, I don’t take you seriously. It gives me no pleasure to have been right about this, by the way. The state has an incredibly strong structural incentive to centralize power using AI, and we are, all of us, not so empowered to stop it. I am quite concerned about this.

Claude knows! —> The Lump of Labor Fallacy and Why AGI Unemployment Panic Is Economically Illiterate Let me lay this out with full rigor, because this argument deserves to be prosecuted completely rather than waved away with a sound bite. I. What the Lump of Labor Fallacy Actually Is The lump of labor fallacy is the assumption that there exists a fixed, finite quantity of work in an economy — a lump — such that if a machine (or an immigrant, or a woman entering the workforce) does some of it, there is necessarily less left for human workers to do. It treats employment as a zero-sum pie. The fallacy was named and formalized in the early 20th century but the error it describes is far older. It animated the Luddite riots of 1811–1816, where English textile workers destroyed power looms convinced that the machines would steal their jobs permanently. It drove opposition to the spinning jenny, the cotton gin, the mechanical reaper, the steam engine, the telegraph, the railroad, the automobile assembly line, the personal computer, and every other major labor-displacing technology in the history of industrial civilization. Every single time, the catastrophists were wrong. Not partially wrong. Structurally, fundamentally, categorically wrong — because they misunderstood the nature of economic production itself. The reason the fixed-pie assumption fails is this: demand is not fixed. Work generates income. Income generates demand for goods and services. Demand for goods and services generates new categories of work. This is an engine, not a reservoir. When you drain some of the reservoir with a machine, the engine speeds up and refills it — and often refills it past its previous level. II. The Classical Economic Mechanism That Destroys the Fallacy To understand why the lump-of-labor assumption is wrong about AGI, you need to understand the precise mechanism by which technological unemployment resolves itself. There are four distinct channels, all operating simultaneously: Channel 1: The Productivity-Demand Feedback Loop (Say’s Law, Modified) When a technology increases the productivity of labor or replaces labor entirely in a given task, it lowers the cost of producing whatever that task was part of. Lower production costs mean either: ∙Lower prices for consumers (real purchasing power rises), or ∙Higher profits for producers (which get reinvested, distributed as dividends, or spent as wages for other workers), or ∙Both. Either way, aggregate real income in the economy rises. That additional real income does not evaporate. It gets spent on something — including goods and services that didn’t previously exist or were previously too expensive to consume at scale. That spending creates demand. That demand creates jobs. This is not a theoretical conjecture. The average American in 1900 spent roughly 43% of their income on food. Today it’s around 10%. Agricultural mechanization didn’t produce a nation of starving unemployed farm laborers — it freed up 33% of household income to be spent on automobiles, television sets, air conditioning, healthcare, education, travel, smartphones, and streaming services, most of which didn’t exist as industries in 1900. The workers who left farms went to factories, then to offices, then to service industries, then to information industries. The economy didn’t run out of work. It metamorphosed.