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.
*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]