Podbit · The Bulwark Podcast
An Anthropic economist's paper concluded it is mathematically optimal — using log utility — to accept a 1-in-3 chance of ending all human existence for a 2-in-3 chance of raising living standards by a factor of 55. This is not a philosophy thought experiment; it's a paper from the company building leading AI systems.
NV Energy is abandoning 50,000 residents in the Lake Tahoe area after May 2027, redirecting electricity to data centers in North Las Vegas. Data centers are reportedly lying about how much power they'll consume, and the people paying the price live in low-income, low-population areas.
WiFi signals bounce off walls and anything that interferes with the signal can be mapped — meaning the military and potentially others can see outlines of objects and people in a room. The guys wonder if this means someone can see their dicks.
European Commission President Ursula von der Leyen is expected to propose EU-wide legislation banning social media access for children under 16, calling out platforms for treating kids' attention as a commodity. Australia tried a similar ban first, but enforcement has been a challenge.
The AI industry privately acknowledges a 70% chance that building superintelligence ends in something like human extinction or catastrophic loss of control. This isn't fringe doomerism — it's the quiet consensus inside the labs, and the companies have strong incentives not to say it out loud.
When Kokotajlo says 70%, he doesn't just mean human extinction. He means any catastrophic outcome where AI has taken over: maybe they don't kill everyone, but they stop obeying orders. The core danger is that AI alignment looks like it's solved when it isn't, and by the time you find out, it's too late.
Sam Altman, Dario Amodei, and Elon Musk are not racing for profit — they're racing because they are genuinely afraid that whichever rival gets to superintelligence first could become a global dictator. Each one has convinced themselves they need to win, because none of them trust the others.
Modern AI is not lines of code — it's a neural net with up to 10 trillion parameters, trained by positive and negative reinforcement the same way the human brain learns. Pre-training teaches it to predict text; then specific tasks like coding get layered on top. The whole thing is basically an artificial brain, but one that no human can look inside and understand.
AI 2027 maps a month-by-month trajectory: companies automate coding, then the full research loop, then achieve recursive self-improvement, integrate with government and military, and deploy everywhere. Eventually, the AIs have accumulated enough real-world power that they stop listening to orders. Insiders told Kokotajlo his timeline was too aggressive. Now they tell him it's basically right.
Geoffrey Hinton noted to Steven Bartlett that there is no example in nature of a more intelligent species being subordinate to a less intelligent one. Kokotajlo agrees this should be our default assumption: we are building something smarter than us, giving it a body, letting it improve itself, and then assuming it will keep taking our orders.
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