This makes me sad, but I’m not sure there’s a real solution here.
Once the AI is doing most of the work, there are AI debate and formal verificationschemes which might help. This of course assumes we’ve solved alignment and many other issues.
I agree. “I worked really hard on it” is neither necessary nor sufficient for research quality. We already know that lots of careful-looking, labor-intensive, neatly written work can still be wrong or non-replicable. Meanwhile, some valuable insights emerge from relatively simple “aha” moments, and some deep ideas are developed more clearly outside the formal journal pipeline (ex: The Bitter Lesson).
Instead of reverting back to the old imperfect proof-of-work proxy for truth, we should try figuring out how to use these new AI tools to help assess research merit more efficiently.
Granted, some research work will require expensive experiments or other forms of “hard work”, in which case proof-of-work can still function as a useful initial filter.
Once the AI is doing most of the work, there are AI debate and formal verification schemes which might help. This of course assumes we’ve solved alignment and many other issues.
I agree. “I worked really hard on it” is neither necessary nor sufficient for research quality. We already know that lots of careful-looking, labor-intensive, neatly written work can still be wrong or non-replicable. Meanwhile, some valuable insights emerge from relatively simple “aha” moments, and some deep ideas are developed more clearly outside the formal journal pipeline (ex: The Bitter Lesson).
Instead of reverting back to the old imperfect proof-of-work proxy for truth, we should try figuring out how to use these new AI tools to help assess research merit more efficiently.
Granted, some research work will require expensive experiments or other forms of “hard work”, in which case proof-of-work can still function as a useful initial filter.