2025-06-30 04:52:32
Cartoons Hate Her tests the internet’s current favorite question: Do Women Have to Lie About Their Jobs to Get More Hinge Matches? Results are sadly paywalled but otherwise it’s a great effort, more of this please!
This blog post is ostensibly about AI, but it’s also one of the most lucid descriptions of academic incentives we’ve ever seen. Especially given how short it is. Highly recommended: Thoughts on the AI 2027 discourse
We know how to fix peer review (Part 2)
The things we are most afraid of are already happening, and will continue to get worse. It feels counter intuitive, but we’re holding tightly onto the feeling of control, and safety, and that is ITSELF what is putting us in danger & making things worse.
Tyler Ransom: Diet Trials of the first half of 2025 (Potato diet success; Honey riff failure)
John Lawrence Aspden tries a sort of potato diet: Ex150ish-fruit-and-chips
So on the 31st of May I ate a load of chips (steak fries US readers), two potatoes cut into thick oblongs and shallow-fried in butter.
And since then I’ve been eating such things pretty regularly, to the point where I’ve got a bit sick of them, which wasn’t a mental state I knew existed. Sometimes I have made them with yams instead.
I’ve have to raw-dawg a plain can of sardines in water as my only breakfast item daily to keep my brain from oozing out of my eye sockets (h/t @E_III_R) — post seems to have been deleted but here’s an archive.
Thrilled to see this, and kudos to Astera for having the guts to do what everyone else in their heart knows they should: Scientific Publishing: Enough is Enough
The headline is so catchy that it seems like it can’t possibly replicate, and yet: Glass bottles found to contain more microplastics than plastic bottles
Optimizing tea: An N=4 experiment
« Untold Stories » are Sherlock Holmes investigations mentioned in the Sherlock Holmes stories but never published. For example:
When I look at the three massive manuscript volumes which contain our work for the year 1894 I confess that it is very difficult for me, out of such a wealth of material, to select the cases which are most interesting in themselves and at the same time most conducive to a display of those peculiar powers for which my friend was famous. As I turn over the pages I see my notes upon the repulsive story of the red leech and the terrible death of Crosby the banker. Here also I find an account of the Addleton tragedy and the singular contents of the ancient British barrow. The famous Smith-Mortimer succession case comes also within this period, and so does the tracking and arrest of Huret, the Boulevard assassin- an exploit which won for Holmes an autograph letter of thanks from the French President and the Order of the Legion of Honour. Each of these would furnish a narrative, but on the whole I am of opinion that none of them unite so many singular points of interest as the episode of Yoxley Old Place, which includes, not only the lamentable death of young Willoughby Smith, but also those subsequent developments which threw so curious a light upon the causes of the crime.
— Dr. Watson.
2025-06-19 04:14:35
In the beginning, scientific articles were just letters. Eventually Henry Oldenburg started pulling some of these letters together and printing them as the Philosophical Transactions of the Royal Society, the first scientific journal. In continuance of this hallowed tradition, here at SLIME MOLD TIME MOLD we occasionally publish our own correspondence as a new generation of philosophical transactions.
Today’s correspondence is from a husband and wife who wish to remain anonymous. This account has been lightly edited for clarity, but what appears below is otherwise the original report as we received it.
The potato diet has mostly been used for weight loss, but it’s also notable for involving mostly one food and being close to nutritionally complete, which means you can use it as an elimination diet to study things like food triggers. We’ve been interested in this idea for a long time, and we find this case study particularly compelling because it’s a rare example of someone doing just that!
Since around 2018, K had been suffering from stomach pain, bloating, gas, and chronic constipation. Chronic constipation worsened after two pregnancies, so K sought medical intervention again in Feb 2025. K was prescribed medication (Linzess) to treat the constipation, which initially improved symptoms but was unreliable and had unpleasant side effects. She had been on that medication for 1 month before starting the potato diet.
Family and friends were bewildered to hear our plan, warning us of muscle loss and blood sugar problems since potatoes are ‘bad’.
