I would like to suggest that Logarithmic Scales of Pleasure and Pain (“Log Scales” from here on out) presents a novel, meaningful, and non-trivial contribution to the field of Effective Altruism. It is novel because even though the terribleness of extreme suffering has been discussedmultipletimesbefore, such discussions have not presented a method or conceptual scheme with which to compare extreme suffering relative to less extreme varieties. It is meaningful because it articulates the essence of an intuition of an aspect of life that deeply matters to most people, even if they cannot easily put it into words. And it is non-trivial because the inference that pain (and pleasure) scales are better understood as logarithmic in nature does require one to consider the problem from multiple points of view at once that are rarely, if ever, brought up together (e.g. combining empirical deference graphs, descriptions of pain scales by their creators, latent-trait analysis, neural recordings, and psychophysics).
Fundamentally, we could characterize this article as a conceptual reframe that changes how one assesses magnitudes of suffering in the world. To really grasp the significance of this reframe, let’s look back into how Effective Altruism itself was an incredibly powerful conceptual reframe that did something similar. In particular, a core insight that establishes the raison d’etre of Effective Altruism is that the good that you can do in the world with a given set of resources varies enormously depending on how you choose to allocate it: by most criteria that you may choose (whether it’s QALYs or people saved from homelessness), the cost-effectiveness of causes seem to follow much more closely (at least qualitatively) a long-tail rather than a normal distribution (see: Which world problems are the most pressing to solve? by Benjamin Todd; the long-tail on the left below). In turn, this strongly suggests that researching carefully how to invest one’s altruistic efforts is likely to pay off in very large ways: choosing a random charity versus a top 1% charity will lead to benefits whose scale differs by orders of magnitude.
Log Scales suggests that pain and pleasure themselves follow a long-tail distribution. In what way, exactly? Well, to a first approximation, across the entire board! The article (and perhaps more eloquently the subsequent video presentation at the NYC EA Meetup on the same topic) argues that when it comes to the distribution of the intensity of hedonic states, we are likely to find long-tails almost independently of the way in which we choose to slice or dice the data. This is analogous to, for example, how all of the following quantities follow long-tail distributions: avalanches per country, avalanches per mountain, amount of snow in mountains, number of avalanche-producing mountains per country, size of avalanches, number of avalanches per day, etc. Likewise, in the case of the distribution of pain, the arguments presented suggest we will find that all of the following distributions are long-tails: average pain level per medical condition, number of intensely painful episodes per person per year, intensity of pain per painful episode, total pain per person during life, etc. Thus, that such a small percentage of cluster headache patients accounts for the majority of episodes per year would be expected (see: Cluster Headache Frequency Follows a Long-Tail Distribution; the long-tail on the right above), and along with it, the intensity of such episodes themselves would likely follow a long-tail distribution.
This would all be natural, indeed, if we consider neurological phenomena such as pain to be akin to weather phenomena. Log Scales allows us to conceptualize the state of a nervous system and what it gives rise to as akin to how various weather conditions give rise to natural disasters: a number of factors multiply each other resulting in relatively rare, but surprisingly powerful, black swan events. Nervous systems such as those of people suffering from CRPS, fibromyalgia, and cluster headaches are like the Swiss Alps of neurological weather conditions… uniquely suited for ridiculously large avalanches of suffering.
Log Scales are not just of academic interest. In the context of Effective Altruism, they are a powerful generator for identifying new important, neglected, and tractable cause areas to focus on. For instance, DMT for cluster headaches, microdose ibogaine for augmentation of painkillers in sufferers of chronic pain, and chanca piedra for kidney stones (writeup in progress) are all what we believe to be highly promising interventions (of the significant, neglected, and tractable variety) that might arguably reduce suffering in enormous ways and that would not have been highlighted as EA-worthy were it not for Log Scales. (See also: Get-Out-Of-Hell-Free Necklace). On a personal note, I’ve received numerous thank you notes by sufferers of extreme pain for this research. But the work has barely begun: with Log Scales as a lens, we are poised to tackle the world’s reserves of suffering with laser-focus, assured in the knowledge that preventing a small fraction of all painful conditions is all that we need to abolish the bulk of experiential suffering.
But does Log Scales make accurate claims? Does it carve reality at the joints? How do we know?
The core arguments presented were based on (a) the characteristic distribution of neural activity, (b) phenomenological accounts of extreme pleasure and pain, (c) the way in which the creators of pain scales have explicitly described their meaning, and (d) the results of a statistical analysis of a pilot study we conducted where people ranked, rated, and assigned relative proportions to their most extreme experiences. We further framed this in terms of comparing qualitative predictions from what we called the Normal World vs. Lognormal World. In particular, we stated that: “If we lived in the ‘Lognormal World’, we would expect: (1) That people will typically say that their top #1 best/worst experience is not only a bit better/worse than their #2 experience, but a lot better/worse. Like, perhaps, even multiple times better/worse. (2) That there will be a long-tail in the number of appearances of different categories (i.e. that a large amount, such as 80%, of top experiences will belong to the same narrow set of categories, and that there will be many different kinds of experiences capturing the remaining 20%). And (3) that for most pairs of experiences x and y, people who have had both instances of x and y, will usually agree about which one is better/worse. We call such a relationship a ‘deference’. More so, we would expect to see that deference, in general, will be transitive (a > b and b > c implying that a > c).” And then we went ahead and showed that the data was vastly more consistent with Lognormal World than Normal World. I think it holds up.
An additional argument that since has been effective at explaining the paradigm to newcomers has been in terms of exploring the very meaning of Just-Noticeable Differences (JNDs) in the context of the intensity of aspects of one’s experience. Indeed, for (b), the depths of intensity of experience simply make no sense if we were to take a “Just-Noticeable Pinprick” as the unit of measurement and expect a multiple of it to work as the measuring rod between pain levels in the 1-10 pain scale. The upper ends of pain are just so bright, so immensely violent, so as to leave lesser pains as mere rounding errors. But if on each step of a JND of pain intensity we multiply the feeling by a constant, sooner or later (as Zvi might put it) “the rice grains on the chessboard suddenly get fully out of hand” and we enter hellish territory (for a helpful visual aid of this concept: start at 6:06 of our talk at the 2020 EAGxVirtual Unconference on this topic).
From my point of view, we can now justifiably work under the assumption that the qualitative picture painted by Log Scales is roughly correct. It is the more precise quantitative analysis which is a work in progress that ought to be iterated over in the coming years. This will entail broadening the range of people interviewed, developing better techniques to precisely capture and parametrize phenomenology (e.g. see our tool to measure visual tracers), use more appropriate and principled statistical methods (e.g. see the comment in the original piece about the Bradley-Terry model and extreme value theory), experimental work in psychophysics labs, neuroimaging research of peak experiences, and the search for cost-effective pragmatic solutions to deal with the worst suffering. I believe that future research in this area will show conclusively the qualitative claims, and perhaps there will be strong consilience on the more precise quantitative claims (but in the absence of a true Qualiascope, the quantitative claims will continue to have a non-negligible margin of error).
Ok, you may say, but if I disagree about the importance of preventing pain, and I care more about e.g. human flourishing, why should I care about this? Here I would like to briefly address a key point that people in the EA sphere have raised in light of our work. The core complaint, if we choose to see it that way, is that one must be a valence utilitarian in order to care about this analysis. That only if you think of ethics in terms of classical Benthamite pain-minimization and pleasure-maximization should we be so keen on mapping the true distribution of valence across the globe.
But is that really so?
Three key points stand out: First, that imperfect metrics that are proxies for aspects of what you care about (even when not all that you care about) can nonetheless be important. Second, that if you cared a little about suffering already, then the post-hoc discovery that suffering is actually thatfreakingskewed really ought to be a major update. And third, there really are reasons other than valence maximization as a terminal goal to care about extreme suffering: intense suffering is antithetical to flourishing since it has long-term sequelae. More so, even if confined to non-utilitarian ethical theories, one can make the case that there is something especially terrible about letting one’s fellow humans (and non-humans) suffer so intensely without doing anything about it. And perhaps especially so if stopping such horrors turn out to be rather easy, as is indeed the case.
Let’s tackle these points each in turn.
(1) Perhaps here we should bring a simple analogy: GDP. Admittedly, there are very few conceptions of the good in which it makes sense for GDP to be the metric to maximize. But there are also few conceptions of the good where you should disregard it altogether. You can certainly be skeptical of the degree to which GDP captures all that is meaningful, but in nearly all views of economic flourishing, GDP will likely have a non-zero weight. Especially if we find that, e.g. some interventions we can do to the economy would cause a 99.9% reduction in a country’s GDP, one should probably not ignore that information (even if the value one assigns to GDP is relatively small compared to what other economists and social scientists assign it). Likewise for extreme suffering. There might be only a few conceptions of the good where that is the only thing we ought to work on. But avoiding hellish states is a rather universally desired state for oneself. Why not take it at least somewhat into account?
In truth, this is not something that classical questions in Effective Altruism pre-Log Scales couldn’t overcome either. For instance, as far as I am aware, in practice QALYs are used more as a guide than as an absolute; their value within EA comes from the fact that in practice interventions are orders of magnitude different when it comes to their cost-effectiveness when assessed with QALYs. So even though the vast majority of EAs are not QALY absolutists, the differences in QALYs saved between interventions are large enough that as an approximate guide, the metric still generates huge amounts of consilience.
(2) In turn, the post-hoc finding that hellish states are much, much worse than one would intuitively believe really should at least rebalance one’s priorities somewhat. Is there really no amount of suffering that would do so? Unless one has a utility function akin to a ReLu activation function, going far enough down into the depths of hell ought to count for something. And…
(3) Speaking candidly, fully articulating the true significance of this finding will take us to philosophically polemical territory: philosophy of personal identity where person-affecting views will see the situation quite differently than person-moment-affecting views, philosophy of mind where the ontological status of pleasure and pain might be questioned, and intricate questions that arise at the interface between the views of virtue ethicists, deontologists, negative and classical utilitarians. Of course a negative utilitarian who believes in Empty Individualism and Eternalism at the same time will likely be especially horrified by this information. But, with that said, I would suggest that there are good reasons to care about Log Scales no matter how antithetical one’s views are to philosophical hedonism.
In particular, I would argue that deontologists and virtue ethicists should still take note. The cultivation of virtue requires a minimum of wellbeing in order to maintain motivation to live. And perhaps deontologists might find extreme suffering particularly egregious from the point of view of “things so horrible that ought not to be”. Really, the people we interviewed for the cluster headache writeup told us that experiencing such levels of hellish suffering causes profound psychological transformations (e.g. one interviewee told us that experiencing the higher ends of pain in a cluster headache feels like a profound “spiritual violation” from which you may never recover – a feeling most certainly aggravated by the seeming indifference of people at large about their plight). Virtue ethicists and deontologists might as well recognize this cause area as work that is unconscionable not to perform, regardless of arguments based on the precise mathematical optimization of the prevention of negative valence.
And finally, in all seriousness, as the cognitive intelligentsia of the world begins to see clearly the nature of the distribution of pleasure and pain, we can expect there to be a big social benefit to being the one who destroys hell. Right now there isn’t a huge social reward to be obtained by working on this cause, but I predict this will change. And, pragmatically, it is sensible to present this cause in a motivating rather than depressing light: indeed, let’s give honor, glory, and endless admiration to whoever makes tangible progress in tearing hell down. And to all of the millionaires and billionaires reading this: this could be you! You could be the one who took on the mantle of preventing all future cluster headaches, established the field of anti-tolerance drugs for severe chronic pain, or got rid of kidney stones (and you did it before it was cool!). Let’s get to work!
