The human extinction due to would be "hard takeoff" of an AGI should be understood as a thought experiment, conceived in a specific age when the current connectionist paradigm wasn't yet mainstream. The AI crisis was expected to come from some kind of "hard universal algorithmic artificial intelligence", for example AIXItl undergoing a very specific process of runaway self-optimization.

Current-generation systems aka large connectionist models trained via gradient descent simply don't work like that: they are large, heavy, continuous, the optimization process giving rise to them does so in smooth iterative manner. Before hypothetical "evil AI" there will be thousands of iterations of "goofy and obviously erroneously evil AI", with enough time to take some action. And even then, current systems including this one are more often than not trained with predictive objective, which is very different compared to usually postulated reinforcement learning objective. Systems trained with prediction objective shouldn't be prone to becoming agents, much less dangerous ones.

If you read Scott's blog, you should remember the prior post where he himself pointed that out.

In my honest opinion, unaccountable AGI owners pose multiple OOM more risk than alignment failure of a hypothetical AI trying to predict next token.

We should think more about the Human alignment problem.