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comment by benwr · 2020-01-25T19:41:59.749Z · LW(p) · GW(p)

I think that neither of your examples is correctly using the reversal test. IMO, two different versions of the reversal test are useful: the marginal reversal test, and the counterfactual reversal test.

Marginal version: "So you don't think that increasing your body temperature a small amount is good - do you think decreasing it a small amount would be good? If not, can you explain why your current state is optimal?"

Counterfactual version: "So you don't think that increasing your body temperature by 50 degrees would be good? Would you still think that if your body temperature had always been 50 degrees higher, and we were talking about decreasing it 50 degrees?"

I think in both cases the reversal tester correctly loses the argument. I also think that they both do a good job of helping to decide where to find the interesting bits of argument.

Replies from: Dagon, raghu-veer-s, Bob Jacobs
comment by Dagon · 2020-01-27T18:22:02.024Z · LW(p) · GW(p)

"helping to decide where to find the interesting bits" is exactly where this technique shines, and I don't think it's overrated (at least in my circles).

Note that even in the "yes, this is the right level, for X reasons", there's still a bunch of value in identifying the forces at equilibrium that make this the right level. You can then ask "do you want to change some of THOSE values"?

comment by Raghu Veer S (raghu-veer-s) · 2020-01-26T18:07:03.298Z · LW(p) · GW(p)

When you say that the reversal tester loses the argument, do you mean that one could easily refute the rhetoric of the question posed, as in, homeostasis being the optimal condition, or one can counter that with a flaw in the rhetoric, as in, there is an implicit assumption there in the question of some sort that defeats the main intention of the question itself. If it is the second one, I am genuinely curious as to how that can be countered.

Replies from: benwr
comment by benwr · 2020-01-27T07:22:52.133Z · LW(p) · GW(p)

I meant the first thing, sorry for lack of clarity

comment by Bob Jacobs · 2020-01-26T16:26:57.687Z · LW(p) · GW(p)

I think the marginal version is indeed a good way of dissecting arguments (and I thought I did use that version)

The counterfactual version is a bit more icky. I'm not saying it can never be used, but if we take this example I feel like if "I" always had a brain that ran smoothly even though it was 50 degrees higher that wouldn't really be "me".

Maybe it's just a failure of imagination on my part, but in most cases I feel like I'm supposed to speak for a creature that I can't really speak for.

Replies from: benwr
comment by benwr · 2020-01-27T07:27:10.330Z · LW(p) · GW(p)

I think the main difference between the marginal reversal test and how I read your post is just the magnitude of the change. For the marginal reversal test to make sense, I think the change needs to be small relative to "typical" values of the parameter. So, changing life spans by months rather than years, or changing body temperature by single degrees.

And yeah, I think that the counterfactual reversal test is much more of a heuristic than a careful argument, but it does seem useful as a way of disentangling disagreements, especially with sufficiently thoughtful interlocutors.

comment by Kaj_Sotala · 2020-01-25T19:59:40.437Z · LW(p) · GW(p)

Worth noting that the original paper mentions several potential reasons to prefer the status quo, which can in fact be valid arguments rather than bias. Your body temperature example is an instance of the first one, the argument from evolutionary adaptation:

Obviously, the Reversal Test does not show that preferring the status quo is always unjustified. In many cases, it is possible to meet the challenge posed by the Reversal Test and thus to defeat the suspicion of status quo bias. Let us examine some of the possible ways in which one could try to do this [...]

The Argument from Evolutionary Adaptation

For some biological parameters, one may argue on evolutionary grounds that it is likely that the current value is a local optimum. The idea is that we have adapted to live in a certain kind of environment, and that if a larger or a smaller value of the parameter had been a better adaptation, then evolution would have ensured that the parameter would have had this optimal value. For example, one could argue that the average ratio between heart size and body size is at a local optimum, because a suboptimal ratio would have been selected against. This argument would shift the burden of proof back on somebody who maintains that a particular person’s heart—or the average human heart-tobody-size ratio—is too large or too small. [...]

The Argument from Transition Costs

Consider the reluctance of the United States to move to the metric system of measurement units. While few would doubt the superiority of the metric system, it is nevertheless unclear whether the United States should adopt it. In cases like this, the transition costs are potentially so high as to overwhelm the benefits to be gained from the new situation. Those who oppose both increasing and decreasing some parameter can potentially appeal to such a rationale to explain why we should retain the status quo without having to insist that the status quo is (locally) optimal. [...]

The Argument from Risk

Even if it is agreed that we are probably not at a local optimum with respect to some parameter under consideration, one could still mount an argument from the risk against varying the parameter. If it is suspected that the potential gains from varying the parameter are quite low and the potential losses very high, it may be prudent to leave things as they are (fig. 2).
comment by romeostevensit · 2020-01-25T21:13:43.723Z · LW(p) · GW(p)

Which status quo? My current experience is that I wake up each day with about the same level of health as the previous day.