[Draft] It is really hard to communicate the level/strength of basically anything on a sliding scale, but especially things that could not make any intuitive sense even if you stated a percentage. One recent example I encountered is expressing what is in my mind the optimal tradeoff between reading quickly and thinking deeply to achieve the best learning efficiency.
Not sure what is the best way to deal with the above example, and other situations where percentage doesn’t make sense.
But where percentage makes sense, there are still two annoying problems. 1. sometimes you don’t have (haven’t generated) a fixed percentage in your mind. 2. You still need to express the uncertainty of that percentage. (vague example: 70% +- 20% vs 70% +- 5%).
I think it could be worth it to establish a common knowledge for what percentages do the uncertainty-hinting keywords represent. Say, “seems like” = 75% +- 30%
Unsorted Ideas Below
A lot of people don’t seem to realise this problem because their models are too black and white.
It is more difficult to communicate that the other person is being slightly too confident, than to tell them that they are way too overconfident.
For most topics, it’s probably not worth going very deep in the rabbit hole of “what does a probability mean in this context”. Yes, there are multiple kinds of uncertainty, and multiple kinds of ratio that can be expressed by a percentage. Yes, almost everything is a distribution, most not normal, and even when normal it’s not generally specified what the stddev is. Yes, probability is causally recursive (the probability that your model is appropriate causes uncertainty in the ground-level probability you hold). None of that matters, for most communication. When it does, then it’s probably best to acknowledge it and give the details that go into your beliefs, rather than the posterior belief itself.
For your example, the tradeoff between fast and careful, I doubt it can be formalized that way, even if you give yourself 10 dimensions of tradeoff based on context. “Slow is smooth, smooth is fast” is the classic physical training adage, and I can’t think of a numeric representation that helps.
[Draft] It is really hard to communicate the level/strength of basically anything on a sliding scale, but especially things that could not make any intuitive sense even if you stated a percentage. One recent example I encountered is expressing what is in my mind the optimal tradeoff between reading quickly and thinking deeply to achieve the best learning efficiency.
Not sure what is the best way to deal with the above example, and other situations where percentage doesn’t make sense.
But where percentage makes sense, there are still two annoying problems. 1. sometimes you don’t have (haven’t generated) a fixed percentage in your mind. 2. You still need to express the uncertainty of that percentage. (vague example: 70% +- 20% vs 70% +- 5%).
I think it could be worth it to establish a common knowledge for what percentages do the uncertainty-hinting keywords represent. Say, “seems like” = 75% +- 30%
Unsorted Ideas Below
A lot of people don’t seem to realise this problem because their models are too black and white.
It is more difficult to communicate that the other person is being slightly too confident, than to tell them that they are way too overconfident.
For most topics, it’s probably not worth going very deep in the rabbit hole of “what does a probability mean in this context”. Yes, there are multiple kinds of uncertainty, and multiple kinds of ratio that can be expressed by a percentage. Yes, almost everything is a distribution, most not normal, and even when normal it’s not generally specified what the stddev is. Yes, probability is causally recursive (the probability that your model is appropriate causes uncertainty in the ground-level probability you hold). None of that matters, for most communication. When it does, then it’s probably best to acknowledge it and give the details that go into your beliefs, rather than the posterior belief itself.
For your example, the tradeoff between fast and careful, I doubt it can be formalized that way, even if you give yourself 10 dimensions of tradeoff based on context. “Slow is smooth, smooth is fast” is the classic physical training adage, and I can’t think of a numeric representation that helps.