algekalipso

Consciousness researcher and co-founder of the Qualia Research Institute. I blog at qualiacomputing.com

Core interests span - measuring emotional valence objectively, formal models of phenomenal space and time, the importance of phenomenal binding, models of intelligence based on qualia, and neurotechnology.

algekalipso's Comments

What are the key ongoing debates in EA?

Whether avoiding *extreme suffering* such as cluster headaches, migraines, kidney stones, CRPS, etc. is an important, tractable, and neglected cause. I personally think that due to the long-tails of pleasure and pain, and how cheap the interventions would be, focusing our efforts on e.g. enabling cluster headaches sufferers to access DMT would prevent *astronomical amounts of suffering* at extremely low costs.

The key bottleneck here might be people's ignorance of just *how bad* these kinds of suffering are. I recommend reading the "long-tails of pleasure and pain" article linked above to get a sense of why this is a reasonable interpretation of the situation.

Logarithmic Scales of Pleasure and Pain (@Effective Altruism NYC)

Thank you! I just left a reply to your comment. Here's a summary of the core claim:

In this account, the fact that people would naturally and spontaneously use a logarithmic scale to report their level of pain is a simple implication of the fact that you can only definitively tell that "the pain got worse" when it got 10% worse and not when it became 1 unit worse (which soon becomes hard to notice when you talk about experiences with e.g. 1000 pain units per second).
Logarithmic Scales of Pleasure and Pain: Rating, Ranking, and Comparing Peak Experiences Suggest the Existence of Long Tails for Bliss and Suffering

Hey Michael,

Thank for commenting. First of all I agree that the claims of (A) and (B) do need to be distinguished, and I admit I didn't make that conceptual distinction very clear in the article. I agree that the most important takeaway from the piece is (B), and I also think that this alone is already enough to challenge EA's prioritization methods (i.e. ultra-painful experiences are completely flying under the radar from the point of view of QALYs and similar metrics; reducing the incidence of cluster headaches, migraines, kidney stones, etc. could be an extremely cost-effective EA objective).

With that said, I would claim that (1) the article does actually provide evidence for (A), (2) taking this seriously clarifies a lot of puzzling facts about experience and how it is reported, and (3) understanding that pain and pleasure follows a long-tail (most likely a log-normal distribution) gives us a new principled way to approach cause prioritization.

I understand the fact that the pain scales of stings and cluster headaches are *by construction* logarithmic. But you have to understand that such a scale would only ever be "filled to the top" if experiences actually differed in intensity also by the same amount. The article (and presentation, which I strongly recommend you watch) explain that all of the following are consistent with the pain scales (as reported!) are actually logarithmic:

(a) the characteristic distribution of neural activity is log-normal, and under the modest assumption that intensity of experience is roughly proportional (or at least polynomially proportional) to intensity of experience, that entails the distribution of intensity is also log-normal.

(b) the above can be further understood as a kind of "neuronal weather" (see the "avalanches" metaphor in the video presentation)

(c) the predictions of the log-normal world are held by the data, and in particular:

(c1) there are few categories of experiences that capture most of the extremely good and extremely bad sensations

(c2) there is consistency in the deference judgements of the quality of experience (as seen in the deference graph), and importantly

(c3) The ratio of "1st worst or best experience vs. 2nd worst or best experience" fits a log-normal distribution and it does not fit a normal distribution.

For the above reasons, bringing up the Fechner-Weber is not, I would claim, a red-herring. Rather, I think it ties together the whole argument. Here is why:

I understand that Fechner-Weber's law maps physical intensity to subjective intensity, and that valence is not externally driven a lot of the time. But you may have missed the argument I'm making here. And that is that in one interpretation of the law, a pre-conscious process does a log transform on the intensity of the input and that by the time we are aware of it, what we become aware of are the linear differences in our experience. In the alternate interpretation of the law, which I propose, the senses (within the window of adaptation) translate the intensity of the input into an equivalent intensity of experience. And the reason *why* we can only detect multiplicative differences in the input *is because* we can only notice consciously multiplicative differences in the intensity of experience. Do you see what I am saying? In this account, the fact that people would naturally and spontaneously use a logarithmic scale to report their level of pain is a simple implication of the fact that you can only definitively tell that "the pain got worse" when it got 10% worse and not when it became 1 unit worse (which soon becomes hard to notice when you talk about experiences with e.g. 1000 pain units per second).

In other words, the scales are logarithmic because we can only notice with confidence multiplicative increments in the intensity of experience. And while this is fine and does not seem to have strong implications on the lower end of the scale, it very quickly escalates, to the point where by the time you are in 7/10 pain you live in a world with orders of magnitude more pain units per second than you did when you were in 2/10 pain.

Finally, you really need the logarithmic scales to make room for the ultra-intense levels of pleasure and pain that I highlighted in the "existence of extremes" section. If people reported their pain on a linear scale, they would quickly run into the problem that they cannot describe even something as painful as a broken bone, let along something like a cluster headache.

Is pain just a signal to enlist altruists?

Thanks for writing this.

How would this model explain Cluster Headaches? They are not particularly more incapacitating than migraines, yet they are (possibly literally*) thousands of times more acutely painful than them. What is the role of this X1000 multiplier on phenomenal pain in such cases? As far as I can tell, in the ancestral environment nobody could have done anything to help you if you were having a Cluster Headache, and your chances of reproduction seem to be the same whether that pain was a thousand times less bad (which would still be VERY bad, but not in the level of ultra-Hellish pain). In particular, other species are known the have Cluster Headaches too, such as cats. So perhaps we should cluster pains into two buckets - those that have social significance and those that don't. I worry that this study will make people dismiss extreme suffering in nonhuman animals, but that should only really apply to socially-useful pains. I suspect that there are many species-specific ultra-painful experiences that we will not discover (and prioritize!) unless we look for them.