Based on: the characteristic distribution of neural activity, personal accounts of intense pleasure and pain, the way various pain scales have been described by their creators, and the results of a pilot study we conducted which ranks, rates, and compares the hedonic quality of extreme experiences, we suggest that the best way to interpret pleasure and pain scales is by thinking of them as logarithmic compressions of what is truly a long-tail. The most intense pains are orders of magnitude more awful than mild pains (and symmetrically for pleasure).
This should inform the way we prioritize altruistic interventions and plan for a better future. Since the bulk of suffering is concentrated in a small percentage of experiences, focusing our efforts on preventing cases of intense suffering likely dominates most utilitarian calculations.
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. 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).
Why This Matters
The Non-Linearity of Pleasure and Pain
Peak Pleasure States: Jhanas and Temporal Lobe Seizures
Logarithmic Pain Scales: Stings, Peppers, and Cluster Headaches
Deference-type Approaches for Experience Ranking
Normal World vs. Lognormal World
Predictions of Lognormal World
Appearance Base Rates
Deference Graph of Top Experiences
Rebalanced Smoothed Proportion
Latent Trait Ratings
Long-tails in the Responses to “How Many Times Better/Worse” Question
Key Pleasures Surfaced
Birth of Children
Falling in Love
Games of Chance Earnings
Death of Father and Mother
Future Directions for Methodological Approaches
Graphical Models with Log-Normal Priors
Closing Thoughts on the Valence Scale
Dimensionality of Pleasure and Pain
Weber’s Law describes the relationship between the physical intensity of a stimulus and the reported subjective intensity of perceiving it. For example, it describes the relationship between how loud a sound is and how loud it is perceived as. In the general case, Weber’s Law indicates that one needs to vary the stimulus intensity by a multiplicative fraction (called “Weber’s fraction”) in order to detect a just noticeable difference. For example, if you cannot detect the differences between objects weighing 100 grams to 105 grams, then you will also not be able to detect the differences between objects weighing 200 grams to 210 grams (implying the Weber fraction for weight perception is at least 5%). In the general case, the senses detect differences logarithmically.
There are two compelling stories for interpreting this law:
In the first story, it is the low-level processing of the senses which do the logarithmic mapping. The senses “compress” the intensity of the stimulation and send a “linearized” packet of information to one’s brain, which is then rendered linearly in one’s experience.
In the second story, the senses, within the window of adaptation, do a fine job of translating (somewhat) faithfully the actual intensity of the stimulus, which then gets rendered in our experience. Our inability to detect small absolute differences between intense stimuli is not because we are not rendering such differences, but because Weber’s law applies to the very intensity of experience. In other words, the properties of one’s experience could follow a long-tail distribution, but our ability to accurately point out differences between the properties of experiences is proportional to their intensity.
We claim that, at least for the case of valence (i.e the pleasure-pain axis), the second story is much closer to the truth than the first. Accordingly, this article rethinks the pleasure-pain axis (also called the valence scale) by providing evidence, arguments, and datapoints to support the idea that how good or bad experiences feel follows a long-tail distribution.
The concrete line of argument we will present is based on the following:
Phenomenological accounts of intense pleasure and pain (w/ accounts of phenomenal time and space expansion),
The way in which pain scales are described by those who developed them, and
The analytic results of a pilot study we conducted which investigates how people rank, rate, and assign relative proportions to their top 3 best and worst experiences
Why This Matters
Even if you are not a strict valence utilitarian, having the insight that the valence scale is long-tailed is still very important. Most ethical systems do give some weight to the prevention of suffering (in addition to the creation of subjectively valuable experiences), even if that is not all they care about. If your ethical system weighted slightly the task of preventing suffering when believing in a linear valence scale, then learning about the long-tailed nature of valence should in principle cause a major update. If indeed the worst experiences are exponentially more negative than originally believed by one’s ethical system, which nonetheless still cared about them, then after learning about the true valence scale the system would have to reprioritize. We suggest that while it might be unrealistic to have every ethical system refocus all of its energies on the prevention of intense suffering (and subsequently on researching how to create intense bliss sustainably), we can nonetheless expect such systems to raise this goal on their list of priorities. In other words, while “ending all suffering” will likely never be a part of most people’s ethical system, we hope that the data and arguments here presented at least persuade them to add “…and prevent intense forms of suffering” to the set of desiderata.
Indeed, lack of awareness about the long-tails of bliss and suffering may be the cause of an ongoing massive moral catastrophe (notes by Linch). If indeed the degree of suffering present in experiences follows a long-tail distribution, we would expect the worst experiences to dominate most utilitarian calculus. The biggest bang for the buck in altruistic interventions would therefore be those that are capable of directly addressing intense suffering and generating super-bliss.
The Non-Linearity of Pleasure and Pain
True long-tail pleasure scale (warning: psychedelics increase valence variance – the values here are for “good/lucky” trips and there is no guarantee e.g. LSD will feel good on a given occasion). Also: Mania is not always pleasant, but when it is, it can be super blissful.
True long-tail pain scale
As we’ve briefly discussed in previous articles (1, 2, 3), there are many reasons to believe that both pleasure and pain can be felt along a spectrum with values that range over possibly orders of magnitude. Understandably, someone who is currently in a state of consciousness around the human median of valence is likely to be skeptical of a claim like “the bliss you can achieve in meditation is literally 100 times better than eating your favorite food or having sex.” Intuitively, we only have so much space in our experience to fit bliss, and when one is in a “normal” or typical state of mind for a human, one is forced to imagine “ultra blissful states” by extrapolating the elements of one’s current experience, which certainly do not seem capable of being much better than, say, 50% of the current level of pleasure (or pain). The problem here is that the very building blocks of experiences that enable them to be ultra-high or ultra-low valence are themselves necessary to imagine accurately how they can be put together. Talking about extreme bliss to someone who is anhedonic is akin to talking about the rich range of possible color experiences to someone who is congenitally fully colorblind (cf. “What Mary Didn’t Know“).
“Ok”, you may say, “you are just telling me that pleasure and pain can be orders of magnitude stronger than I can even conceive of. What do you base this on?”. The most straightforward way to be convinced of this is to literally experience such states. Alas, this would be deeply unethical when it comes to the negative side, and it requires special materials and patience for the positive side. Instead, I will provide evidence from a variety of methods and conditions.
I’ve been lucky to not have experienced major pain in my life so far (the worst being, perhaps, depression during my teens). I have, however, had two key experiences that gave me some time to introspect on the non-linear nature of pain. The first one comes from when I accidentally cut a super-spicy pepper and touched it with my bare hands (the batch of peppers I was cutting were mild, but a super-hot one snuck into the produce box). After a few minutes of cutting the peppers, I noticed that a burning heat began to intensify in my hands. This was the start of experiencing “hot pepper hands” for a full 8 hours (see other people’s experiences: 1, 2, 3). The first two to three hours of this ordeal were the worst, where I experienced what I rated as a persistent 4/10 pain interspersed with brief moments of 5/10 pain. The curious thing was that the 5/10 pain moments were clearly discernible as qualitatively different. It was as if the very numerous pinpricks and burning sensations all over my hands were in a somewhat disorganized state most of the time, but whenever they managed to build-up for long enough, they would start clicking with each other (presumably via phase-locking), giving rise to resonant waves of pain that felt both more energetic, and more aversive on the whole. In a way, this jump from what I rated as 4/10 to 5/10 was qualitative as well as quantitative, and it gave me some idea of how something that is already bad can become even worse.
My second experience involves a mild joint injury I experienced while playing Bubble Soccer (a very fun sport no doubt, and a common corporate treat for Silicon Valley cognotariats, but according to my doctor it is also a frequent source of injuries among programmers). Before doing physical therapy to treat this problem (which mostly took care of it), I remember spending hours introspecting on the quality of the pain in order to understand it better. It wasn’t particularly bad, but it was constant (I rated it as 2/10 most of the time). What stuck with me was how its constant presence would slowly increase the stress of my entire experience over time. I compared the experience to having an uncomfortable knot stuck in your body. If I had a lot of mental and emotional slack early in the day, I could easily take the stress produced by the knot and “send it elsewhere” in my body. But since the source of the stress was constant, eventually I would run out of space, and the knot would start making secondary knots around itself, and it was in those moments where I would rate the pain at a 3/10. This would only go away if I rested and somehow “reset” the amount of cognitive and emotional slack I had available.
The point of these two stories is to highlight the observation that there seem to be phase-changes between levels of discomfort. An analogy I often make is with the phenomenon of secondary coils when you twist a rope. The stress induced by pain- at least introspectively speaking- is pushed to less stressed areas of your mind. But this has a limit, which is until your whole world-simulation is stressed to the point that the source of stress starts creating secondary “stress coils” on top of the already stressed background experience. This was a very interesting realization to me, which put in a different light weird expressions that chronic pain patients use like “my pain now has a pain of its own” or “I can’t let the pain build up”.
DNA coils and super-coils as a metaphor for pain phase-changes?
What about more extreme experiences? Here we should briefly mention psychedelic drugs, as they seem to be able to increase the energy of one’s consciousness (and in some sense “multiply the amount of consciousness“) in a way that grows non-linearly as a function of the dose. An LSD experience with 100 micrograms may be “only” 50% more intense than normal everyday life, but an LSD experience with 200 micrograms is felt as 2-3X as intense, while 300 micrograms may increase the intensity of experience by perhaps 10X (relative to normal). Usually people say that high-dose psychedelic states are indescribably more real and vivid than normal everyday life. And then there are compounds like 5-MeO-DMT, which people often describe as being in “a completely different category”, as it gives rise to what many describe as “infinite consciousness”. Obviously there is no such thing as an experience with infinite consciousness, and that judgement could be explained in terms of the lack of “internal boundaries” of the state, which gives the impression of infinity (not unlike how the surface of a torus can seem infinite from the point of view of a flatlander). That said, I’ve asked rational and intelligent people who have tried 5-MeO-DMT in non-spiritual settings what they think the intensity of their experiences was, and they usually say that a strong dose of 10mg or more gives rise to an intensity and “quantity” of consciousness that is at least 100X as high as normal everyday experiences. There are many reasons to be skeptical of this, no doubt, but the reports should not be dismissed out of hand.
Secondary knots and links as a metaphor for higher bliss
As with the above example, we can reason that one of the ways in which both pain and pleasure can be present in *multiples* of one’s normal hedonic range is because the amount of consciousness crammed into a moment of experience is not a constant. In other words, when someone in a typical state of consciousness asks “if you say one can experience so much pain/pleasure, tell me, where would that fit in my experience? I don’t see much room for that to fit in here”, one can respond by saying that “in other states of consciousness there is more (phenomenal) time and space within each moment of experience”. Indeed, at Qualia Computing we have assembled and interpreted a large number of experiences of high-energy states of consciousness that indicate that both phenomenal time, and phenomenal space, can drastically expand. To sum it up – you can fit so much pleasure and pain in peak experiences precisely because such experiences make room for them.
