Having 1000 utils is by definition exactly 10 times better than having 100 utils. If this relationship does not hold, you are talking about something other than utils.
I don’t see how that is a response to what I said, so I am probably missing your point entirely. If you’re in the mood to back up some inferential steps, I might appreciate it.
Utils aren’t just another form of currency. They’re a currency that we’ve adjusted the value of so that we’re exactly twice as happy with two utils than with one. Hence if the 1000 utils range is contentment, the 100 utils range can’t possibly really really suck, instead it’s exactly 10 times worse than contentment.
Thinking about them as a currency is in general misleading, since they’re not fungible—what is worth 1 util to you isn’t necessarily worth 1 util to anyone else.
So, by definition, if I’m content with 1000 utils, then given 100 utils I’m a tenth of content. (Cononet?) And being cononet is, again by definition, not bad enough that a 99% chance of it is something I could rationally choose to avoid, even if it meant giving up a 1% chance at being gloriously conthousandt.
Well, OK, if y’all say so. But I don’t understand where those quantitative judgments are coming from.
Put another way: if the range I’m in right now is 1000 utils, and I want to estimate what range I was in during the month after my stroke, when things really really sucked… a state that I would not willingly accept a 99% chance of returning to… well, how do I estimate that?
I mean, I understand that 100 is too high a number, though I don’t know how you calculated that, but what is the right number? 10? 1? −100? −10000? What equations apply?
Imagine this bet: If you win, you’ll get to a point that is twice as good as the one you’re at right now: 2000 utils. If you lose, you’ll be at a point that sucked as much as that post-stroke month. What would the probabilty of winning have to be for you to be indifferent to this bet?
The utility of the awful state is then x in the equation 2000P(w) + x(1 - P(w)) = 1000, where P(w) is the probability of winning.
If x were 100, the bet would be worth taking if it offered odds better than 9 in 19. If you wouldn’t take that bet, x is lower. On this scale, I suspect your utility for x is very, very far below 0.
OK… that question at least makes sense to me. Thank you.
Hm. Would I take, say, a 50% bet along those lines? I flip a coin, heads I have another stroke, tails things suddenly get as much better than they are now as now is better than then. Nope, I don’t take that bet.
A 25% chance? Hm.
No, I don’t take that bet.
A 5% chance? Hmmmmmmmm… that is tempting. And I’ll probably always wonder what-if. But no, I don’t think I take that bet.
A 1% chance? Yeah, OK. I probably take that bet.
So P(w) is somewhere between .01 and .05; probably closer to .01. Call it .015.
I think what I’ve probably just demonstrated is that I’m subject to cognitive biases involving small percentage chances… I think my mind is just rounding 1% to “close enough to zero as makes no difference.”
But, OK, I guess utils can measure biased preferences as well as rational ones. All that matters is that it’s my preference, right, not why it’s my preference.
Ah! That makes far more sense. (That number seemed really implausible, but after triple-checking my math I shrugged my shoulders and went with it.)
OK. So, it no longer seems nearly so plausible that I’d turn down the original bet… it really does help me to have something concrete to attach these numbers to. Thanks.
No, wait. Thinking about this some more, I realize I’m being goofy.
You offered me a series of bets about “twice as good as the one you’re at right now: 2000 utils” vs “a point that sucked as much as that post-stroke month”. I interpreted that as “I have another stroke” vs. “things suddenly get as much better than they are now as now is better than then” and evaluated those bets based on that interpretation.
But that was a false interpretation, and my results are internally inconsistent. If how-things-were-then is −64.5K, then 2000 is not as much better than they are now as now is better than then… they are merely 1/65th better. In which case I don’t accept that bet, after all… a 1% chance of another stroke vs a 99% chance of a 1/65th improvement in my life is not nearly as compelling.
More generally, I accepted the initial statement that the state we labeled 2000 is “twice as good as” the state we labeled 1000, because that seemed to make sense when we were talking about numbers. But now that I’m trying to actually map those numbers to something, it’s less clear to me that it makes sense.
I mean, it follows that my stroke was “-64 times worse” than how things are now, and… well, what does that even mean?
Sorry… I’m not trying to be a pedant here, I’m just trying to make sure I actually understand what we’re talking about, and it’s pretty clear that I don’t.
Yeah, the notion of “twice as good as things are now” doesn’t actually make sense, because utility is only defined up to affine transformations. (That is, if you decided to raise your utility for every outcome by 1000, you’d make the same decisions afterward as you did before; it’s the relative distances that matter, not the scaling or the place you call 0. It’s rather like the Fahrenheit and Celsius scales for temperature.)
But anyway, you can figure out the relative distances in the same way; call what you have right now 1000, imagine some particular awesome scenario and call that 2000, and then figure out the utility of having another stroke, relative to that. For any plausible scenario (excluding things that could only happen post-Singularity), you should wind up again with an extremely negative (but not ridiculous) number for a stroke.
On the other hand, conscious introspection is a very poor tool for figuring out our relative utilities (to the degree that our decisions can be said to flow from a utility function at all!), because of signaling reasons in particular.