Her initial goal was to lose 5-10 pounds from a starting BMI of 23.4 and test out the claims we read online about the diet. K actually joked, “wouldn’t it be funny if this diet fixes my stomach problems?”
We started the diet on 21MAR2025. The first two and a half days were 100% potato for both of us. Morale was suffering by the afternoon of day 3, so we caved and had a potato-heavy dinner with our kids. Afterwards, we agreed to eat only potatoes until dinner so we could still have a normal family meal time. We did make sure potatoes featured heavily in the weekly meal plan.
Within a week, K noticed improved symptoms and regularity without any medication. Initially, she thought she might have a lactose intolerance, so she switched to lactose-free milk and quit the potato diet once we reached the end of our planned testing window.
Back on a regular diet (but still avoiding lactose), K’s symptoms came back worse, with constant stomach aches and bloating. K realized that she had unintentionally been on a low-FODMAP diet while on the potato diet and decided to do intolerance testing.
Her methodology for intolerance testing follows:
Incorporating lots of potatoes allowed K to test out food groups while still eating a well-balanced diet. The culprit for K is fructans from wheat, which is why cutting out daily servings of wheat has made her symptoms disappear.
K is finishing FODMAP testing (still a couple more groups to go), but has had reliable relief from all symptoms without any meds. Potatoes are a regular addition to meals these days.
Below is the blank version of the log she used.
2025-05-30 21:00:31
Finding the Best Sleep Tracker
Environmental allergies are curable? (Sublingual immunotherapy)
Is Australian Sunscreen ACTUALLY stronger than Asian Sunscreen? I put them to the test!
Join the Big Taping Truth Trial / Let’s Find Out If Mouth Taping Actually Works
Dynomight: My 16-month theanine self-experiment
Oh my dear f*cking gawd it worked. The damn coke and French fries worked – Annals of Reddit Migraine Cures (more study needed)
“8 months later and we now have HUMAN GRADE horseade bucket”
China Might Have Moved Too Fast on Lithium Production
The Church FAQ — “A few years ago, we bought a church building. Since then, every time I mention it online and/or on social media, someone always responds, “wait, you bought a church, what” and then asks some standard questions. At this point it makes good sense to offer up a Church FAQ to answer some of those most common questions. Let’s begin!”
Flipping the switch on far-UVC (h/t Matt)
Serious Music — “A new paper in Science Robotics reports a device that Schumann would have jumped at the chance to try: a robotic exoskeleton for the hand.”
Sauropod Vertebra Picture of the Week: If you believe in “Artificial Intelligence”, take five minutes to ask it about stuff you know well
The hardest working font in Manhattan
The Unbearable Loudness of Chewing
Brighter: The World’s Brightest Floor Lamp
In Which I Declare War On Beloved Entertainer Bo Burnham
“boiled eggs suck because yolk and white are best cooked at diff. temperatures”:
> Nature paper figures out how to cook eggs evenly by duty-cycling the temperature of water between 30°C and 100°C every 2 mins, derived from a model of heat transfer between yolk and white
> @sdamico implements the paper using his stoves that can hold water steady at 30°C and 100°C
2025-05-16 01:12:38
Previous Philosophical Transactions:
This account has been lightly edited for clarity, but what appears below is otherwise the original report as we received it.
Hi Slimes,
I’ve recently wrapped up a year-long weight loss self-experiment. During this time I lost 50 lbs, most of it on a Potatoes + Dairy version of the potato diet.
This corroborates your recent case studies where Potatoes + Dairy caused just about as much weight loss as the standard potato diet. It certainly worked well for me. I found the diet really enjoyable, my meals were always delicious. I didn’t get tired of the potatoes, they remain one of my favorite foods. And there were a few other interesting findings as well, all described below.
I’m a longtime reader of the blog so this is me sending you my report, which you can publish if you like. Please list me as “Cole” (not my real name). I hope you find it helpful.
First, my demographics. I’m a white male American in my early-mid 30s. I’m about 5 feet 11 inches tall, but I have a large frame. While you should feel free to calculate my BMI at any point, I don’t think it’s a very accurate measure of adiposity in my case.
