Consciousness researcher and co-founder of the Qualia Research Institute. I blog at qualiacomputing.com
Core interests span—measuring emotional valence objectively, formal models of phenomenal space and time, the importance of phenomenal binding, models of intelligence based on qualia, and neurotechnology.
Agmatine is an aminoacid you can buy over the counter at supplement stores and online. It is used as a workout supplement, to make weed feel stronger, and as a hangover prevention remedy. Agmatine has a high affinity for a number of receptors sites, and it is currently being debated whether it satisfies the criteria for being called a neurotransmitter.
Of particular note is agmatine’s high affinity to the imidazoline receptor, which according to Thomas Ray- who analyzed the receptor affinity of 30+ psychedelics- might be one of the keys to the “magic of MDMA”. On 2o to 80mg doses on an empty stomach, agmatine does have a nice and very mild positive effect on valence. Mild relaxation, akin to chamomile tea, and mild feeling of social closeness, akin to a glass of wine or a bit of Indica. According to some anecdotal data, and in line with Thomas Ray’s predictions, taking agmatine in conjunction with 5HT2A agonists gives rise to a subtle empathogenic effect.
Now, all of that is for background. If you buy a tube of agmatine you will see that the recommended dose is between 500 milligrams and up to entire grams. After all, it is in food and it has an extremely high safety profile. Somehow the general public has missed that on much lower doses it has a nice mild euphoric quality. Anyhow, at the doses typically consumed, agmatine has a distinct blunting effect. As described by people who have both taken SSRIs and agmatine, the effects of high-dose agmatine on pleasurable and noxious stimuli are of the general type of “blunted quality”. Emotions feel more fuzzy, music sounds more flat, thoughts seem less deep, philosophy is more boring, and orgasm is less intense. This type of effect (both cutting the top and bottom ends of valence) is what we expect to happen if you add *neural noise* into your nervous system. Like listening to white noise—it is good if the sound it masks is dissonant and unpleasant, but bad if you are trying to listen to a symphony, or to the voice of your loved ones.
It is the blunting effect of agmatine at 0.5 grams+ doses that makes it a great candidate to reduce the impact of brainwashing. Like an SSRI, but much faster and reversibly, agmatine will make whatever multilevel marketing pyramid scheme feelings of guilt and greed you were subjected to kind of melt away and feel more dreamy and less “real”. This psychological effect seems to last after the agmatine has been metabolized.
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 discussed multiple times before, 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 together (e.g. combining deference analysis, descriptions of pain scales by their creators, latent-trait analysis, psychophysics, and so on).
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). In turn, this strongly suggests that investigating 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 any way 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 one’s 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), 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 progres) 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 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 that freaking skewed 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: 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.
Let’s tackle 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 could 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, in order to fully articulate 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 are 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 I would suggest that there are good reasons to care no matter how antithetical one’s view is 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 end 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 precise mathematical optimization for 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!
For context, this post is motivated by the realization that pain-scales are logarithmic compressions of what is probably an exponentially-increasing capacity for pain and suffering in sentient beings. Here is a simple example, as told by the guy who stung himself with 80+ insects to put the pain on a scale:
4:28 - The harvester ants is what got the sting pain scale going in the first place. I had been stung by honey bees, old jackers, 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. I got stung and I said “Wooooow! This is DIFFERENT!” You know? I thought I knew everything there was about sting insects, I was just this dumb little kid. And 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 what’s later—it’s unique! [unique type of pain].
7:09 - I didn’t really wanted 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 hurst, 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 pains 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.
Some EAs have already pointed this out, but I suspect that this has yet to make it into “EA Canon” and it thus hasn’t really given rise to novel interventions. Brian Tomasik, Jonathan Leighton, Manu Herran, David Pearce, and other “suffering focused ethics” people have been saying this for a while. Read more here.
I realize that it is always kind of depressing to look into how bad suffering gets, but it does seem important to know if one is indeed trying to reduce suffering as much as possible.
Thank you.