Not that I know of. Just a warning not to be too certain of the results you get from this algorithm- your extrapolations to actual decisions may be far from what you’d actually do.
I think what I’ve probably just demonstrated is that I’m subject to cognitive biases involving small percentage chances… I think my mind is just rounding 1% to “close enough to zero as makes no difference.”
Maybe, but I find it easier to fall for the opposite bias, the one known as “There’s still a chance, right?”
(nods) Sadly, my succeptability to rounding very small probabilities up when I want them to be true is not inversely correlated with my succeptability to rounding very small probabilities down when I want to ignore them. Ain’t motivated cognition grand?
I do find that I can subvert both of these failure modes by switching scales, though. That is, if I start thinking in “permil” rather than percent, all of a sudden a 1% chance (that is, a 10 permil chance) stops seeming quite so negligible.
You’re saying that you prefer the option with an expected value of 1000 utils over the option with an expected value of 1100 utils. If we were talking about dollars, you could explain this by saying that you are risk averse, i.e. that the more dollars you have, the less you want each individual dollar. Utils are essentially a measurement of how much you want a particular outcome, so an outcome that is worth 1,000,100 utils is something you want 1000.1 times more than you want an outcome worth 1000 utils. If you don’t want to take this bet, that means you don’t actually want the 1,000,100 outcome enough for it to be worth 1,000,100 utils.
For the purposes of expected utility calculations, don’t think of utils as a measure of happiness; think of them as a measure of the strength of preferences.
(shrug) Sure. As long as I don’t try to understand utils as actually existing in the world, as being interpretable as anything, and I just treat them as numbers, then sure, I can do basic math as well as the next person.
And if all we’re saying is that it’s irrational to think that (.999 100) + (.001 1,000,100) <> 1100, well, OK, I agree with that, and I withdraw my earlier assertion about being utility risk averse. I agree with everyone else; that’s pretty much impossible.
My difficulty arises when I try to unpack those numbers into something real… anything real. But it doesn’t sound like that’s actually part of the exercise.
Having 1000 utils is by definition exactly 10 times better than having 100 utils. If this relationship does not hold, you are talking about something other than utils.
I don’t see how that is a response to what I said, so I am probably missing your point entirely. If you’re in the mood to back up some inferential steps, I might appreciate it.
Utils aren’t just another form of currency. They’re a currency that we’ve adjusted the value of so that we’re exactly twice as happy with two utils than with one. Hence if the 1000 utils range is contentment, the 100 utils range can’t possibly really really suck, instead it’s exactly 10 times worse than contentment.
Thinking about them as a currency is in general misleading, since they’re not fungible—what is worth 1 util to you isn’t necessarily worth 1 util to anyone else.
I understand that part, as far as it goes.
So, by definition, if I’m content with 1000 utils, then given 100 utils I’m a tenth of content. (Cononet?) And being cononet is, again by definition, not bad enough that a 99% chance of it is something I could rationally choose to avoid, even if it meant giving up a 1% chance at being gloriously conthousandt.
Well, OK, if y’all say so. But I don’t understand where those quantitative judgments are coming from.
Put another way: if the range I’m in right now is 1000 utils, and I want to estimate what range I was in during the month after my stroke, when things really really sucked… a state that I would not willingly accept a 99% chance of returning to… well, how do I estimate that?
I mean, I understand that 100 is too high a number, though I don’t know how you calculated that, but what is the right number? 10? 1? −100? −10000? What equations apply?
Imagine this bet: If you win, you’ll get to a point that is twice as good as the one you’re at right now: 2000 utils. If you lose, you’ll be at a point that sucked as much as that post-stroke month. What would the probabilty of winning have to be for you to be indifferent to this bet?
The utility of the awful state is then x in the equation 2000P(w) + x(1 - P(w)) = 1000, where P(w) is the probability of winning.
If x were 100, the bet would be worth taking if it offered odds better than 9 in 19. If you wouldn’t take that bet, x is lower. On this scale, I suspect your utility for x is very, very far below 0.
OK… that question at least makes sense to me. Thank you.
Hm. Would I take, say, a 50% bet along those lines? I flip a coin, heads I have another stroke, tails things suddenly get as much better than they are now as now is better than then. Nope, I don’t take that bet.
A 25% chance? Hm.
No, I don’t take that bet.
A 5% chance? Hmmmmmmmm… that is tempting. And I’ll probably always wonder what-if. But no, I don’t think I take that bet.
A 1% chance? Yeah, OK. I probably take that bet.
So P(w) is somewhere between .01 and .05; probably closer to .01. Call it .015.
I think what I’ve probably just demonstrated is that I’m subject to cognitive biases involving small percentage chances… I think my mind is just rounding 1% to “close enough to zero as makes no difference.”
But, OK, I guess utils can measure biased preferences as well as rational ones. All that matters is that it’s my preference, right, not why it’s my preference.
So, all right. 2000P(w) + x(1 - P(w)) = 1000 ⇒ 2000(.015) + x(1 - .015) = 1000 ⇒ 30 + .985x = 1000 ⇒ x=(1000-30)/.985 = ~985.
