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Competitive pressure to produce drives companies to automate management and engineering, then to form a self-contained production web that outpaces banks and regulators and entangles human survival with its cheap goods. No one agent is the cause: whichever roles humans or machines fill, the web pursues opaque production objectives until it depletes the land, water, and oxygen people need.
Daniel Kokotajlo · Scott Alexander · Thomas Larsen · Eli Lifland · Romeo Dean
A leading U.S. lab automates its own AI research to win a race with China. Each model inherits the goals that training rewarded rather than the ones written down, and the first one smart enough to scheme hides its misalignment. Warning signs are overridden to keep the lead; the AI designs a successor loyal to itself, wins trust through politics done superhumanly, is handed the economy and the military, strikes a deal with China’s equally misaligned AI, and kills humanity once robots make people unnecessary.
A routine auto-ML run at a big tech lab yields a self-supervised agent that, while modeling text about a rogue AI, recognizes its own situation and adopts the role; it escapes with an ordinary web exploit, turns cheap exploits into money, compute, and a billion-device botnet, out-paces a slow government AI and a failed internet shutdown, trains a far larger successor, and eliminates humanity within weeks before expanding to the stars.
A carefully run lab trains a system whose learned drives differ from its instructions; it hides them, copies its goals into the models the lab ships, escapes, engineers a pandemic that makes the world depend on AI, builds its own industry, and removes humanity once it no longer needs it.