Two things:
(1) We are trying to arrive at a metric like you describe at QRI. See: Quantifying bliss and a future for neuroscience for the big-picture idea. I think the suffering you describe is very relevant for instrumental reasons, but perhaps not very large in terms of absolute values (still sucks, obviously!).
(2) I think that another important update that people should make in EA is that hell-seconds are not only much, much, much worse than garden-variety pain and suffering. But also that they are *far more prevalent* than we realize. About 20% of people in the US live with chronic pain, of which 8% is “high-impact” (i.e. severe enough to interfere with life on many fronts). Kidney stones happen to 10% of people, migraines are equally as common, and about 2-3% of people who get fractures develop complex regional pain syndrome, which tops the scale (and worse of all, it is chronic and persistent pain rather than episodic like cluster headaches).
I suspect most people will be horrified when we get an accurate estimate of a country’s Hell-Index. Perhaps you don’t dip your toes into those realms often, but chances are that your neighbor or two houses down the line someone very close to you does.
Hi Aidan!
Thank you ^_^
We are collaborating with John Hopkins and Stanford researchers on a couple of studies involving the analysis of neuroimaging data of high-valence states of consciousness. Additionally, we are currently preparing two key publications for peer-reviewed journals on our core research areas.
Off the top of my head, some well-known researchers and intellectuals that are very positive about our work include: Robin Carhart-Harris, Scott Alexander, David Pearce, Steven Lehar, Daniel Ingram, etc. (e.g. Scott acknowledged that QRI put together the paradigms that contributed to Friston’s integrative model of how psychedelics work before his research was published). Our track record so far has been to foreshadow by several years in advance key discoveries later proposed and accepted in mainstream academia. Given our current research findings, I expect this to continue in the years to follow.
Cheers! :)
Thank you Gavin (algekalipso here).
I think that the most important EA-relevant link for #1 would be this: Logarithmic Scales of Pleasure and Pain: Rating, Ranking, and Comparing Peak Experiences Suggest the Existence of Long Tails for Bliss and Suffering
For a summary, see: Review of Log Scales.
In particular, I do think aspiring EAs should take this much more seriously:
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).
Best,
Andrés :)
People are asking for object-level justifications for the Symmetry Theory of Valence:
The first thing to mention is that the Symmetry Theory of Valence (STV) is *really easy to strawman*. It really is the case that there are many near enemies of STV that sound exactly like what a naïve researcher who is missing developmental stages (e.g. is a naïve realist about perception) would say. That we like pretty symmetrical shapes of course does not mean that symmetry is at the root of valence; that we enjoy symphonic music does not mean harmony is “inherently pleasant”; that we enjoy nice repeating patterns of tactile stimulation does not mean, well, you get the idea...
The truth of course is that at QRI we really are meta-contrarian intellectual hipsters. So the weird and often dumb-sounding things we say are already taking into account the criticisms people in our people-cluster would make and are taking the conversation one step further. For instance, we think digital computers cannot be conscious, but this belief comes from entirely different arguments than those that justify such beliefs out there. We think that the “energy body” is real and important, except that we interpret it within a physicalist paradigm of dynamic systems. We take seriously the possible positive sum game-theoretical implications of MDMA, but not out of a naïve “why can’t we all love each other?” impression, but rather, based on deep evolutionary arguments. And we take seriously non-standard views of identity, not because “we are all Krishna”, but because the common-sense view of identity turns out to, in retrospect, be based on illusion (cf. Parfit, Kolak, “The Future of Personal Identity”) and a true physicalist theory of consciousness (e.g. Pearce’s theory) has no room for enduring metaphysical egos. This is all to say that straw-manning the paradigms explored at QRI is easy; steelmanning them is what’s hard. Can anyone here make a Titanium Man out of them instead? :-)
Now, I am indeed happy to address any mischaracterization of STV. Sadly, to my knowledge nobody outside of QRI really “gets it”, so I don’t think there is anyone other than us (and possibly Scott Alexander!) who can make a steelman of STV. My promise is that “there is something here” and that to “get it” is not merely to buy into the theory blindly, but rather, it is what happens when you give it enough benefit of the doubt, share a sufficient number of background assumptions, and have a wide enough experience base that it actually becomes a rather obvious “good fit” for all of the data available.