Let us now illustrate the point with some paradigmatic cases of very high and vey low valence:
Peak Pleasure States: Jhanas and Temporal Lobe Seizures
On the pleasure side, we have Buddhist meditators who experience meditative states of absorption (aka. “Jhanas”) as extremely, and counter-intuitively, blissful:
The experience can include some very pleasant physical sensations such as goose bumps on the body and the hair standing up to more intense pleasures which grow in intensity and explode into a state of ecstasy. If you have pain in your legs, knees, or other part of the body during meditation, the pain will actually disappear while you are in the jhanas. The pleasant sensations can be so strong to eliminate your painful sensations. You enter the jhanas from the pleasant experiences exploding into a state of ecstasy where you no longer “feel” any of your senses.
There are 8 (or 9, depending on who you ask) “levels” of Jhanas, and the above is describing only the 1st of them! The higher the Jhana, the more refined the bliss becomes, and the more detached the state is from the common referents of our everyday human experience. Ultra-bliss does not look at all like sensual pleasure or excitement, but more like information-theoretically optimal configurations of resonant waves of consciousness with little to no intentional content (cf. semantically neutral energy). I know this sounds weird, but it’s what is reported.
“Streamlines from the insula to the cortex” – the insula (in red) is an area of the brain intimately implicated in the super-bliss that sometimes precedes temporal lobe epilepsy (source)
Another example I will provide about ultra-bliss concerns temporal lobe epilepsy, which in a minority of sufferers gives rise to extraordinarily intense states of pleasure, or pain, or both. Such experiences can result in Geschwind syndrome, a condition characterized by hypergraphia (writing non-stop), hyper-religiosity, and a generally intensified mental and emotional life. No doubt, any experience that hits the valence scale at one of its extremes is usually interpreted as other-worldly and paranormal (which gives rise to the question of whether valence is a spiritual phenomenon or the other way around). Famously, Dostoevsky seems to have experienced temporal lobe seizures, and this ultimately informed his worldview and literary work in profound ways. Here is how he describes them:
“A happiness unthinkable in the normal state and unimaginable for anyone who hasn’t experienced it… I am then in perfect harmony with myself and the entire universe.”
– From a letter to his friend Nikolai Strakhov.
“I feel entirely in harmony with myself and the whole world, and this feeling is so strong and so delightful that for a few seconds of such bliss one would gladly give up 10 years of one’s life, if not one’s whole life. […] You all, healthy people, can’t imagine the happiness which we epileptics feel during the second before our fit… I don’t know if this felicity lasts for seconds, hours or months, but believe me, I would not exchange it for all the joys that life may bring.”
– from the character Prince Myshkin in Dostoevsky’s novel, The Idiot, which he likely used to give a voice to his own experiences.
Dostoevsky is far from the only person reporting these kinds of experiences from epilepsy:
As Picard [a scientist investigating seizures] cajoled her patients to speak up about their ecstatic seizures, she found that their sensations could be characterised using three broad categories of feelings (Epilepsy & Behaviour, vol 16, p 539). The first was heightened self-awareness. For example, a 53-year-old female teacher told Picard: “During the seizure it is as if I were very, very conscious, more aware, and the sensations, everything seems bigger, overwhelming me.” The second was a sense of physical well-being. A 37-year-old man described it as “a sensation of velvet, as if I were sheltered from anything negative”. The third was intense positive emotions, best articulated by a 64-year-old woman: “The immense joy that fills me is above physical sensations. It is a feeling of total presence, an absolute integration of myself, a feeling of unbelievable harmony of my whole body and myself with life, with the world, with the ‘All’,” she said.
– from “Fits of Rapture”, New Scientist (January 25, 2014) (source)
All in all, these examples illustrate the fact that blissful states can be deeper, richer, more intense, more conscious, and qualitatively superior to the normal everyday range of human emotion.
Now, how about the negative side?
Logarithmic Pain Scales: Stings, Peppers, and Cluster Headaches
“The difference between 6 and 10 on the pain scale is an exponential difference. Believe it or not.”
– Insufferable Indifference, by Neil E. Clement (who experiences chronic pain ranging between 6/10 to 10/10, depending on the day)
(1) Justin O. Schmidt stung himself with over 80 species of insects of the Hymenoptera order, and rated the ensuing pain on a 4-point-scale. About the scale, he had to say the following:
4:28 – Justin Schmidt: The harvester ant is what got the sting pain scale going in the first place. I had been stung by honeybees, yellow jackets, paper wasps, etc. the garden variety stuff, that you get bitten by various beetles and things. I went down to Georgia, which has the Eastern-most extension of the harvester ant. I got stung and I said “Wooooow! This is DIFFERENT!” You know? I thought I knew everything there was about insect stings, I was just this dumb little kid. And I realized “Wait a minute! There is something different going on here”, and that’s what got me to do the comparative analysis. Is this unique to harvester ants? Or are there others that are like that. It turns out while the answer is, now we know much later – it’s unique! [unique type of pain].
7:09 – Justin Schmidt: I didn’t really want to go out and get stung for fun. I was this desperate graduate student trying to get a thesis, so I could get out and get a real job, and stop being a student eventually. And I realized that, oh, we can measure toxicity, you know, the killing power of something, but we can’t measure pain… ouch, that one hurts, and that one hurts, and ouch that one over there also hurts… but I can’t put that on a computer program and mathematically analyze what it means for the pain of the insect. So I said, aha! We need a pain scale. A computer can analyze one, two, three, and four, but it can’t analyze “ouch!”. So I decided that I had to make a pain scale, with the harvester ant (cutting to the chase) was a 3. Honey bees was a 2. And I kind of tell people that each number is like 10 equivalent of the number before. So 10 honey bee stings are equal to 1 harvester ant sting, and 10 harvester ant stings would equal one bullet ant sting.
11:50 – [Interviewer]: When I finally worked up the courage to [put the Tarantula Hawk on my arm] and take this sting. The sting of that insect was electric in nature. I’ve been shocked before, by accidentally taking a zap from an electrical cord. This was that times 10. And it put me on the ground. My arm seized up from muscle contraction. And it was probably the worst 5 minutes of my life at that point.
Justin Schmidt: Yeah, that’s exactly what I call electrifying. I say, imagine you are walking along in Arizona, and there is a wind storm, and the power line above snaps the wire, and it hits you, of course that hasn’t happened to me, but that’s what you imagine it feels like. Because it’s absolutely electrifying, I call it debilitating because you want to be macho, “ah I’m tough, I can do this!” Now you can’t! So I tell people lay down and SCREAM! Right?
[Interviewer]: That’s what I did! And Mark would be like, this famous “Coyote, are you ok? Are you ok?”
Justin Schmidt: No, I’m not ok!
[Interviewer]: And it was very hard to try to compose myself to be like, alright, describe what is happening to your body right now. Because your mind goes into this state that is like blank emptiness. And all you can focus on is the fact that there’s radiating pain coming out of your arm.
Justin Schmidt: That’s why you scream, because now you’re focusing on something else. In addition to the pain, you’re focusing on “AAAAAAHHHHH!!!” [screams loudly]. Takes a little bit of the juice off of the pain, so maybe you lower it down to a three for as long as you can yell. And I can yell for a pretty long time when I’m stung by a tarantula hawk.
If we take Justin’s word for it, a sting that scores a 4 on his pain scale is about 1,000 times more painful than a sting that scores a 1 on his scale. Accordingly, Christopher Starr (who replicated the scale), stated that any sting that scores a 4 is “traumatically painful” (source). Finally, since the scale is restricted to stings of insects of the Hymenoptera order, it remains possible that there are stings whose pain would be rated even higher than 4. A 5 on the sting pain index might perhaps be experienced with the stings of the box jellyfish that produces Irukandji syndrome, and the bite of the giant desert centipede. Needless to say, these are to be avoided.
(2) The Scoville scale measures how spicy different chili peppers and hot sauces are. It is calculated by diluting the pepper/sauce in water until it is no longer possible to detect any spice in it. The number that is associated with the pepper or sauce is the ratio of water-to-sauce that makes it just barely possible to taste the spice. Now, this is of course not itself a pain scale. I would nonetheless anticipate that taking the log of the Scoville units of a dish might be a good approximation for the reported pain it delivers. In particular, people note that there are severalqualitative jumps in the type and nature of the pain one experiences when eating hot sauces of different strengths (e.g. “Fuck you Sean! […] That was a leap, Sean, that was a LEAP!” – Ken Jeong right after getting to the 135,000 Scoville units sauce in the pain porn Youtube series Hot Ones). Amazon reviews of ultra-hot sauces can be mined for phenomenological information concerning intense pain, and the general impression one gets after reading such reviews is that indeed there is a sort of exponential range of possible pain values:
I know it may be fun to trivialize this kind of pain, but different people react differently to it (probably following a long-tail too!). For some people who are very sensitive to heat pain, very hot sauce can be legitimately traumatizing. Hence I advise against having ultra-spicy sauces around your house. The novelty value is not worth the probability of a regrettable accident, as exemplified in some of the Amazon reviews above (e.g. a house guest assuming that your “Da’Bomb – Beyond Insanity” bottle in the fridge can’t possibly be thathot… and ending up in the ER and with PTSD).
I should add that media that is widely consumed about extreme hot sauce (e.g. the Hot Ones mentioned above and numerous stunt Youtube channels) may seem fun on the surface, but what doesn’t make the cut and is left in the editing room is probably not very palatable at all. From an interview: “Has anyone thrown up doing it?” (interviewer) – “Yeah, we’ve run the gamuts. We’ve had people spit in buckets, half-pass out, sleep in the green room afterwards, etc.” (Sean Evans, Hot Ones host). T.J. Miller, when asked about what advice he would give to the show while eating ultra-spicy wings, responded: “Don’t do this. Don’t do this again. End the show. Stop doing the show. That’s my advice. This is very hot. This is painful. There’s a problem here.”
Trigeminal Neuralgia pain scale – a condition similarly painful to Cluster Headaches
(3) Finally, we come to the “KIP scale”, which is used to rate Cluster Headaches, one of the most painful conditions that people endure:
The KIP scale
KIP-0 No pain, life is beautiful KIP-1 Very minor, shadows come and go. Life is still beautiful KIP-2 More persistent shadows KIP-3 Shadows are getting constant but can deal with it KIP-4 Starting to get bad, want to be left alone KIP-5 Still not a “pacer” but need space KIP-6 Wake up grumbling, curse a bit, but can get back to sleep without “dancing” KIP-7 Wake up, sleep not an option, take the beast for a walk and finally fall into bed exhausted KIP-8 Time to scream, yell, curse, head bang, rock, whatever works KIP-9 The “Why me?” syndrome starts to set in KIP-10 Major pain, screaming, head banging, ER trip. Depressed. Suicidal.
The duration factor is multiplied by the intensity factor, which uses the KIP scale in an exponential way – a KIP 10 is not just twice as bad as a KIP 5, it’s ten times as intense.
As seen above, the KIP scale is acknowledged by its creator and users to be logarithmic in nature.
In summary: We see that pleasure comes in various grades and that peak experiences such as those induced by psychedelics, meditation, and temporal lobe seizures seem to be orders of magnitude more energetic and better than everyday sober states. Likewise, we see that across several categories of pain, people report being surprised by the leaps in both quality and intensity that are possible. More so, at least in the case of the Schmidt Index and the Kip Scale, the creators of the scale were explicit that it was a logarithmic mapping of the actual level of sensation.