*See: https://forum.effectivealtruism.org/posts/gtGe8WkeFvqucYLAF/logarithmic-scales-of-pleasure-and-pain-rating-ranking-and

Cluster Headache Frequency Follows a Long-Tail Distribution

That's a good point, thank you. We should distinguish between lifetime use and current use in future surveys. Perhaps even asking whether "they worked the first time you used them" to see if people who currently use them had a better reaction to their first try relative to those who did try them at some point but do not currently use them.

I would add that other reasons why people might have used them in the past but don't currently include "can't access it now", "too afraid of legal repercussions", and "social stigma". While discontinuing them due to side-effects and lack of effectiveness can make them look more effective than they are among the "use them" group, the other reasons for discontinuation do not have this effect. I don't know what % of past users discontinued for which reason, and that seems like a good thing to find out.

Cluster Headache Frequency Follows a Long-Tail Distribution

Depends on context. In most cases the 'we' refers to my team and I at the Qualia Research Institute. For example: "Since a number of interviews we’ve conducted have shown that even sub-hallucinogenic doses of DMT can abort cluster headaches" refers to QRI (with other members of the research group having conducted such interviews).


I should note that the word is also used in the 'didactic we' sense a number of times (as in "we will explore the era of the dinosaurs together" in a National Geographic documentary).

Logarithmic Scales of Pleasure and Pain: Rating, Ranking, and Comparing Peak Experiences Suggest the Existence of Long Tails for Bliss and Suffering

According to "Right Concentration: A Practical Guide to the Jhanas" by L. Brasington and "The Mind Illuminated" by Culadasa, it is feasible to achieve Jhana states within two years of dedicated practice. This entails a few hours of meditation a day and attending at least one 9-day retreat over the course of this time period. The books explain in detail how to get there in a very practical and no-nonsense way.

I personally have yet to invest that time into this task, but I know that one of the other core members of the Qualia Research Institute, Romeo Stevens, is now able to achieve Jhanas thanks to his meditation practice. I do intend to do this in the near future.

Also, we are looking into doing EEG and fMRI studies on people who can enter those states as a means to test the CDNS approach to valence quantification, which is a core part of our research plan.

Logarithmic Scales of Pleasure and Pain: Rating, Ranking, and Comparing Peak Experiences Suggest the Existence of Long Tails for Bliss and Suffering

2019-09-04 Update: Since posting this I've learned about the Bradley-Terry model for obtaining latent traits based on sets of rankings (https://en.wikipedia.org/wiki/Bradley%E2%80%93Terry_model) and also that there are libraries to do this (e.g. https://pypi.org/project/choix/).

Additionally, I've learned about "extreme value theory", which describes the statistical distribution of extreme values (e.g. https://en.wikipedia.org/wiki/Generalized_extreme_value_distribution) and seen some applications to other long-tail events (see: https://blog.givewell.org/2015/07/13/geomagnetic-storms-using-extreme-value-theory-to-gauge-the-risk/).

I will use those two new key statistical approaches to analyze this pilot dataset and also future iterations of this study (focused more on people who've experienced extremes of valence like cluster headaches or 5-MeO-DMT states). I am currently busy working on a number of other projects critical for the Qualia Research Institute, so doing this is currently on the back-burner (though of course I'm happy to hear if anyone is interested in taking on this challenge as a volunteer project).

Cheers!

Cause X Guide

To zoom in on the "logarithmic scales of pleasure and pain" angle (I'm the author), I would say that this way of seeing the world suggests that the bulk of suffering is concentrated on a small percentage of experiences. Thus, finding scaleable treatments specially for ultra-painful conditions could take care of a much larger percent of the world burden of suffering than most people would intuitively realize. I really think this should be up in the list of considerations for Cause X. Specifically:

An important pragmatic takeaway from this article is that if one is trying to select an effective career path, as a heuristic it would be good to take into account how one’s efforts would cash out in the prevention of extreme suffering (see: Hell-Index), rather than just QALYs and wellness indices that ignore the long-tail. Of particular note as promising Effective Altruist careers, we would highlight working directly to develop remedies for specific, extremely painful experiences. Finding scalable treatments for migraines, kidney stones, childbirth, cluster headaches, CRPS, and fibromyalgia may be extremely high-impact (cf. Treating Cluster Headaches and Migraines Using N,N-DMT and Other Tryptamines, Using Ibogaine to Create Friendlier Opioids, and Frequency Specific Microcurrent for Kidney-Stone Pain). More research efforts into identifying and quantifying intense suffering currently unaddressed would also be extremely helpful.

(see also the writeup of an event we hosted about possible new EA Cause Xs)

Ask Me Anything!

Do you think that the empirical finding that pain and suffering are distributed along a lognormal distribution (cf. Logarithmic Scales of Pleasure and Pain) has implications for how to prioritize causes? In particular, what do you say about these tentative implications:

Of particular note as promising Effective Altruist careers, we would highlight working directly to develop remedies for specific, extremely painful experiences. Finding scalable treatments for migraines, kidney stones, childbirth, cluster headaches, CRPS, and fibromyalgia may be extremely high-impact (cf. Treating Cluster Headaches and Migraines Using N,N-DMT and Other Tryptamines, Using Ibogaine to Create Friendlier Opioids, and Frequency Specific Microcurrent for Kidney-Stone Pain). More research efforts into identifying and quantifying intense suffering currently unaddressed would also be extremely helpful. Finally, if the positive valence scale also has a long-tail, focusing one’s career in developing bliss technologies may pay-off in surprisingly good ways (whereby you may stumble on methods to generate high-valence healing experiences which are orders of magnitude better than you thought were possible).

Thank you!!!

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