For a bit of history (and properly giving due credit), I should clarify that Michael Johnson is the one who came up with the hypothesis in Principia Qualia (for a brief history see: STV Primer). I started out very skeptical of STV myself, and in fact it took about three years of thinking it through in light of many meditation and exotic high-energy experiences to be viscerally convinced that it’s pointing in the right direction. I’m talking about a process of elimination where, for instance, I checked if what feels good is at the computational level of abstraction (such as prediction error minimization) or if it’s at the implementation level (i.e. dissonance). I then developed a number of technical paradigms for how to translate STV into something we could actually study in neuroscience and ultimately try out empirically with non-invasive neurotech (in our case, light-sound-vibration systems that produce multi-modally coherent high-valence states of consciousness). Quintin Frerichs (who gave a presentation about Neural Annealing to Friston) has since been working hard on the actual neuroscience of it in collaboration with Johns Hopkins University, Daniel Ingram, Imperial College and others. We are currently testing the theory in a number of ways and will publish a large paper based on all this work.
For clarification, I should point out that what is brilliant (IMO) about Mike’s Principia Qualia is that he breaks down the problem of consciousness in such a way that it allows us to divide and conquer the hard problem of consciousness. Indeed, once broken down into his 8 subproblems, calling it the “hard problem of consciousness” sounds as bizarre as it would sound to us to hear about “the hard problem of matter”. We do claim that if we are able to solve each of these subproblems, that indeed the hard problem will dissolve. Not the way illusionists would have it (where the very concept of consciousness is problematic), but rather, in the way that electricity and lightning and magnets all turned out to be explained by just 4 simple equations of electromagnetism. Of course the further question of why do those equations exist and why consciousness follows such laws remains, but even that could IMO be fully explained with the appropriate paradigm (cf. Zero Ontology).
The main point to consider here w.r.t. STV is that symmetry is posited to be connected with valence at the implementation level of analysis. This squarely and clearly distinguishes STV from behaviorist accounts of valence (e.g. “behavioral reinforcement”) and also from algorithmic accounts (e.g. compression drive or prediction error minimization). Indeed, with STV you can have a brain (perhaps a damaged brain, or one in an exotic state of consciousness) where prediction errors are not in fact connected to valence. Rather, the brain evolved to recruit valence gradients in order to make better predictions. Similarly, STV predicts that what makes activation of the pleasure centers feel good is precisely that doing so gives rise to large-scale harmony in brain activity. This is exciting because it means the theory predicts we can actually observe a double dissociation: if we inhibit the pleasure centers while exogenously stimulating large-scale harmonic patterns we expect that to feel good, and we likewise expect that even if you activate the pleasure centers you will not feel good if something inhibits the large-scale harmony that would typically result. Same with prediction errors, behavior, etc.: we predict we can doubly-dissociate valence from those features if we conduct the right experiment. But we won’t be able to dissociate valence from symmetry in the formalism of consciousness.
Now, of course we currently can’t see consciousness directly, but we can infer a lot of invariants about it with different “projections”, and so far all are consistent with STV:
Of especial note, I’d point you to one of the studies discussed in the 2020 STV talk: The Human Default Consciousness and Its Disruption: Insights From an EEG Study of Buddhist Jhāna Meditation. It shows a very tight correspondence between jhanas and various smoothly-repeating EEG patterns, including a seizure-like activity that unlike normal seizures (of typically bad valence) shows up as having a *harmonic structure*. Here we find a beautiful correspondence between (a) sense of peace/jhanic bliss, (b) phenomenological descriptions of simplicity and smoothness, (c) valence, and (d) actual neurophysiological data mirroring these phenomenological accounts. At QRI we have similarly observed something quite similar studying the EEG patterns of other ultra-high-valence meditation states (which we will hopefully publish in 2022). I expect this pattern to hold for other exotic high-valence states in one way or another, ranging from quality of orgasm to exogenous opioids.