While we do not have enough evidence (and conceptual clarity) to assert that the intensity of pain and pleasure does grow exponentially, the information presented so far does suggest that the valence of experiences follows a long-tail distribution.
Deference-type Approaches for Experience Ranking
The above considerations underscore the importance of coming up with a pleasure-pain scale that tries to take into account the non-linearity and non-normality of valence ratings. One idea we came up with was a “deference”-type approach, where we ask open-ended questions about people’s best and worst experiences and have them rank them against each other. Although locally the data would be very sparse, the idea was that there might be methods to integrate the collective patterns of deference into an approximate scale. If extended to populations of people who are known to have experienced extremes of valence, the approach would even allow us to unify the various pain scales (Scoville, Schmidt, KIP, etc.) and assign a kind of universal valence score to different categories of pain and pleasure.* That will be version 2.0. In the meantime, we thought to try to get a rough picture of the extreme joys and affections of members of the general public, which is what this article will focus on.
Normal World vs. Lognormal World
There is a world we could call the “Normal World”, where valence outliers are rare and most types of experiences affect people more or less similarly, distributed along a Gaussian curve. Then there is another, very different world we could call the “long-tailed world” or if we want to make it simple (acknowledging uncertainty) “Lognormal World”, where almost every valence distribution is a long-tail. So in the “Lognormal World”, say, for pleasure (and symmetrically for pain), we would expect to see a long-tail in the mean pleasure of experiences between different categories across all people, a long-tail in the amount of pleasure within a given type of experience across people, a long-tail for the number of times an individual has had a certain type of pleasure, a long-tail in the intensity of the pleasure experienced with a single category of experience within a single person, and so on. Do we live in the Normal World or the Lognormal World?
Predictions of Lognormal World
If we lived in the “Lognormal World”, we would expect:
That people will typically say that their top #1 best/worst experience is not only a bit better/worse than their #2 experience, but a lot better/worse. Like, perhaps, even multiple times better/worse.
That there will be a long-tail in the number of appearances of different categories (i.e. that a large amount, such as 80%, of top experiences will belong to the same narrow set of categories, and that there will be many different kinds of experiences capturing the remaining 20%).
That for most pairs of experiences x and y, people who have had both instances of x and y, will usually agree about which one is better/worse. We call such a relationship a “deference”. More so, we would expect to see that deference, in general, will be transitive (a > b and b > c implying that a > c).
To test the first and second prediction does not require a lot of data, but the third does because one needs to have enough comparisons to fill a lot of triads. The survey results we will discuss bellow are congruent with the first and second prediction. We did what we could with the data available to investigate the third, and tentatively, it seems to hold up (with ideas like deference network centrality analysis, triadic analysis, and tournament-style approaches).
The survey asked the following questions: current level of pleasure, current level of pain, top 3 most pleasurable experiences (in decreasing order) along with pleasure ratings for each of them and the age when they were experienced, and the same for the top 3 most painful experiences. I specifically did not provide a set of broad categories (such as “physical” or “emotional”) or a drop-down menu of possible narrow categories (e.g. going to the movies, aerobic exercise, etc.). I wanted to see what people would say when the question was as open-ended as possible.
I also included questions aimed more directly at probing the long-tailed nature of valence: I asked participants to rate “how many times more pleasant was the #1 top experience relative to the #2 top experience” (and #2 relative to #3, and the same for the top most painful experiences).
I also asked them to describe in more detail the single most pleasant and unpleasant experiences, and added a box for comments at the end in order to see if anyone complained about the task (most people said “no comment”, many said they enjoyed the task, and one person said that it made them nostalgic). I also asked about basic demographics (age and gender). Participants earned $1.75 for the task, which seems reasonable given the time it took to complete in most cases.
Mechanical Turk: Participant Composition
The survey was run on Mechanical Turk. I requested “Masters” qualifications for 90/110 of the survey responses. To be a Mechanical Turk Master you need to have a good track record of task approval, which I reasoned would increase the rate of well thought-out high-quality responses (this turned out to be true). The participants’ genders were fairly balanced (50/97 women, 47/97 men), and the average age was 36.5 years (sd = 10):
Bots (easy to spot – unless extremely sophisticated)
While reading the responses I discovered that some of them seemed to be generated by bots. Apparently task requesters started noticing the presence of bots a couple of years ago. This is obviously a problem for academics trying to use the service for their research, and for machine learning professionals using the service for data-tagging. Having been both of those things in the past, I can say that a few years ago I did not see any submissions that looked suspiciously bot-like. Though low-quality rushed responses did seem to be relatively common back then, I never observed bot-like responses to open-ended questions. Unfortunately this time I was able to spot several responses clearly written by bots. For example, one respondent answered the question “write a brief essay about your #1 best experience” with:
The reason these types of assignments are given so often is that anyone can write about their own experience and it doesn’t require any outside resources or research. However, even though anyone can tell a story about their life, that does not mean anyone can write a good essay about that experience. As a professor and teacher for 30 years, I’ve read thousands of essays and can tell you there is a distinct difference from telling a story about yourself and writing an excellent personal experience essay. The difference between good and great:
And it ends that way, with a colon indicating that the respondent is about to explain what the difference between good and great is. But it never does it. This answer, great, it is not.
In most cases the difference between a genuine response and a bot response was very obvious. That said, I erred on the side of caution for filtering bots and I got rid of answers even if they seemed just a little suspicious. This left me with 97 out of the 110 original responses. The following analysis was conducted on those 97 responses.
Since the responses were open-ended I had to tag each of them with an experience category. To do this I read each response and identified the key theme in them and classified them with a label that was specific enough to distinguish it from nearby experiences (e.g. different types of fractures), but not so specific that we would never get more than one response per category (e.g. “breaking the middle finger in elementary school”). In general, most responses fell into very unambiguous categories (e.g. “When my father passed away” and “Watching my father die and take his last few breaths.” were both classified as “Father death”). About 10% of the responses were relatively ambiguous: it wasn’t clear what the source of the pain or pleasure was. To deal with those responses I used the label “Unspecified”. When some detail was present but ambiguity remained, such as when a broad type of pain or pleasure was mentioned but not the specific source I tagged it as “Unspecified X” where X was a broad category. For example, one person said that “broken bones” was the most painful experience they’ve had, which I labeled as “Unspecified fracture”.
I should preface the following by saying that we are very aware of the lack of scientific rigor in this survey; it remains a pilot exploratory work. We didn’t specify the time-scale for the experiences (e.g. are we asking about the best minute of your life or the best month of your life?) or whether we were requesting instances of physical or psychological pain/pleasures. Despite this lack of constraints it was interesting to see very strong commonalities among people’s responses:
Appearance Base Rates
There were 77 and 124 categories of pleasure and pain identified, respectively. On the whole it seemed like there was a higher diversity of ways to suffer than of ways to experience intense bliss. Summoning the spirit of Tolstoy: “Happy families are all alike; every unhappy family is unhappy in its own way.”
Here are the raw counts for each category with at least two appearances:
Best experiences appearances (with at least two reports)
Worst experience appearances (with at least two reports)
For those who want to see the full list of number of appearances for each experience mentioned see the bottom of the article (I also clarify some of the more confusing labels there too)**.
A simple way to try to incorporate the information about the ranking is to weight experiences rated as top #1 with 3 points, those as top #2 with 2 points, and those as the top #3 with 1 point. If you do this, the experiences scores are:
Weighted appearances of best experiences (#1 – 3 points, #2 – 2 points, #3 – 1 point)
Given the relatively small sample size, I will only report the mean rating for pain and pleasure (out of 10) for categories of experience for which there were 6 or more respondents:
Father death (n = 19): mean 8.53, sd 2.3
Childbirth (n = 16): mean 7.94, sd 2.16
Grandmother death (n = 13): mean 8.12, sd 2.5
Mother death (n = 11): mean 9.4, sd 0.62
Car accident (n = 9): mean 8.42, sd 1.52
Kidney stone (n = 9): mean 5.97, sd 3.17
Migraine (n = 9): mean 5.36, sd 3.11
Romantic breakup (n = 9): mean 7.11, sd 1.52
Broken arm (n = 6): mean 8.28, sd 0.88
Broken leg (n = 6): mean 7.33, sd 2.02
Work failure (n = 6): mean 5.88, sd 3.57
(Note: the very high variance for kidney stones and migraine is partly explained by the presence of some very low responses, with values as low as 1.1/10 – perhaps misreported, or perhaps illustrating the extreme diversity of experiences of migraines and kidney stones).
And for pleasure:
Falling in love (n = 42): mean 8.68, sd 1.74
Children born (n = 41): mean 9.19, sd 1.64
Marriage (n = 21): mean 8.7, sd 1.25
Sex (n = 19): mean 8.72, sd 1.45
College graduation (n = 13): mean 7.73, sd 1.4
Orgasm (n = 11): mean 8.24, sd 1.63
Alcohol (n = 8): mean 6.84, sd 1.59
Vacation (n = 6): mean 9.12, sd 0.73
Getting job (n = 6): mean 7.22, sd 1.47
Personal favorite sports win (n = 6): mean 8.17, sd 1.23
Deference Graph of Top Experiences
We will now finally get to the more exploratory and fun/interesting analysis, at least in that it will generate a cool way of visualizing what causes people great joy and pain. Namely, the idea of using people’s rankings in order to populate a global scale across people and show it in the form of a graph of deferences. While the scientific literature has some studies that compare pain across different categories (e.g. 1, 2, 3) I was not able to find any dataset that included actual rankings across a variety of categories. Hence why it was so appealing to visualize this.
The simplest way of graphing experience deferences is to assign a node to each experience category and add an edge between experiences with deference relationships with a weight proportional to the number of directed deferences. For example, if 4 people have said that A was better than B, and 3 people have said that B was better than A, then there will be an edge from A to B with a weight of 4 and an edge from B to A with a weight of 3. Additionally, we can then run a graph centrality algorithm such as PageRank to see where the “deferences end up pooling”.
The images below do this: the PageRank of the graph is represented with the color gradient (darker shades of green/red representing higher PageRank values for good/bad experiences). In addition, the graphs also represent the number of appearances in the dataset for each category with the size of each node:
Best experiences deferences – edge thickness based on number of deferences, node size based on number of appearances, and color scheme based on PageRank
Worst experiences deferences – edge thickness based on number of deferences, node size based on number of appearances, and color scheme based on PageRank
The main problem with the approach above is that it double (triple?) counts experiences that are very common. Say that, for example, taking 5-MeO-DMT produces a consistently higher-valence feeling relative to having sex. If we only have a couple of people who report both 5-MeO-DMT and sex as their top experiences, the edge from sex to 5-MeO-DMT will be very weak, and the PageRank algorithm will underestimate the value of 5-MeO-DMT.
