If you mean the Hilgard scale, ask a few professional hypnotists how useful it actually is.
I mean the Stanford Hypnotic Susceptibility Scales, the most useful being SHSS:C. Hilgard played his cards poorly and somehow failed to have the scale named after himself. I am more interested in the findings of researchers who study the clinical work of professional hypnotists than I am in the opinions of the hypnotists themselves. Like most commonly used psychological metrics, the SHSS:C is far from perfect. Nevertheless, it does manage to correlate strongly with the success of clinical outcomes, which is the best I can expect of it.
Professional hypnotists also know that responsiveness is a learned process (see also the concept of "fractionation"), which means it's probably a mistake to treat it as an intrinsic variable for measuring purposes, unless you have a way to control for the amount of learning someone has done.
Professional scientists studying hypnosis observe that specific training can alter the hypnotic responsiveness from low to high in as much as 50% of cases. Many have expressed surprise at just how stable the baseline is over time and observe that subjects trained to respond to hypnosis revert to the baseline over time. Nevertheless, such reversion takes time and Gosgard found (in 2004) that a training effect can remain for as much as four months.
So, as far as this particular variable is concerned, you're observing the wrong evidence.
When I began researching hypnosis I was forced to subordinate my preferred belief to what the evidence suggests. When it comes to most aspects of personality and personal psychological profile I much prefer to believe in the power of 'nurture' and my ability to mould my own personality profile to my desires with training. I have become convinced over time that there is a far greater heritability component than I would have liked. On the positive side, the importance of 'natural talent' in aquiring expert skills is one area where the genetic component tends to be overestimated most of the time. When it comes to aquiring specialised skills, consistent effortful practice makes all the difference and natural talent is almost irrelevant.
Personal development is an area where science routinely barks up the wrong tree, because there's a difference between "objective" measurement and maximizing utility. Even if it's a fact that people differ, operating as if that fact were true leads to less utility for everyone who doesn't already believe they're great at something.
There is certainly something to that! I do see the merit in 'operating as if [something that may not necessarily be our best prediction of reality]'. It would be great if there were greater scientific efforts in investigating the most effective personal development strategies.
Professional scientists studying hypnosis observe that specific training can alter the hypnotic responsiveness from low to high in as much as 50% of cases.
Indeed. What's particularly important if you're after results, rather than theories, is that just because those other 50% didn't go from low to high, doesn't mean that there wasn't some different form, approach, environment, or method of training that wouldn't have produced the same result!
IOW, if the training they tested was 100% identical for each person, then the odds that the other 50% were still...
Reply to: Practical Advice Backed By Deep Theories
Inspired by what looks like a very damaging reticence to embrace and share brain hacks that might only work for some of us, but are not backed by Deep Theories. In support of tinkering with brain hacks and self experimentation where deep science and large trials are not available.
Eliezer has suggested that, before he will try a new anti-akraisia brain hack:
This doesn't look to me like an expected utility calculation, and I think it should. It looks like an attempt to justify why he can't be expected to win yet. It just may be deeply wrongheaded.
I submit that we don't "need" (emphasis in original) this stuff, it'd just be super cool if we could get it. We don't need to know that the next brain hack we try will work, and we don't need to know that it's general enough that it'll work for anyone who tries it; we just need the expected utility of a trial to be higher than that of the other things we could be spending that time on.
So… this isn't other-optimizing, it's a discussion of how to make decisions under uncertainty. What do all of us need to make a rational decision about which brain hacks to try?
(can these books be judged by their covers? how does this chance vary with the type of exposure? what would you need to do to understand enough about a hack that would work to increase its chance of seeming deeply compelling on first exposure?)
… and, what don't we need?
How should we decide how much time to spend gathering data and generating estimates on matters such as this? How much is Eliezer setting himself up to lose, and how much am I missing the point?