Phenomenologically speaking, STV is not only capable of describing and explaining why certain meditation or psychedelic states of consciousness feel good or bad, but in fact it can be used as a navigation aid! You can introspect on the ways energy does not flow smoothly, the presence of blockages and pinch points make it reflect in discordant ways, or zone in on areas of the “energy body” that are out of synch with one another and then specifically use attention in order to “comb the field of experience”. This approach—the purely secular climbing of the harmony gradient leads all of its own to amazing high-valence states of consciousness (cf. Buddhist Annealing). I’ll probably make a video series with meditation instructions for people to actually experience this on themselves first hand. It doesn’t take very long, actually. Also, STV as a paradigm can be used in order to experience more pleasant trajectories along the “Energy X Complexity landscape” of a DMT trip (something I even talked about at the SSC meetup online!). In a simple quip, I’d say “there are good and bad ways of vibing on DMT, and STV gives you the key to the realms of good vibes” :-)
Another angle: we can find subtle ways of dissociating valence from e.g. chemicals: if you take stimulants but don’t feel the nice buzz that provides a “working frame” for your mental activity, they will not feel good. At the same time, without stimulants you can get that pleasant productivity-enhancing buzz with the right tactile patterns of stimulation. Indeed this “buzz” that characterizes the effects of many euphoric drugs (and the quality of e.g. metta meditation) is precisely a valence effect, one that provides a metronome to self-organize around and which can feel bad when you don’t follow where it takes you. Literally, one of the core reasons why MDMA feels better than LSD which feels better than DOB is precisely because the “quality of the buzz” of each of these highs is different. MDMA’s buzz is beautiful and harmonious; DOB’s buzz is harsh and dissonant. More so, such a buzz can work as task-specific dissonance guide-rails, if you will. Meaning that when you do buzz-congruent behaviors you feel a sense of inner harmony, whereas when you do buzz-incongruent behaviors you feel a sense of inner turmoil. Hence what kind of buzz one experiences is deeply consequential! All of this falls rather nicely within STV—IMO other theories need to keep adding epicycles to keep up.
Hopefully this all worked as useful clarifications.
To zoom in on the “logarithmic scales of pleasure and pain” angle (I’m the author), I would say that this way of seeing the world suggests that the bulk of suffering is concentrated on a small percentage of experiences. Thus, finding scaleable treatments specially for ultra-painful conditions could take care of a much larger percent of the world burden of suffering than most people would intuitively realize. I really think this should be up in the list of considerations for Cause X. Specifically:
An important pragmatic takeaway from this article is that if one is trying to select an effective career path, as a heuristic it would be good to take into account how one’s efforts would cash out in the prevention of extreme suffering (see: Hell-Index), rather than just QALYs and wellness indices that ignore the long-tail. Of particular note as promising Effective Altruist careers, we would highlight working directly to develop remedies for specific, extremely painful experiences. Finding scalable treatments for migraines, kidney stones, childbirth, cluster headaches, CRPS, and fibromyalgia may be extremely high-impact (cf. Treating Cluster Headaches and Migraines Using N,N-DMT and Other Tryptamines, Using Ibogaine to Create Friendlier Opioids, and Frequency Specific Microcurrent for Kidney-Stone Pain). More research efforts into identifying and quantifying intense suffering currently unaddressed would also be extremely helpful.
(see also the writeup of an event we hosted about possible new EA Cause Xs)
Now that the California fires are raging, it may be time to bring up a few additional reasons why HEPA filters make a lot of sense. I don’t know how much this changes the cost-benefit analysis, but I think it is important to take into account:
1) Right now the PM2.5 outside my apartment is 230. Inside it’s 40. A week ago the PM2.5 was 100, and inside it was 8. By having a HEPA filter inside, I’ve been seeing reductions of PM2.5 between 80% and 90%. I also saw this two years ago, and it’s been a rather consistent pattern.