In order to avoid the double counting effect of commonly-reported peak experiences we can instead add edge weights on the basis of the proportion with which an experience defers to the other. Let’s say that f(a, b) means “number of times that b is reported as higher than a”. Then the proportion would be f(a, b) / (f(a, b) + f(b, a)). Now, this introduces another problem, which is that pairs of experiences that appear together very infrequently might get a very high proportion score due to a low sample size. In order to prevent this we use Laplace smoothing and modify the equation to (f(a, b) + 1) / (f(a, b) + f(b, a) + 2). Finally, we transform this proportion score from the range of 0 to 1 to the range of -1 to 1 by multiplying by 2 and subtracting one. We call this a “rebalanced smoothed proportion” w(a, b):
Rebalanced smoothed proportion
I should note that this is not based on any rigorous math. The equation is based on my intuition for what I would expect to see in such a graph, namely a sort of confidence-weighted strength of directionality, but I do not guarantee that this is a principled way of doing so (did I mention this is a pilot small-scale low-budget ‘to a first approximation’ study?). I think that, nonetheless, doing this is still an improvement upon merely using the raw deference counts as the edge weights. To visualize what w(a, b) looks like I graphed its values for a and b in the range of 0 to 20 (literally typing the equation into the google search bar):
Rebalanced smoothed proportion equation
Rebalanced smoothed proportion equation
Rebalanced smoothed proportion equation
Rebalanced smoothed proportion equation
Rebalanced smoothed proportion equation
Rebalanced smoothed proportion equation
To populate the graph I only use the positive edge weights so that we can run the PageRank algorithm on it. This now looks a lot more reasonable and informative as a deference graph than the previous attempts:
Best experiences deference graph: Edge weights based on the rebalanced smoothed proportions, size of nodes is proportional to number of appearances in the dataset, and the color tracks the PageRank of the graph. Edge color based on source node.
Worst experiences deference graph: Edge weights based on the rebalanced smoothed proportions, size of nodes is proportional to number of appearances in the dataset, and the color tracks the PageRank of the graph. Edge color based on source node.
By taking the PageRank of these graphs (calculated with NetworkX) we arrive at the following global rankings:
PageRank of the graph of best experiences with edge weights computed with the rebalanced smoothed proportion equation
PageRank of the graph of worst experiences with edge weights computed with the rebalanced smoothed proportion equation
Intuitively this ranking seems more aligned with what I’ve heard before, but I will withhold judgement on it until we have much more data.
With a more populated deference graph we can analyze in detail the degree to which triads (i.e. sets of three experiences such that each of the three possible deferences are present in the graph) show transitivity (cf. Balance vs. Status Theory).
In particular, we should compare the prevalence of these two triads:
The triads above are 030T, which is transitive, and 030C, which is a loop. The higher the degree of agreement between people and the higher the probability of the existence of an underlying shared scale, we would expect to see more triads of the type 030T relative to 030C. That said, a simple ratio is not enough, since the expected proportion between these two triads can be an artifact of the way the graph is constructed and/or its general shape (and hence the importance of comparing against randomized graphs that preserve as many other statistical features as possible). With our graph, we noticed that the very way in which the edges were introduced generated an artifact of a very strong difference between these two types of triads:
In the case of pain there are 105 ‘030T’, and 3 ‘030C’. And for the pleasure questions there were 98 ‘030T’, and 9 ‘030C’. That said, many of these triads are the artifact of taking into account the top three experiences, which already generates a transitive triad by default when n = 1 for that particular triad of experiences. To avoid this artifact, we filtered the graph by only adding edges when a pair of experiences appeared at least twice (and discounting the edges where w(a, b) = 0). With this adjustment we got 2 ‘030T’, and 1 ‘030C’ for the pain questions, and 1 ‘030T’, and 0 ‘030C’ for the pleasure question. Clearly there is not enough data to meaningfully conduct this type of analysis. If we extend the study and get a larger sample size, this analysis might be much more informative.
Latent Trait Ratings
A final approach I tried for deriving a global ranking of experiences was to assume a latent parameter for pain or pleasure of different experiences and treating the rankings as the tournament results of participants with skill equal to this latent trait. So when someone says that an experience of sex was better than an experience of getting a new bike we imagine that “sex” had a match with “getting bike” and that “sex” won that match. If we do this, then we can import any of the many tournament algorithms that exist (such as the Elo rating system) in order to approximate the latent “skill” trait of each experience (except that here it is the “skill” to cause you pleasure or pain, rather than any kind of gaming ability).
I should mention that the fact that we are asking about peak experiences likely violates some of the assumptions of these algorithms, since the fact that a match takes place is already information that both experiences made it into the top 3. That said, if the patterns of deference are very strong, this might not represent a problem.
To come up with this tournament-style ranking I decided to go for a state-of-the-art algorithm. The one that I was able to find and use was Microsoft Research’s algorithm called TrueSkill (which is employed to rank players in Xbox LIVE). According to their documentation, to arrive at a conservative “leaderboard” that balances the estimated “true skill” and the uncertainty around it, they recommend ranking by the expected skill level minus three times the standard error around this estimate. If we do this, we arrive at the following experience “leaderboards”:
Conservative TrueSkill scores for best experiences (mu – 3*sigma)
Conservative TrueSkill scores for worst experiences (mu – 3*sigma)
Long-tails in Responses to “How Many Times Better/Worse” Question
The survey included four questions aimed at comparing the relative hedonic values of peak experiences: “Relative to the 1st most pleasant experience, how many times better was the 2nd most pleasant experience?” (This was one, the other three were the permutations of also asking about 2nd vs. 3rd and about the bad experiences):
(Note: I’ll ignore the responses to the comparison between the 2nd and 3rd worst pains because I messed up the question -I forgot to substitute “better” for “worse”).
I would understand the skepticism about these graphs. But at the same time, I don’t think it is absurd that for many people the worst experience they’ve had is indeed 10 or 100 times worse than the second worst. For example, someone who has endured a bad Cluster Headache will generally say that the pain of it is tens or hundreds of times worse than any other kind of pain they have had (say, breaking a bone or having skin burns).
The above distributions suggest a long-tail for the hedonic quality of experiences: say that the hedonic quality of each day is distributed along a log-normal distribution. A 45 year old has experienced roughly 17,000 days. Let’s say that such a person’s experience of pain each day is sampled from a log-normal distribution with a Gaussian exponent with a mean of 10 and a standard deviation of 5. If we take 100 such people, and for each of them we take the single worst and the second worst days of their lives, and then take the ratio between them, we will have a distribution like this (simulated in R):
If you smooth the empirical curves above you would get a distribution that looks like these simulations. You really need a long-tail to be able to get results like “for 25% of the participants the single worst experience was at least 4 times as bad as the 2nd worst experience.” Compare that to the sort of pattern that you get if the distribution was normal rather than log-normal:
As you can see (zooming in on the y-axis), the ratios simply do not reach very high values. With the normal distribution simulated here, we see that the highest ratio we achieve is around 1.3, as opposed to the empirical ratios of 10+.*** If you are inclined to believe the survey responses- or at least assign some level of credibility to the responses in the 90th-percentile and below-, the data is much more consistent with a long-tail distribution for hedonic values relative to a normal distribution.
Key Pleasures Surfaced
Birth of children
I have heard a number of mothers and father say that having kids was the best thing that ever happened to them. The survey showed this was a very strong pattern, especially among women. In particular, a lot of the reports deal with the very moment in which they held their first baby in their arms for the first time. Some quotes to illustrate this pattern:
The best experience of my life was when my first child was born. I was unsure how I would feel or what to expect, but the moment I first heard her cry I fell in love with her instantly. I felt like suddenly there was another person in this world that I cared about and loved more than myself. I felt a sudden urge to protect her from all the bad in the world. When I first saw her face it was the most beautiful thing I had ever seen. It is almost an indescribable feeling. I felt like I understood the purpose and meaning of life at that moment. I didn’t know it was possible to feel the way I felt when I saw her. I was the happiest I have ever been in my entire life. That moment is something that I will cherish forever. The only other time I have ever felt that way was with the subsequent births of my other two children. It was almost a euphoric feeling. It was an intense calm and contentment.
I was young and had a difficult pregnancy with my first born. I was scared because they had to do an emergency c-section because her health and mine were at risk. I had anticipated and thought about how the moment would be when I finally got to hold my first child and realize that I was a mother. It was unbelievably emotional and I don’t think anything in the world could top the amount of pleasure and joy I had when I got to see and hold her for the first time.
I was 29 when my son was born. It was amazing. I never thought I would be a father. Watching him come into the world was easily the best day of my life. I did not realize that I could love someone or something so much. It was at about 3am in the morning so I was really tired. But it was wonderful nonetheless.
I absolutely loved when my child was born. It was a wave of emotions that I haven’t felt by anything before. It was exciting and scary and beautiful all in one.
No luck for anti-natalists… the super-strong drug-like effects of having children will presumably continue to motivate most humans to reproduce no matter how strong the ethical case against doing so may be. Coming soon: a drug that makes you feel like “you just had 10,000 children”.
Falling in Love
The category of “falling in love” was also a very common top experience. I should note that the experiences reported were not merely those of “having a crush”, but rather, they typically involved unusually fortunate circumstances. For instance, a woman reported being friends with her crush for 7 years. She thought that he was not interested in her, and so she never dared to confess her love for him… until one day, out of the blue, he confessed his love for her. Other experiences of falling in involve chance encounters with childhood friends that led to movie-deserving romantic escapades, forbidden love situations, and cases where the person was convinced the lover was out of his or her league.
The terms “travel” and “vacation” may sound relatively frivolous in light of some of the other pleasures listed. That said, these were not just any kind of travel or vacation. The experiences described do seem rather extraordinary and life-changing. For example, talking about back-packing alone in France for a month, biking across the US with your best friend, or a long trip in South East Asia with your sibling that goes much better than planned.
It is significant that out of 97 people four of them listed MDMA as one of the most pleasant experiences of their lives. This is salient given the relatively low base rate of usage of this drug (some surveys saying about 12%, which is probably not too far off from the base rate for Mechanical Turk workers using MDMA). This means that a high percentage of people who have tried MDMA will rate it as as one of their top experiences, thus implying that this drug produces experiences sampled from an absurdly long-tailed high-valence distribution. This underscores the civilizational significance of inventing a method to experience MDMA-like states of consciousness in a sustainable fashion (cf. Cooling It Down To Partying It Up).
Likewise, the appearance of LSD and psilocybin is significant for the same reason. That said, measures of the significance of psychedelic experiences in psychedelic studies have shown that a high percentage of those who experience such states rate them among their top most meaningful experiences.
Games of Chance Earnings
Four participants mentioned earnings in games of chance. These cases involved earning amounts ranging from $2,000 all the way to a truck (which was immediately sold for money). What I find significant about this is that these experiences are at times ranked above “college graduation” and other classically meaningful life moments. This brings about a crazy utilitarian idea: if indeed education is as useless as many people in the intellectual elite are saying these days (ex. The Case Against Education) we might as well stop subsidizing higher education and instead make people participate in opt-out games of chance rigged in their favor. Substitute the Department of Education for a Department of Lucky Moments and give people meaningful life experiences at a fraction of the cost.
