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I don't think this is a good objection. Numbers are often approximate. 20% means 'somewhere between 10% and 30%' as much as 'around a hundred pounds' might mean '75-125 pounds'. On the other hand, I usually think it's better to actually say what ideas and conditionals inform your judgement rather than just saying a number, and I'm not sure what the number adds to the former.
There is some deep epistemological stuff operating here.
If the complaint is that numbers are too "precise", and the solution is to add ranges (whether implicit or explicit), the obvious next question is what these ranges mean.
In formal Bayesian epistemology, there are no "error bars" around probability estimates. The probability estimate is simply the probability you believe X will occur, which can be computed using Bayes formula and a prior probability in simple cases (more complicated cases yield more complicated formulas).
In less Bayesian epistemology, you can recapture much of this using something like proper scoring rules, but, again, a scoring rule only asks for a number - not a range, so it's still unclear what it even means to say "somewhere between 10% and 30%".
In human language, you might want to say something like "I'm saying 20%, but that's because I've consulted the important evidence, but I know there is smaller evidence I'm not considering that might tweak that ±10pp." In this case, you are using error bars to indicate logical uncertainty.
Alternatively, there is a decent analogue in finance: market makers often have both buy and sell limit orders. The spread between them is an indicator of confidence. Note: in finance, the spread is useful only because finance is a fundamentally social endeavor. If you choose to offer a very small spread, what you're really doing is saying that you don't think anyone else can do better than you. [note: this is less true for non-market-makers, who, for binary instruments mostly just care about point estimates].
The financial framing has an obvious betting analogy here: when you say "between 10% and 30%" under this interpretation, you're actually saying is that you would accept a bet that X is true if the odds given were higher than 9:1 and that X is false if the odds were better than 7:3. If we wanted to formalize error bars on probability, this is the model I would advocate for.
[To be a tad pedantic, finance also cares about risk. If I'm market making, I might actually have multiple buy and sell limit orders with different volumes. Likewise, me saying "between 10% and 30%" might mean I'm willing to bet 1¢ at those odds, but it doesn't necessarily imply I'm willing to bet half my 401k.]
@Gillitrut
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The numbers at least for me give me a ballpark estimate of what I think will actually happen given a certain set of conditions. If I say 25% (which in my mind is generally within 10% of the number I give) that communicates in a way that “low probability” doesn’t because “low” doesn’t mean anything. My low might be 25%, your low might be 5%. And making decisions, in a group setting especially, requires precision so that when weighing options you can know with some degree of certainty what people think are likely and unlikely and to what degree. This allows you to discuss whether an X% (+/-10%) risk of something happening being serious enough to make that decision a bad idea. If low can mean anything between 5% and 35%, it’s going to cause people to either overestimate the risk and be too cautious, or underestimate it and take risks that they might not take otherwise.
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My point is that it's important to make that uncertainty explicit because not everyone talking to you is going to understand that. Maybe you think 20% is shorthand for 10-30% but someone else thinks it's precisely 20% or is actually 15-25% or some other range. I think the "around a hundred pounds" is a good example because "around" conveys a degree of uncertainty on the "hundred pounds." If I was quoted a price of some good at "a hundred pounds" (no "around") and later found out it was actually 125 I would feel like I was deceived.
Probability already inherently indicates uncertainty though! You can just say you're combining the different 'levels' of uncertainty (what that means is debatable), and the average of [10..30] is 20.
But the average of [5..35] and [0..40] are also 20. Do you think all three of these ranges are conveying the same information because their average is 20? I don't.
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