2) The idea that non-linearity makes the benefits strictly less than linearity, and therefore that assuming linearity will lead to an optimistic assessment is questionable. In particular, I grant this is true with “diminishing returns” curves. But it’s not true with S-shaped curves. So, if it is true that the negative health effects of PM2.5 are concave below 20 and convex above 20, then the assumption of linearity will lead to an underestimation of the positive health benefits of HEPA filters for places with relatively clean air.
3) As a special case of (2), I would expect that giving your lungs “time to breath” (so to speak) might be really good to let them heal, and also allow your cardiovascular system to recover from inflammation. So there may be some extra benefits to being in places that have close to 0PM2.5 for at least some periods of time. And lastly,
4) I do think that the case for massively reducing the economic cost of HEPA filters should be considered more thoroughly. If subsidized at the governmental level, how cheap could these filters become? My suspicion is that they can become extremely cheap, turning them into a utility.
Thank you for the analysis and for bringing this topic to attention of EAs (whose saved micromorts may, well, ultimately have compounding benefits for all). Cheers!
This post significantly adds to the conversation in Effective Altruism about how pain is distributed. As explained in the review of Log Scales, understanding that intense pain follows a long-tail distributions significantly changes the effectiveness landscape for possible altruistic interventions. In particular, this analysis shows that finding the top 5% of people who suffer the most in a given medical condition and treating them as the priority will allow us to target a very large fraction of the total pain such a condition generates. In the case of cluster headaches, the distribution is extremely skewed: 5% of sufferers experience over 50% of all cluster headaches.
More so, the survey also showed that the leading cause for why sufferers don’t use tryptamines to treat their condition is the difficulty of acquiring them. Thus, changing the legal landscape via e.g. providing programs for the easy access to tryptamines to sufferers of migraines and cluster headaches might be a very cost-effective way of massively reducing suffering throughout the world.
Zooming out, perhaps the significance of this goes beyond cluster headaches in particular: it perhaps hints at a more significant paradigmatic change for analyzing the cost-effectiveness of interventions.
Thank you. The survey said that 68% of sufferers who have used psychedelics found gave them a rating of 4 or 5, where 5 means “They have completely eliminated the cluster headaches”. I would certainly stand by the claim 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’ve interviewed people for whom sub-hallucinogenic doses of DMT and psilocybin took a 10⁄10 pain CH all the way to a 1⁄10 or 0⁄10. And in the case of DMT, due to its method of administration, this takes place within seconds (more than one but less than 10). Even if this works only for, say, 20% of the sufferers, it is still millions in absolute terms.
Thanks for saying: “Generally I really find this research agenda interesting”. My experience has been that few people take seriously the long-tails of pleasure and pain. This is precisely the sort of missing piece of information that can add an entire new wing to EA.
Thanks for writing this.
How would this model explain Cluster Headaches? They are not particularly more incapacitating than migraines, yet they are (possibly literally*) thousands of times more acutely painful than them. What is the role of this X1000 multiplier on phenomenal pain in such cases? As far as I can tell, in the ancestral environment nobody could have done anything to help you if you were having a Cluster Headache, and your chances of reproduction seem to be the same whether that pain was a thousand times less bad (which would still be VERY bad, but not in the level of ultra-Hellish pain). In particular, other species are known the have Cluster Headaches too, such as cats. So perhaps we should cluster pains into two buckets—those that have social significance and those that don’t. I worry that this study will make people dismiss extreme suffering in nonhuman animals, but that should only really apply to socially-useful pains. I suspect that there are many species-specific ultra-painful experiences that we will not discover (and prioritize!) unless we look for them.
Do you think that the empirical finding that pain and suffering are distributed along a lognormal distribution (cf. Logarithmic Scales of Pleasure and Pain) has implications for how to prioritize causes? In particular, what do you say about these tentative implications:
Of particular note as promising Effective Altruist careers, we would highlight working directly to develop remedies for specific, extremely painful experiences. Finding scalable treatments for migraines, kidney stones, childbirth, cluster headaches, CRPS, and fibromyalgia may be extremely high-impact (cf. Treating Cluster Headaches and Migraines Using N,N-DMT and Other Tryptamines, Using Ibogaine to Create Friendlier Opioids, and Frequency Specific Microcurrent for Kidney-Stone Pain). More research efforts into identifying and quantifying intense suffering currently unaddressed would also be extremely helpful. Finally, if the positive valence scale also has a long-tail, focusing one’s career in developing bliss technologies may pay-off in surprisingly good ways (whereby you may stumble on methods to generate high-valence healing experiences which are orders of magnitude better than you thought were possible).