Key Pains Surfaced
Kidney Stones and Migraines
The fact that these two medical issues were surfaced is, I think, extremely significant. This is because the lifetime incidence of kidney stones is about 10% (~13% for men, 7% for women) and for migraines it is around 13% (9% for men, 18% for women). In the survey we saw 9/93 people mentioning kidney stones, and the same number of people mentioning migraines. In other words, there is reason to believe that a large fraction of the people who have had either of these conditions will rate them as one of their top 3 most painful experiences. This fact alone underscores the massive utilitarian benefit that would come from being able to reduce the incidence of these two medical problems (luckily, we have some good research leads for addressing these problems at a large scale and in a cost-effective way: DMT for migraines, and frequency specific microcurrent for kidney stones)
Childbirth was mentioned 16 times, meaning that roughly 30% of women rate it as one of their three most painful experiences. While many people may look at this and simply nod their heads while saying “well, that’s just life”, here at Qualia Computing we do not condone that kind of defeatism and despicable lack of compassion. As it turns out, there are fascinating research leads to address the pain of childbirth. In particular, Jo Cameron, a 70 year old vegan schoolteacher, described her childbirth by saying that it “felt like a tickle”. She happens to have a mutation in the FAAH gene, which is usually in charge of breaking down anandamine (a neurotransmitter implicated in pain sensitivity and hedonic tone). As we’ve argued before, every child is a complete genetic experiment. In the future, we may as well try to at least make educated guesses about our children’s genes associated with low mood, anxiety, and pain sensitivity. In defiance of common sense (and the Bible) the future of childbirth could indeed be one devoid of intense pain.
Car accidents are extremely common (the base rate is so high that by the age of 40 or so we can almost assume that most people have been in at least one car accident, possibly multiple). More so, it seems likely that the health-damaging effects of car accidents, by their nature, follow a long-tail distribution. The high base rate of people mentioning car accidents in their top 3 most painful experiences underscores the importance of streamlining the process of transitioning into the era of self-driving cars.
Death of Father and Mother
This one does not come as a surprise, but what may stand out is the relatively higher frequency of mentions of “death of father” relative to “death of mother”. I think this is an artifact of the longevity difference between men and women. This is in agreement with the observed effect of age: about 15% vs. 25% of people under and over 40 had mentioned the death of their father, as opposed to a difference of 5% vs. 25% for death of mother. The reason why the father might be over-represented might simply be due to the lower life expectancy of men relative to women, and hence the father, on average, dying earlier. Thus, it being reported more frequently by a younger population.
Future Directions for Methodological Approaches:
Graphical Models with Log-normal Priors
After trying so many analytic angles on this dataset, what else is there to do? I think that as a proof of concept the analysis presented here is pretty well-rounded. If the Qualia Research Institute does well in the funding department, we can expect to extend this pilot study into a more comprehensive analysis of the pleasure-pain axis both in the general population and among populations who we know have endured or enjoyed extremes of valence (such as cluster headache sufferers or people who have tried 5-MeO-DMT).
In terms of statistical models, an adequate amount of data would enable us to start using probabilistic graphical models to determine the most likely long-tail distributions for all of the key parameters of pleasure and pain. For instance, we might want to develop a model similar to Item Response Theory where:
Each participant samples experiences from a distribution.
Each experience category generates samples with an empirically-determined base rate probability (e.g. chances that it happens in a given year), along with a latent hedonic value distribution.
A “discrimination function” f(a, b) that gives the probability that experience of hedonic value a is rated as more pleasant (or painful) relative an experience with a hedonic value of b.
And a generative model that estimates the likelihood of observing experiences as the top 3 (or top x) based on the parameters provided.
In brief, with an approach like the above we can potentially test the model fit for different distribution types of hedonic values per experience. In particular, we would be able to determine if the model fit is better if the experiences are drawn from a Gaussian vs. a log-normal (or other long-tailed) distribution.
Finally, it might be fruitful to explicitly ask about whether participants have had certain experiences in order to calibrate their ratings, or even have them try a battery of standardized pain/pleasure-inducing stimuli (capsaicin extract, electroshocks, stings, massage, orgasm, etc.). We could also find the way to combine (a) the numerical ratings, (2) the ranking information, and (3) the “how many times better/worse” responses into a single model. And for best results, restrict the analysis to very recent experiences in order to reduce recall biases.
Closing Thoughts on the Valence Scale
To summarize, I believe that the case for a long-tail account of the pleasure-pain axis is very defensible. This picture is supported by:
The long-tailed nature of neuronal cascades,
The phenomenological accounts of intense pleasure and pain (w/ phenomenological accounts of time and space expansion),
The way in which pain scales are constructed by those who developed them, and
The analytic results of the pilot study we conducted and presented here.
In turn, these results give rise to a new interpretation of psychophysical observations such as Weber’s Law. Namely, that Just Noticeable Differences may correspond to geometric differences in qualia, not only in sensory stimuli. That is, that the exponential nature of many cases where Weber’s Law appears are not merely the result of a logarithmic compression on the patterns of stimulation at the “surface” of our sense organs. Rather, the observations presented here suggest that these long-tails deal directly with the quality and intensity of conscious experience itself.
Dimensionality of Pleasure and Pain
Pain and pleasure may have an intrinsic “dimensionality”. Without elaborating, we will merely state that a generative definition for the “dimensionality of an experience” is the highest “virtual dimension” implied by the patterns of correlation between degrees of freedom. The hot pepper hands account I related suggested a kind of dimensional phase transition between 4/10 and 5/10 pain, where the patterns of a certain type (4/10 “sparks” of pain) would sometimes synchronize and generate a new type of higher-dimensional sensation (5/10 “solitons” of pain). To illustrate this idea further:
First, in Hot Ones, Kumail Nanjiani describes several “leaps” in the spiciness of the wings, first at around 30,000 Scoville (“this new ghost that appears and only here starts to visit you”), and second at around 130k Scoville (paraphrasing: “like how NES to Super Nintendo felt like a big jump, but then Super Nintendo to N64 was an even bigger leap” – “Now we are playing in the big leagues motherfucker! This is fucking real!”). This hints at a change in dimensionality, too.
And second, Shinzen Young‘s advice about dealing with pain involves not resisting it. He discusses how suffering is generated by the coordination between emotional, cognitive, and physical mental formations. If you can keep each of these mental formations happening independently and don’t allow their coordinated forms, you will avoid some of what makes the experience bad. This also suggests that higher-dimensional pain is qualitatively worse. Pragmatically, training to do this may make sense for the time being, since we are still some years away from sustainable pain-relief for everyone.
We have yet to discuss in detail how mixed states come into play for a log-normal valence scale. The Symmetry Theory of Valence would suggest that most states are neutral in nature and that only processes that reduce entropy locally such as neural annealing would produce highly-valenced states. In particular, we would see that high-valence states have very negative valence states nearby in configuration space; if you take a very good high-energy state and distort it in a random direction it will likely feel very unpleasant. The points in between would be mixed valence, which account for the majority of experiences in the wild.
Qualia Formalism posits that for any given system that sustains experiences, there is a mathematical object such that the mathematical features of that object are isomorphic to the system’s phenomenology. In turn, Valence Structuralism posits that the hedonic nature of experience is encoded in a mathematical feature of this object. It is easier to find something real if you posit that it exists (rather than try to explain it away). We have suggested in the past that valence can be explained in terms of the mathematical property of symmetry, which cashes out in the form of neural dissonance and consonance.
In contrast to eliminativist, illusionist, and non-formal approaches to consciousness, at QRI we simply start by assuming that experience has a deep ground truth structure and we see where we can go from there. Although we currently lack the conceptual schemes, science, and vocabulary needed to talk in precise terms about different degrees of pleasure and pain (though we are trying!), that is not a good reason to dismiss the first-person claims and indirect pieces of evidence concerning the true amounts of various kinds of qualia bound in each moment of experience. If valence does turn out to intrinsically be a mathematical feature of our experience, then both its quality and quantity could very well be precisely measurable, conceptually crisp, and tractable. A scientific fact that, if proven, would certainly have important implications in ethics and meta-ethics.
* It’s a shame that Coyote Peterson didn’t rate the pain produced by the various wings he ate on the Hot Ones show relative to insect stings, but that sort of data would be very helpful in establishing a universal valence scale. More generally, stunt-man personalities like the L.A. Beast who subject themselves to extremes of negative valence for Internet points might be an untapped gold mine for experience deference data (e.g. How does eating the most bitter substance known compare with the bullet ant glove? Asking this guy might be the only way to find out, without creating more casualties).
[('Falling in love', 42), ('Children born', 41), ('Marriage', 21), ('Sex', 19), ('College graduation', 13), ('Orgasm', 11), ('Alcohol', 8), ('Vacation', 6), ('Getting job', 6), ('Personal favorite sports win', 6), ('Nature scene', 5), ('Owning home', 5), ('Sports win', 4), ('Graduating highschool', 4), ('MDMA', 4), ('Getting paid for the first time', 4), ('Amusement park', 4), ('Game of chance earning', 4), ('Job achievement', 4), ('Getting engaged', 4), ('Cannabis', 3), ('Eating favorite food', 3), ('Unexpected gift', 3), ('Moving to a better location', 3), ('Travel', 3), ('Divorce', 2), ('Gifting car', 2), ('Giving to charity', 2), ('LSD', 2), ('Won contest', 2), ('Friend reunion', 2), ('Winning bike', 2), ('Kiss', 2), ('Pet ownership', 2), ('Children', 1), ('First air trip', 1), ('First kiss', 1), ('Public performance', 1), ('Hugs', 1), ('Unspecified', 1), ('Recovering from unspecified kidney problem', 1), ('College party', 1), ('Graduate school start', 1), ('Financial success', 1), ('Dinner with loved one', 1), ('Feeling supported', 1), ('Children graduates from college', 1), ('Family event', 1), ('Participating in TV show', 1), ('Psychedelic mushrooms', 1), ('Opiates', 1), ('Having own place', 1), ('Making music', 1), ('Becoming engaged', 1), ('Theater', 1), ('Extreme sport', 1), ('Armed forces graduation', 1), ('Birthday', 1), ('Positive pregnancy test', 1), ('Feeling that God exists', 1), ('Belief that Hell does not exist', 1), ('Getting car', 1), ('Academic achievement', 1), ('Helping others', 1), ('Meeting soulmate', 1), ('Daughter back home', 1), ('Winning custody of children', 1), ('Friend stops drinking', 1), ('Masturbation', 1), ('Friend not dead after all', 1), ('Child learns to walk', 1), ('Attending wedding of loved one', 1), ('Children safe after dangerous situation', 1), ('Unspecified good news', 1), ('Met personal idol', 1), ('Child learns to talk', 1), ('Children good at school', 1)]
For clarity – “Personal favorite sports win” means that the respondent was a participant in the sport as opposed to a spectator (which was labeled as “Sports win”). The difference between “Sex” and “Orgasm” is that Sex refers to the entire act including foreplay and cuddles whereas Orgasm refers to the specific moment of climax. For some reason people would either mention one or the other, and emphasize very different aspects of the experience (e.g. intimacy vs. physical sensation) so I decided to label them differently.
*** It is possible that some fine-tuning of parameters could give rise to long-tail ratios even with a normal distribution (especially if the mean is, say, a negative value and the standard deviation is very wide). But in the general case a normal distribution will have a fairly narrow range for the ratios of the “top value divided by the second top value”. So at least as a general qualitative argument, I think, the simulations do suggest a long-tailed nature for the reported hedonic values.
“A new study by the CDC revealed that 50 million Americans (just under 20% of the age-adjusted adult population) suffered from chronic pain, which was defined as “pain on most days or every day in the past 6 months.” Nearly 20 million (about 7.5%) experienced high-impact chronic pain, defined as “limiting life or work activities on most days or every day in the past 6 months.”
