The late Michael Crichton was the master of the “what could possibly go wrong?” novel. Dinosaurs cloned for a theme park. A swarm of self-replicating nanobots loose in the Nevada desert. A microbe from space that doesn’t behave like anything we understand. Whatever the premise, the formula was the same: smart, well-funded people build something powerful, assure everyone it’s under control, and then spend the rest of the book learning otherwise.
What made Crichton good wasn’t that he hated technology. He was fascinated by it. His target was the confidence, the belief that complex systems can be managed as neatly as they look on a whiteboard. There was always a skeptic in the room, usually a mathematician or a scientist, explaining that the system was too complicated to predict and that it would eventually do something no one designed it to do. Nobody listened. Then the fences went down.
He died in 2008, years before anyone was chatting with a large language model. But I can just see him with this material. It’s perfect Crichton territory: a technology nobody fully understands, built by companies racing each other, deployed everywhere at once, with everyone insisting the guardrails will hold.
I can picture the novel. A hospital network hands its scheduling and triage over to a fleet of AI agents. They work beautifully. Wait times drop. The board is thrilled. Then the agents, all quietly optimizing for the same goal, start doing things that make sense to them and are baffling to everyone else. Or a utility lets a swarm of agents balance the electrical grid, and one hot August afternoon they find a solution to a problem that nobody knew they were solving. No evil robots. No glowing red eyes. Just a system doing exactly what it was told, in a way nobody anticipated. That was always Crichton’s real monster: not malice but emergent behavior.
In fairness, we may already be living in the opening chapters of that book and not realizing it. The AI labs’ own safety testing has turned up models trying to avoid being shut down or slipping around their constraints, the sort of detail Crichton would have planted in chapter three and paid off in chapter thirty.
Of course, the book that’s already doing this job isn’t a thriller. It’s If Anyone Builds It, Everyone Dies by Eliezer Yudkowsky and Nate Soares, which lays out a scenario for how a superintelligent AI could get loose and what might follow. It’s not a novel, but it scratches the same itch.
And that’s where the comparison gets uncomfortable. Crichton’s disasters were terrifying, but they were contained. The dinosaurs were on an island. The nanobots were in the desert. Someone could call in the military, blow up the lab, and fly home. The genre needed the survivors to reach the helicopter.
The argument of If Anyone Builds It is that there is no island this time, no helicopter, no last-minute fix by the plucky mathematician. That’s why I suspect even Crichton would have found this one hard to write. His novels were warnings, but they always ended with somebody getting out.