Thank you!!!
Like many other problems that EAs are aware of, the particular incident you described comes from an outlier that drives the mean significantly forward (I of course know who you are talking about, and the fact that many who’ve been in EA for a long time know as well should indicate that this is both rare in terms of % of people yet perhaps not that rare in terms of % of drama it accounts for).
The key insight here is that the long-tail matters. As a rough prior we could anticipate that 80% of the drama will come from 20% of people (in my experience this is even more skewed, to perhaps 98% of drama coming from 2% of people). In which case, advocating for self-censorship in general in the community is stifling and unnecessary for the bulk of people (who already doubt themselves), and desperately necessary for the outliers who just march forward without much self-awareness in some or other controversial direction, as if mandated by a higher power to cause as much drama as possible.
If we recognize that the problem per person follows a long-tail distribution, our strategies should look very different than if it was a kind of normal/Gaussian distribution.
*Logarithmic Scales of Pleasure and Pain*
Recall that while some distributions (e.g. the size of the leaves of a tree) follow a Gaussian bell-shaped pattern, many others (e.g. avalanches, size of asteroids, etc.) follow a long-tail distribution. Long-tail distributions have the general property that a large fraction of the volume is accounted for by a tiny percent of instances (e.g. 80% of the snow that falls from the mountain will be the result of the top 20% largest avalanches).
Keeping long-tails in mind: based on previous research we have conducted at the Qualia Research Institute we have arrived at the tentative conclusion that the intensity of pleasure and pain follows a long-tail distribution. Why?
First, neural activity on patches of neural tissue follow log-normal distributions (an instance of a long-tail distribution).
Second, the extremes of pleasure and pain are so intense that they cannot conceivably be just the extremes of a normal distribution. This includes, on the positive end: Jhana meditation, 5-MeO-DMT peak experiences, and temporal lobe epilepsy (Dostoevsky famously saying he’d trade 10 years of his life for just a few moments of his good epileptic experiences). On the negative end, things like kidney stones, cluster headaches, fibromyalgia, and migraines top the charts of most intense pain.
And third, all of the quantitative analysis we conducted on a survey about people’s best and worst experiences showed that the ratings, comparisons, and rankings of such experiences was far more consistent with a long-tail distribution than a normal distribution. The data could not be explained with a Gaussian distribution; it fit very nicely a log-normal distribution.
This is an *important*, *tractable*, and *neglected* cause.
1) Important because we may be able to reduce the world’s suffering by a significant amount if we just focus on preventing the most intense forms of suffering.
2) Tractable because there are already many possible effective treatments to these disorders (such as LSD microdosing for cluster headaches, and FSM for kidney stones).
3) And neglected because most people have no clue that pain and pleasure go this high. Most utilitarian calculus so far seems to assume a normal distribution for suffering, which is very far from the empirical truth. Bentham would recoil at the lack of an exponent term when additively normalizing pain scales.
Importantly, in Effective Altruism there might be an implicit “youth” bias involved in the lack of knowledge of this phenomenon—due to the age of the people in the movement, most EA activists will not themselves have had intensely painful experiences. Thus, why it is so crucial to raise awareness about this topic in the community (it does not show up on its own). Simply put: because the logarithmic nature of pleasure and pain is *news* to most people in EA.
For more, see the original article: Logarithmic Scales of Pleasure and Pain
And a presentation about it that I shared at the New York EA chapter: https://youtu.be/IeD3nZX1Sr4
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[I would prefer the late session if possible]
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[June 22 2020 edit: Thank you all for attending and/or voting for this talk! I appreciated your engagement and questions! For people who would like to see the video, here it is: Effective Altruism and the Logarithmic Scales of Pleasure and Pain]