Using IHME’s GBD visualization tool, about 5% of total DALYs come from conditions associated with chronic pain (back pain, neck pain and self-harm), not to mention the implications pain has in a variety of other conditions, from osteoporosis to cancer.
The Most Effective Tool for Pain Management Carries its Own Significant Burdens
Opioids are highly effective as analgesics for managing chronic and acute pain, and are the most widely used pain treatment. However, consistent use of opioids results in tolerance, dependence, withdrawal and overdose, which claimed the lives of 47,600 people in 2017. Furthermore, the CDC estimates the total economic burden of prescription opioid misuse in the US is $78.5 billion a year, including the costs of health care, lost productivity, addiction treatment, and criminal justice involvement.
Finding a solution for opioids’ dark side would help millions enjoy life, reduce the global health burden by no less than 5%, avoid 10s of thousands of future deaths, and recover billions in lost productivity.
A solution may be to combine variable doses of Ibogaine, the active compound found in the Tabernanthe iboga shrub with safer classes of opioids.
The proliferation of opioids (specifically, full mu-opioid agonists) has this laundry list of problems: tolerance, addiction, withdrawal, overdose and euphoria (if one chooses to see it as a negative side-effect). In an effort to wean off of opioids, several groups have sought to attack these symptoms. Non-opioid therapeutics include cannabidiol (CBD) and CA-008, a TRPV-1 agonist which acts on nociceptive c-fibers in the peripheral nervous system similarly to capsaicin. These tend to be less habit-forming than opioids (attributed to their lower affinity for nuclei in the mesolimbic system), but also less effective at offering relief from intense neuropathic pain. Other attempts to tame opioids have been made, most of them having the reduction of pleasure as the main target. CARA Therapeutics has created a kappa-opioid agonist which acts selectively on receptors in the peripheral nervous system to “produce little to no CNS-mediated side effects that one sees with traditional CNS-acting mu opioids like nausea/vomiting, sedation, respiratory depression, abuse, addiction or euphoria”. NKTR-181, a novel full mu-opioid agonist, is more direct: “NKTR-181, a first-in-class opioid analgesic, is a new chemical entity (NCE) that is the first full mu-opioid agonist molecule designed to provide potent pain relief without the high levels of euphoria that can lead to abuse and addiction with standard opioids”. As it turns out, addiction and pleasure have a complex relationship; one is not reducible to the other. Euphoria-inducing psychedelic drugs and the jhana states of meditative absorption seem to lack the addictive profile of opioids. Pleasure and habit become decoupled over time in the path of opioid addiction as well, one fading with the other stubbornly immovable. If we can have opioids that forego tolerance, addiction, withdrawal and overdose, but keep the euphoria, wouldn’t that be better?
Ibogaine has a history of being used for the treatment of opioid addiction, but it may also have interesting properties for producing safer opioids as well. While at high doses (1g+) it creates intense psychedelic effects, it also has interesting properties at both lower doses of 500-600mg and at ‘microdoses’ of around 50mg. Ibogaine is illegal in many countries, but unregulated in Mexico, legal in Brazil, Gabon, and Costa Rica, and on the prescription drug list in New Zealand and Canada. For a more in-depth review of the history of Ibogaine and its use in treatment, read this review on Pysmposia.
In this case study, a patient who had been a long-term opioid user and recently transitioned to methadone (a replacement for harder opioids like heroin, but maintaining the full agonist mu-opioid method of action) was taken off methadone without withdrawal using increasing doses of Ibogaine (150mg, 300mg, 400mg, 500mg, 600mg). As the Ibogaine dose was increased, the methadone was halved each time. We could allow opioid users to substantially decrease their opioid intake without withdrawal, while continuing to use opioids for pain management. After a few applications at the 100-600mg level, users could be maintaining their usage at ¼ of their original intake. Then they could utilize “dirty maintenance”: taking 25-50mg of Ibogaine daily while using a much lower amount of the opioid they typically use. Microdosing ibogaine alone is also potentially mood-enhancing, and some former opioid users have employed “clean maintenance” (i.e. just Ibogaine), to reduce post-acute-withdrawal syndrome (PAWS).
The reason these solutions work is because Ibogaine acts as an ‘anti-tolerance’ drug. It potentiates the effects of opioids and prevents patterns of tolerance and dependence from forming at the neurological level. When combined with full mu-opioid agonists, even in lower doses, this can pose a risk since the dose required to overdose could be more unpredictable with Ibogaine. A ‘best of both worlds’ solution would be to continue microdosing Ibogaine in conjunction with a partial mu-opioid agonist. Partial mu-opioid agonists prevent overdose by creating an upper-bound on activity at the opioid receptor and preventing the respiratory depression that causes death in full agonists.
While existing partial mu-opioid agonists, such as the drug combo of buprenorphine and naloxone are used in opioid replacement therapy settings, they too lack euphoria-producing properties. With this new class of analgesics, patients could choose when to start, stop, and for how long to take their pain medication without fear, along with a depression-preventing hedonic enhancement. For more, see: On Hitting the Actual Target of Hedonic Tone.
A well-known example of a partial mu-opioid agonist is 7-hydroxymitragynine, the active compound in kratom. Brazil is the only country to not prohibitively schedule either kratom or Ibogaine, and so might be an option for conducting research into this new form of non-tolerance-inducing opioid mixture. In the United States, research is being done at DemeRX for approving Ibogaine through the FDA IND process for the detoxification of people afflicted with opioid addiction. Their success would also open the door to further innovation in Ibogaine-assisted pain treatments in the US.
Risks of Ibogaine
Unfortunately, Ibogaine has a harsher risk profile than most psychedelics, and has been associated with about 30 deaths due to cardiac complications. However, many researchers who have worked with Ibogaine for decades believe that these incidents can be minimized or even eliminated by standard medical practices like employing EKG screenings. Medical screenings should not only assess current heart health, but also in-system drugs, which can be potentiated by Ibogaine use, and can lead to unexpected overdose. In a population of drug users to be treated, higher incidences of poor heart health and the presence of other drugs likely contributed to a significant number of the cases of death recorded.
Mash et al. 2018 reviewed 191 cases of ibogaine therapy (all at Dr. Mash’s clinic on Saint Kitts) and found that there were no cases of cardiac-related death at doses used for interrupting addiction. Furthermore, Clear Sky Recovery has administered 1000s of Ibogaine sessions without a single fatality.
Iboga rescheduling in the US may be far off, but its potential shouldn’t be underestimated. As Hamilton Morris notes, Ibogaine is “alien technology”, with the potential to help us humans solve some of our greatest medical mysteries. For now, it’s enough to think that it might be able to a create stable, long-term pain medication with no risk of respiratory depression, tolerance, and minimal withdrawal. Along with risk-free… risk tolerant euphoria. Whether that sustainable euphoria will be available to all, remains to be seen.
How people in different (Buddhist) realms interpret pain:
1) Heavenly Realm / God Realm: Pain is impermanent. It’s a trick of the mind. A method to help us wake up and realize who we truly are. [said while peacefully unaware of actual pain due to the formidable amounts of pleasure and distractions on hand]
2) Asura Realm / Titan Realm: Pain is a tool to succeed. It is a challenge to be overcome at a personal level, and a weapon to be used against one’s enemies. If I didn’t suffer intensely for the things that I achieved, would they mean anything? [said while experiencing intense cravings for social recognition and the need to feel superbly significant]
3) Animal Realm: Pain is the separation from my pleasures of the day to day. My morning coffee, interrupted by a call. My conversations with a friend, when someone’s bad luck is brought up. The annoying commercials in-between the chunks of TV I like. [said while snoozing the alarm for the 4th time in a row]
4) Hell Realm: Pain is reality in and of itself. Life is suffering. And if it isn’t at the moment, that’s just temporary good luck. Happiness is merely the absence of suffering; happiness is therefore as good as nonexistence. [said while waiting in the ER while experiencing a kidney stone]
5) Hungry Ghost Realm: Pain is realizing that only 10 out of the 15 people who RSVP’ed to my party showed up. It is the feeling of noticing that the Pringles are almost gone. The feeling that you get when you make out with someone and only get to 2nd base when you could have gotten to 3rd or 4th. [said while scrolling Reddit for the 3rd hour in a row].
6) Human Realm: Pain is a healthy signaling mechanism. When you look at it scientifically, it is just a negative reinforcement signal that propagates throughout your nervous system in order to prevent the chain of causes that led to the current state. It’s nothing to worry about, just as you shouldn’t worry about the weather or the shape of the solar system. [said while dispassionately reading a neuroscience textbook].
[Warning: Disturbing content ahead. Why talk about it? This is an ethically very serious topic and it deserves more attention. But please beware that thinking about this might be bad for one’s mental health.]
One of the key insights that shows why Effective Altruism is so important is that the positive effect on the world that results from donating to various charities follows a long-tail distribution:
It is for this, among other, reasons why focusing on the best interventions really pays off. Where else can we expect long-tails to appear?
In Get-Out-Of-Hell-Free Necklace we discussed how introducing a new metric into the Effective Altruist ecosystem could shed light on neglected cost-effective interventions. We presented the Hell-Index:
A country’s Hell-Index could be defined as the yearly total of people-seconds in pain and suffering that are at or above 20 in the McGill Pain Index (or equivalent)*. This index captures the intuition that intense suffering can be in some ways qualitatively different and more serious than lesser suffering in a way that isn’t really captured by a linear pain scale.
In a future article we will discuss how the quality of suffering as a function of different medical and psychological conditions very likely follows a long-tail distribution. That is, some conditions such as Cluster Headaches (which affect about 1 in 1000 people worldwide) produce pain that is orders of magnitude worse than the pain experienced in other kinds of medical conditions, such as migraines (which are themselves already described as orders of magnitude worse than tension headaches). In other words, a 0-10 pain-scale is better thought of as a logarithmic compression of the true levels of pain rather than a linear scale. So concentrating on the worst conditions could really pay off for reducing suffering in bulk amounts.
Now: the long-tailed nature of suffering may extend beyond the quality of suffering, and show up also in its quantity. That is, the frequency with which people experience episodes of intense suffering, even among those who experience the same kind of suffering, is unlikely to be normally distributed.
Intuitively, one may think that how much suffering people endure on a given year follows a normal distribution. This intuition says that if the median number of hell-seconds people endure in a year is, say, 1,000, then people who are at the 90% percentile of hell-seconds experienced per year will be experiencing something like 1,500 or at most 2,000. If suffering follows a long-tail distribution, in reality the 90% percentile might be experiencing something more akin to 10,000 hell-seconds per year, the 99% percentile something akin to 100,000, and the 99.9% something akin to 1,000,000. If true, such a heavy skew of the distribution would suggest that we should concentrate our energies on addressing the problems of the people who are unlucky to be on the upper ranges, rather than be overly concerned with “the typical person”*.
Unfortunately, I come to share the bad news that suffering probably follows a very long-tail distribution:
It is generally acknowledged that Cluster Headaches are some of the most painful experiences that people endure. Having a single Cluster Headache, lasting anywhere between 15 minutes to 4 hours, is already an ethically unacceptable situation that should never happen to begin with. It is disheartening to know that 1 in 1,000 people experience such extreme pain. But the truth of the matter is yet much worse than we intuitively think…
We recently analyzed a survey** of Cluster Headache patients that was conducted with the intention of determining the reasons why sufferers do or do not use psychedelics to relieve their pain. As it turns out, LSD, psilocybin, and DMT all get rid of Cluster Headaches in a majority of sufferers. Given the safety profile of these agents, it is insane to think that there are millions of people suffering needlessly from this condition who could be nearly-instantly cured with something as simple as growing and eating some magic mushrooms.
