I had a worry on similar lines that I was surprised not to see discussed.
I think the obvious objection to using additional precision is that this will falsely convey certainty and expertise to most folks (i.e. those outside the EA/rationalist bubble). If I say to a man in the pub either (A) “there’s a 12.4% chance of famine in Sudan” or (B) “there’s a 10% chance of famine in Sudan”, I expect him to interpret me as an expert in (A) - how else could I get so precise? - even if I know nothing about Sudan and all I’ve read about discussing probabilities is this forum post. I might expect him to take my estimate more seriously than of someone who knows about Sudan but not about conveying uncertainty.
(In philosophy of language jargon, the use of a non-rounded percentage is a conversational implicature that you have enough information, by the standards of ordinary discourse, to be that precise.)
Personally, I think that the post did discuss that objection. In particular, the section “‘False precision’” seems to capture that objection, and then the section “Resilience” suggests Greg thinks that his proposal addresses that objection. In particular, Greg isn’t suggesting saying (A), but rather saying something like (A+) “I think there’s a 12% chance of a famine in South Sudan this year, but if I spent another 5 hours on this I’d expect to move by 6%”.
What I was wondering was what his thoughts were on the possibility of substantial anchoring and false perceptions of certainty even if you adjust A to A+. And whether that means it’d often be best to indeed make the adjustment of mentioning resilience, but to still “round off” one’s estimate even so.
Hmm. Okay, that’s fair, on re-reading I note the OP did discuss this at the start, but I’m still unconvinced. I think the context may make a difference. If you are speaking to a member of the public, I think my concern stands, because of how they will misinterpret the thoughtfulness of your prediction. If you are speaking to other predict-y types, I think this concerns disappears, as they will interpret your statements the way you mean them. And if you’re putting a set of predictions together into a calculation, not only it is useful to carry that precision through, but it’s not as if your calculation will misinterpret you, so to speak.
I had a worry on similar lines that I was surprised not to see discussed.
I think the obvious objection to using additional precision is that this will falsely convey certainty and expertise to most folks (i.e. those outside the EA/rationalist bubble). If I say to a man in the pub either (A) “there’s a 12.4% chance of famine in Sudan” or (B) “there’s a 10% chance of famine in Sudan”, I expect him to interpret me as an expert in (A) - how else could I get so precise? - even if I know nothing about Sudan and all I’ve read about discussing probabilities is this forum post. I might expect him to take my estimate more seriously than of someone who knows about Sudan but not about conveying uncertainty.
(In philosophy of language jargon, the use of a non-rounded percentage is a conversational implicature that you have enough information, by the standards of ordinary discourse, to be that precise.)
Personally, I think that the post did discuss that objection. In particular, the section “‘False precision’” seems to capture that objection, and then the section “Resilience” suggests Greg thinks that his proposal addresses that objection. In particular, Greg isn’t suggesting saying (A), but rather saying something like (A+) “I think there’s a 12% chance of a famine in South Sudan this year, but if I spent another 5 hours on this I’d expect to move by 6%”.
What I was wondering was what his thoughts were on the possibility of substantial anchoring and false perceptions of certainty even if you adjust A to A+. And whether that means it’d often be best to indeed make the adjustment of mentioning resilience, but to still “round off” one’s estimate even so.
Hmm. Okay, that’s fair, on re-reading I note the OP did discuss this at the start, but I’m still unconvinced. I think the context may make a difference. If you are speaking to a member of the public, I think my concern stands, because of how they will misinterpret the thoughtfulness of your prediction. If you are speaking to other predict-y types, I think this concerns disappears, as they will interpret your statements the way you mean them. And if you’re putting a set of predictions together into a calculation, not only it is useful to carry that precision through, but it’s not as if your calculation will misinterpret you, so to speak.