Utility scaling/translation can mean something if you’re scaling them to normalize the average and standard deviation (or other spreading statistic) of reported marginal utilities in group decisions over time; see my comment above.
ETA: In case it’s not clear, I agree that a choice of scale for your utility function doesn’t mean anything by default, and you’re right to be pointing that out, because people mistaken assume that way too often. But if you scale it with a certain purpose in mind, like group decision making, utility can take on additional meaning.
An example of what I mean: if you and I have to make a series of binary decisions as a two-person team, we could each report, on each decision, what is the marginal utility of option 1 over option 2, using a scale of our own choosing. Reporting marginal utility eliminates the choice of translational constant, but we are still scaling our answers according to some arbitrary choice of unit. However, suppose we expect to make, say, 100 decisions per year. We can make a rule: the absolute values of the marginal utilities you report must add up to less than 1000. In other words, you should choose your units so the average absolute marginal utility you report is around 10, or slightly less. This will result in a certain balance in our decision-making procedure: you can’t claim to care more than me on every decision; we will end up having about the same amount of influence on the outcomes.
But again, this doesn’t mean numerical utilities are intrinsically comparable across individuals. The comparison depends on a choice of scale,.a choice that can be tailored to differing purposes and hence give different meanings to the numerical utilities.
Utility scaling/translation can mean something if you’re scaling them to normalize the average and standard deviation (or other spreading statistic) of reported marginal utilities in group decisions over time; see my comment above.
ETA: In case it’s not clear, I agree that a choice of scale for your utility function doesn’t mean anything by default, and you’re right to be pointing that out, because people mistaken assume that way too often. But if you scale it with a certain purpose in mind, like group decision making, utility can take on additional meaning.
An example of what I mean: if you and I have to make a series of binary decisions as a two-person team, we could each report, on each decision, what is the marginal utility of option 1 over option 2, using a scale of our own choosing. Reporting marginal utility eliminates the choice of translational constant, but we are still scaling our answers according to some arbitrary choice of unit. However, suppose we expect to make, say, 100 decisions per year. We can make a rule: the absolute values of the marginal utilities you report must add up to less than 1000. In other words, you should choose your units so the average absolute marginal utility you report is around 10, or slightly less. This will result in a certain balance in our decision-making procedure: you can’t claim to care more than me on every decision; we will end up having about the same amount of influence on the outcomes.
But again, this doesn’t mean numerical utilities are intrinsically comparable across individuals. The comparison depends on a choice of scale,.a choice that can be tailored to differing purposes and hence give different meanings to the numerical utilities.