We will get back to this in more depth in later articles, but for the time being what we want to highlight is the responses to the question “About how many cluster headaches do you get in a typical year?”.
After cleaning the data***, we end up with 270 participants. We then ranked the values from smallest to largest, and visualize them:
Honestly I am a bit suspicious of the very top numbers (I do not know how you can fit 25,000 Cluster Headaches in a year, so perhaps the participant interpreted the question as “lifetime number of Cluster Headaches”). So, just to be safe, we cut the top 20 highest numbers and visualize the bottom 250 values:
This is clearly a long-tail distribution. And since many people online do claim to have 3 or more Cluster Headaches a day, I am inclined to believe this curve. To zoom in on some parts of the distribution, here are some additional histograms that focus on the lower percentiles:
Bins of 1, responses between 1 and 10 CHs per year.
Bins of 1, responses between 1 and 100 CHs per year.
Bins of 10, responses between 1 and 1000 CHs per year.
Bins of 100, responses between 1 and 2000 CHs per year.
Bins of 10, responses between 1 and 5000 CHs per year.
If we take the logarithm of the number of yearly Cluster Headaches, the distribution looks remarkably normal:
Natural log of the responses to the question “About how many cluster headaches do you get in a typical year?”
I should also point out that the distribution is really close to the 80/20 Pareto principle – we see that the top 20% of the participants contain about 83% of the CH incidents per year. Below you will find the percent of the total number of incidents accounted for by the bottom x% of the respondents:
The bottom 10% accounts for .06% of incidents
The bottom 20% accounts for 0.36% of incidents
The bottom 30% accounts for .95% of incidents
The bottom 40% accounts for 1.82% of incidents
The bottom 50% accounts for 3.17% of incidents
The bottom 60% accounts for 5.54% of incidents
The bottom 70% accounts for 9.56% of incidents
The bottom 80% accounts for 17% of incidents
The bottom 90% accounts for 30% of incidents
The bottom 95% accounts for 43% of incidents
Below we also include the number of yearly Cluster Headaches experiences at different percentiles:
10% percentile experiences 5 CH/year
20% percentile experiences 17 CH/year
30% percentile experiences 30 CH/year
40% percentile experiences 45 CH/year
50% percentile experiences 70 CH/year
60% percentile experiences 105 CH/year
70% percentile experiences 200 CH/year
80% percentile experiences 365 CH/year
90% percentile experiences 730 CH/year
95% percentile experiences 1095 CH/year
98% percentile experiences 2190 CH/year
I believe that this information is crucial to consider when assessing cost-effective interventions to help people who endure intense suffering.
Here are some additional results from the survey.
The following graphs are about the beliefs and attitudes of Cluster Headache sufferers who do not use tryptamines (LSD, psilocybin, DMT, etc.) to treat their condition:
Difficulty getting. 0 – Extremely easy to acquire, 5 – Nearly impossible to acquire
Legal risk. 0 – Not concerned at all, 5 – Extremely concerned
Side effects. 0 – Not concerned at all, 5 – Extremely concerned
Social stigma. 0 – Not concerned at all, 5 – Extremely concerned
I think it is fair to say that the survey shows that one of the biggest barriers preventing CH patients from using tryptamines to treat their condition is simply the difficulty of acquiring them. Since a number of interviews we’ve conducted have shown that even sub-hallucinogenic doses of DMT can abort cluster headaches (writeup coming soon), more education could easily address the barrier of being concerned about hallucinogenic side effects. The social stigma seems like a minor problem, and the legal implications (the hardest to change, perhaps), are a big concern to about half of the participants (ratings of 4 or 5/5). Hence the importance of passing new laws allowing people with this condition to use them without repercussions.
Do CH sufferers who do not use tryptamines think they would work?
And do they work? Here is what the CH sufferers who do use them say:
If we interpret a 2 or 3 in the 0 to 5 scale as an equivalent to a “maybe”, and a 4 or 5 as a “yes” to the question “do they work?” we see a big difference between non-users beliefs in their effectiveness and their reported effectiveness by users. 24% of people who use tryptamines to treat their CHs report that “They have completely eliminated the cluster headaches” and in total 68% mark it as either a 4 or a 5 in the scale (which we can interpret as “working” even if not “completely eliminating them”). This is compared to only 30% of non-users who believe the tryptamines would work. This large discrepancy also suggests that outreach and education could help sufferers give this approach a try.
Finally, we also looked at whether the users and non-users had different number of incidents per year (reasoning that perhaps those who experience more incidents would be more desperate to try legally and socially risky treatments). We notices that there is a very slight difference in the mean (and mean-log) for the number of CH incidents a year between the 20% of sufferers who treat their CHs with tryptamines and those who don’t. I won’t report the difference in the mean because the skew of the distribution makes such a metric deceptive, but the log-mean of yearly incidents of tryptamine users is 4.73 whereas for all the rest it is 4.10 (which reaches statistical significance of p < 0.05 based on a t-test). That said, we don’t think this is a very practically relevant difference. The distributions look roughly the same:
The similarity between these two distributions also suggests that there is a long way to go to make sure that those who are the worse off get prompt access to tryptamines.
See also https://clusterbusters.org/, which is an organization that aims to make psychedelics legally available to people who suffer from this condition. Please consider donating to them to help this very important cause. Also consider donating to MAPS which is championing the use of psychedelics for mental health applications. Finally, consider also donating to organizations that care and strategize about how to reduce intense suffering, such as: QRI, FRI, OPIS, and The Neuroethics Foundation.
*There are instrumental considerations here – if experiencing more than, say, 5,000 hell-seconds in a year is very likely to make you depressed and ineffective, then it might pay-off to also spend resources on keeping as many people as possible below that level. In particular, to be an effective Effective Altruist it pays off not to be heavily depressed and nihilistic.
**Thanks to Harlan Stewart for taking the initiative to conduct this survey. He advertised it on the Facebook groups and subreddits of Cluster Headache sufferers and got 371 responses.
***Some people provided numerical answers, which we used directly. Some other people provided ranges, in which case we used the middle point between the values provided (e.g. “200 to 300” was coded as “250”). Some people provided lower bounds, in which case we simply used such lower bound (e.g. “500+” was coded as “500”). We discarded the data of people who didn’t provide an answer in any of those formats – which left 270 participants. A more strict analysis that uses *only* the numerical responses results in the same observations listed above (e.g. the distribution is equally long-tailed and it appears to be log-normal).
For some, abstinence from narcotic analgesics is not a reality-based goal. Many chronic pain patients are really not going to cast off their crutches [sic], light up some medical marijuana and dance in the meadow, after ibogaine.
In addition to chronic-pain patients, there are many people who are using narcotic analgesics to self-medicate a variety of comorbid conditions. In some cases a “successful” detox from opiates means that somebody can look forward to a lifetime’s worth of maintenance on neuroleptics.
Given the choice between opiates and neuroleptics, there is no simple answer, but the side-effects of current anti-psychotic medications can be devastating. When you compare the quality of someone’s life when they are controlling schizophrenia, for example, through the use of opiates (which tend to have extremely mild side effects) vs. the qualify of life attained using sanctioned medicines (usually neuroleptics, with Cogentin to alleviate some of the side-effects anti-psychotics produce), it is entirely possible, even probable, that the person is happier with the opiates.
Ibogaine is remarkably effective in addressing one of the primary problems in any sort of opiate or opioid maintenance: tolerance. Over time, individuals find they must do extremely high doses of their medications in order to achieve any effect whatsoever.
WARNING: the following category should be considered highly experimental. There is a complete lack of published scientific data regarding the following examples. The difference between 50mg and 500mg is extremely significant and quite possibly fatal. Ibogaine potentiates the analgesic effect of opiates and opioids.
Individual 1: Male, mid-30’s, in good health, who has experienced full-blown resets using ibogaine HCl in the past. His average daily intake was 20Mgs oxycodone and 4–6Mgs hydromorphone (Dilaudid), which he is prescribed for pain management.
By using a very low-dose regimen of 25–50Mgs of ibogaine HCl on a daily basis, he was able to taper down to a point at which 3.75Mg of oxycodone is subjectively providing him with identical pain relief.
He began by taking 25Mg ibogaine HCl per day, and was able to immediately halve his intake of narcotic analgesics with no withdrawal symptoms or discomfort whatsoever. After 6 days he increased the ibogaine HCl to 40Mg, and at week two, he went up to 50Mg a day of ibogaine HCl. After 22 days of ibogaine maintenance, he took a ten day break, before returning to 50Mg which he presently takes every other day. His intake of oxycodone has remained consistent at 3.75Mg/day.
In his own words, “The goal with adding ibogaine to the oxycodone is to minimize if not end the need for it [oxycodone] for pain management. The HCl seems to help with the pain, or at least gives me awareness to take better care of my body by stretching, drinking more water and to get outside for exercise and sunshine.”
“Most importantly the HCl has given me a feeling of well being and feeling comfortable in my place in the universe, allowing me to process through a depression I have been suffering from. I feel GREAT. The darkness has lifted, the impending doom is cast away! The low dose regimen has also been extremely helpful in musical inspiration; songs I had half-written are coming to completion and new songs are being created. There is a distinct connection between ibo and rhythm/melody, and further underscores for me the important aspect of music in the Bwiti ceremonies.”
Individual 2: Female, early 40s, overall good health but suffering from anorexia, has been physically dependent on narcotic analgesics for 19 years. Her use started with heroin and eventually shifted to methadone maintenance and finally hydromorphone (Dilaudid). She has extreme fear and dislike of “tripping” and has repeatedly refused to take a full-blown ibogaine reset.
Her average daily intake was 28Mg of hydromorphone which she “cold-shakes” (breaks down the pills in a cooker so they can be injected) and IVs.
She began by doing 35Mg of ibogaine HCl and was immediately able to stop injecting the hydromorphone and obtained similar analgesia from 24Mg of Dilaudid. Over a period of five days she maintained on 35Mg of ibogaine HCl while continuously decreasing the hydromorphone, which she was taking orally, as prescribed. After five days she was on 16Mg of hydromorphone.
At the start of day 8 she began attending psychotherapy. Over the next two weeks she gradually increased her intake of ibogaine HCl to 50Mg/day, and decreased hydromorphone to 6Mg. On day 19, she took a 10 day break from ibogaine HCl, and her hydromorphone intake rose back to 12Mg/daily (oral), before tapering back down to 6Mg/day within hours of restarting ibogaine maintenance at 35Mg.
At six months out, this cycle appears to be consistent. She takes a break from ibogaine maintenance every 20 days. Slowly drifts from 6Mg/day of hydromorphone, up to 12Mg, before restarting ibogaine at 35Mg/day, at which point she drops back to 6Mg—which appears to be her comfort zone—while gradually increasing ibogaine HCl to 50Mg/day.
She has plans to try a 500Mg dose of ibogaine HCl, and attempt complete cessation of narcotic analgesics.