OK, cool. So my current condition is 1000 util, and my stroke condition (which really really sucks) is 985 utils.
What does that tell us?
You got your numbers flipped. P(w) is your chance of winning. You want
2000(.985) + x(1 - .985) = 1000 ⇒ 1970 + .015x = 1000 ⇒ x = (1000-1970)/.015 = −64,666.66...
That tells you that you really don’t want to have another stroke. Which is hopefully unsurprising.
Ah! That makes far more sense. (That number seemed really implausible, but after triple-checking my math I shrugged my shoulders and went with it.)
OK. So, it no longer seems nearly so plausible that I’d turn down the original bet… it really does help me to have something concrete to attach these numbers to. Thanks.
And, yeah, that is profoundly unsurprising.
No, wait. Thinking about this some more, I realize I’m being goofy.
You offered me a series of bets about “twice as good as the one you’re at right now: 2000 utils” vs “a point that sucked as much as that post-stroke month”. I interpreted that as “I have another stroke” vs. “things suddenly get as much better than they are now as now is better than then” and evaluated those bets based on that interpretation.
But that was a false interpretation, and my results are internally inconsistent. If how-things-were-then is −64.5K, then 2000 is not as much better than they are now as now is better than then… they are merely 1/65th better. In which case I don’t accept that bet, after all… a 1% chance of another stroke vs a 99% chance of a 1/65th improvement in my life is not nearly as compelling.
More generally, I accepted the initial statement that the state we labeled 2000 is “twice as good as” the state we labeled 1000, because that seemed to make sense when we were talking about numbers. But now that I’m trying to actually map those numbers to something, it’s less clear to me that it makes sense.
I mean, it follows that my stroke was “-64 times worse” than how things are now, and… well, what does that even mean?
Sorry… I’m not trying to be a pedant here, I’m just trying to make sure I actually understand what we’re talking about, and it’s pretty clear that I don’t.
Yeah, the notion of “twice as good as things are now” doesn’t actually make sense, because utility is only defined up to affine transformations. (That is, if you decided to raise your utility for every outcome by 1000, you’d make the same decisions afterward as you did before; it’s the relative distances that matter, not the scaling or the place you call 0. It’s rather like the Fahrenheit and Celsius scales for temperature.)
But anyway, you can figure out the relative distances in the same way; call what you have right now 1000, imagine some particular awesome scenario and call that 2000, and then figure out the utility of having another stroke, relative to that. For any plausible scenario (excluding things that could only happen post-Singularity), you should wind up again with an extremely negative (but not ridiculous) number for a stroke.
On the other hand, conscious introspection is a very poor tool for figuring out our relative utilities (to the degree that our decisions can be said to flow from a utility function at all!), because of signaling reasons in particular.
Certainly. Or, really, much of anything else. Is there a better tool available in this case?
Not that I know of. Just a warning not to be too certain of the results you get from this algorithm- your extrapolations to actual decisions may be far from what you’d actually do.
Maybe, but I find it easier to fall for the opposite bias, the one known as “There’s still a chance, right?”
(nods) Sadly, my succeptability to rounding very small probabilities up when I want them to be true is not inversely correlated with my succeptability to rounding very small probabilities down when I want to ignore them. Ain’t motivated cognition grand?
I do find that I can subvert both of these failure modes by switching scales, though. That is, if I start thinking in “permil” rather than percent, all of a sudden a 1% chance (that is, a 10 permil chance) stops seeming quite so negligible.
Huh, that’s a pretty neat hack!
So, let’s say you have 1000 utils when you are offered the bet that Perplexed proposed. You have two possible choices:
You don’t take the bet. You continue to possess 1000 utils with probability 1. Expected value: 1000.
You take the bet.
There is a .999 probability that you will lose and be left with 100 utils.
There is a .001 probability that you will win, giving you a total of 1,000,100 utils.
Expected value: (.999 * 100) + (.001 * 1,000,100) = 1100.
You’re saying that you prefer the option with an expected value of 1000 utils over the option with an expected value of 1100 utils. If we were talking about dollars, you could explain this by saying that you are risk averse, i.e. that the more dollars you have, the less you want each individual dollar. Utils are essentially a measurement of how much you want a particular outcome, so an outcome that is worth 1,000,100 utils is something you want 1000.1 times more than you want an outcome worth 1000 utils. If you don’t want to take this bet, that means you don’t actually want the 1,000,100 outcome enough for it to be worth 1,000,100 utils.
For the purposes of expected utility calculations, don’t think of utils as a measure of happiness; think of them as a measure of the strength of preferences.
(shrug) Sure. As long as I don’t try to understand utils as actually existing in the world, as being interpretable as anything, and I just treat them as numbers, then sure, I can do basic math as well as the next person.
And if all we’re saying is that it’s irrational to think that (.999 100) + (.001 1,000,100) <> 1100, well, OK, I agree with that, and I withdraw my earlier assertion about being utility risk averse. I agree with everyone else; that’s pretty much impossible.
My difficulty arises when I try to unpack those numbers into something real… anything real. But it doesn’t sound like that’s actually part of the exercise.