I don’t think this is quite right, for reasons related to this post.
Sometimes a hypothesis can be “too strong” or “too weak”. Sometimes hypotheses can just be different. You mention the 2-4-6 task and the soda task. In the soda task, Hermoine makes a prediction which is “too strong” in that it predicts anything spilled on the robe will vanish; but also “too weak” in that it predicts the soda will not vanish if spilled on the floor. Actually, I’m not even sure if that is right. What does “too strong” mean? What is a maximally strong or weak hypothesis? Is it based on the entropy of the hypothesis?
I think this mis-places the difficulty in following Eliezer’s “twisty thinking” advice. The problem is that trying to disconfirm a hypothesis is not a specification of a computation you can just carry out. It sort of points in a direction; but, it relies on my ingenuity to picture the scenario where my hypothesis is false. What does this really mean? It means coming up with a second-best hypothesis and then finding a test which differentiates between the best and second best. Similarly, your “too strong” heuristic points in the direction of coming up with alternate hypotheses to test. But, I claim, it’s not really about being “too strong”.
What I would say instead is your test should differentiate between hypotheses (the best hypotheses you can think of; formally, your test should have maximal VIO). The bias is to test your cherished hypothesis against hypotheses which already have a fairly low probability (such as the null hypothesis, perhaps), rather than testing it against the most plausible alternatives.
Just letting you know that after a couple days of thinking about it, I’ve completely come around to your point of view. Figuring out the next best hypothesis that explains all your current data is a much more general approach. It covers so many cases that I even thought of it as the “key to rationality” for a few hours.
I agree, it is the key to rationality. :) I got the idea from Heuer’s CIA debiasing guide, Psychology of Intelligence Analysis. Or rather, from someone at a LW meetup who got it from that guide. An older source is the essay The Method of Multiple Working Hypotheses. Both sources give more detail on the breadth of this idea.
Thanks for the comment! Yeah, “too strong” is mostly a suggestive phrase for figuring out what to test next. But somehow it works better than it has any right to. For example:
Hermione makes a prediction which is “too strong” in that it predicts anything spilled on the robe will vanish; but also “too weak” in that it predicts the soda will not vanish if spilled on the floor.
Let’s just chase the “too strong” angle in the ordinary English sense, without thinking about it too deeply. You spill something else on your robe and it doesn’t vanish, so you come up with the next hypothesis—that the unique combination of robe and soda is doing the trick. That hypothesis also sounds “too strong” somehow, and the obvious test is to try spilling the soda on the floor. Then the soda vanishes and you have your answer.
I don’t think this is quite right, for reasons related to this post.
Sometimes a hypothesis can be “too strong” or “too weak”. Sometimes hypotheses can just be different. You mention the 2-4-6 task and the soda task. In the soda task, Hermoine makes a prediction which is “too strong” in that it predicts anything spilled on the robe will vanish; but also “too weak” in that it predicts the soda will not vanish if spilled on the floor. Actually, I’m not even sure if that is right. What does “too strong” mean? What is a maximally strong or weak hypothesis? Is it based on the entropy of the hypothesis?
I think this mis-places the difficulty in following Eliezer’s “twisty thinking” advice. The problem is that trying to disconfirm a hypothesis is not a specification of a computation you can just carry out. It sort of points in a direction; but, it relies on my ingenuity to picture the scenario where my hypothesis is false. What does this really mean? It means coming up with a second-best hypothesis and then finding a test which differentiates between the best and second best. Similarly, your “too strong” heuristic points in the direction of coming up with alternate hypotheses to test. But, I claim, it’s not really about being “too strong”.
What I would say instead is your test should differentiate between hypotheses (the best hypotheses you can think of; formally, your test should have maximal VIO). The bias is to test your cherished hypothesis against hypotheses which already have a fairly low probability (such as the null hypothesis, perhaps), rather than testing it against the most plausible alternatives.
Just letting you know that after a couple days of thinking about it, I’ve completely come around to your point of view. Figuring out the next best hypothesis that explains all your current data is a much more general approach. It covers so many cases that I even thought of it as the “key to rationality” for a few hours.
I agree, it is the key to rationality. :) I got the idea from Heuer’s CIA debiasing guide, Psychology of Intelligence Analysis. Or rather, from someone at a LW meetup who got it from that guide. An older source is the essay The Method of Multiple Working Hypotheses. Both sources give more detail on the breadth of this idea.
Maybe we should have a post spelling out how much of rationality is covered by this. It’s not widely understood here.
Thanks for the comment! Yeah, “too strong” is mostly a suggestive phrase for figuring out what to test next. But somehow it works better than it has any right to. For example:
Let’s just chase the “too strong” angle in the ordinary English sense, without thinking about it too deeply. You spill something else on your robe and it doesn’t vanish, so you come up with the next hypothesis—that the unique combination of robe and soda is doing the trick. That hypothesis also sounds “too strong” somehow, and the obvious test is to try spilling the soda on the floor. Then the soda vanishes and you have your answer.
So her tests weren’t “powerful” enough to “prove” her hypothesis.