My first baseline is in mid 2022, when I weighed about 220 lbs. I know this because I tried a version of the potato diet at the time and lost about 10 lbs over about 40 days. I wasn’t seriously concerned with my weight at the time, I was mostly just curious about the potato diet and what it feels like “from the inside”. But this turned out to be relevant later on because it let me know that I’m a potato diet responder.
In mid 2022 I was about to start a new job, one that involved a lot of hard work, stress, and late nights, and also a longer commute / a lot more driving than I am used to (I mention this because I’m sympathetic to the hypothesis that obesity is linked to motor vehicle exposure in some way).
I didn’t notice at first, but after starting this new job, I started to gain weight. Around April 2024, I realized that I weighed almost 250 lbs. This was heavier than I had ever been before, and also quite uncomfortable. For anyone who’s never gained 10+ lbs before, let me tell you, it makes everything in your life just a little more difficult, including things like sleeping, and that sucks.
But this crisis turned into an opportunity: I was about to change jobs again, this time to a job with much more reasonable hours and that required almost no driving. I wanted to lose the weight anyways, so I decided to take this opportunity to run a series of diet experiments and investigate some of the findings you’ve presented on the blog.
I began the study on May 12, 2024, with a starting weight of 247.6 lbs. Per previous potato diet experiments, I weighed myself in my underwear every morning for consistency.
To track my weight and my progress, I used a google sheet based on the one you shared from Krinn’s self-experiment with drinking high doses of potassium. I found her columns tracking 7-day average, personal best, and “ratchet” to be pretty helpful. Would recommend for anyone else trying a weight loss self-experiment.
I didn’t start any new exercise habit, though as I mentioned, I did start a new job and was driving less, I no longer had a weekly commute. So it’s possible that some of the weight loss is from “lifestyle changes” but I don’t think it could be much. According to my phone I’ve averaged about 7,000 steps per day the entire time, while gaining the weight and then while losing it.
The self-experiment can be broken into three main phases: the high-potassium brine phase, the Potatoes + Dairy phase, and a short run-out phase at the end.
I had already lost some weight on the potato diet in the past, so from the perspective of pure science, starting with the potato diet didn’t seem very interesting. Instead, I figured I would investigate the hypothesis that high doses of potassium are part of the reason the potato diet causes weight loss.
For the first 147 days of the experiment, I tried different high-potassium brines, and lost about 12 lbs.
All brines started with a base of two 591 ml blue Gatorades, mixed in a liter bottle with whatever dry electrolytes or other ingredients I was trying. Potassium was always added as KCl in the form of Nu-Salt.
I tried a wide variety of different brine mixtures, using different amounts of KCl as well as NaCl, sodium bicarbonate (baking soda), magnesium malate, iodine (as Lugol’s 2% solution), and glycine powder. But I don’t think these mixtures are worth reporting individually, because I wasn’t able to seriously distinguish between them. Regardless of the mix, I mostly kept losing weight at a very slow pace.
My impression is that magnesium is important, and that brines with added sodium work better than brines without, but I’m the first to admit that the data isn’t strong enough to back this intuition up. The most I can say is that I seemed to lose weight in kind of a sine-wave pattern, which you can see on the graph. These ups and downs roughly lined up with the 14-day cycles where I tried different brine recipes (i.e. I tried most recipes for 2 weeks), but I might have imagined a pattern where in reality there were just natural fluctuations.
While I originally hoped to get around 10,000 mg a day of potassium from my brine, like Krinn did, this wasn’t possible. I found doses above 6,600 mg/day K hard to drink, so I settled at that dosage, reasoning that Krinn lost weight even at lower doses.
In general, the brines made me feel weird. I sometimes became anxious, sometimes fatigued, sometimes got headaches, and sometimes it did weird things to my sense of smell. I did sometimes feel very energetic, and sometimes it seriously reduced my appetite. Some days I ate almost nothing and had almost no appetite. But even with a clear reduction in my appetite, even when I was eating very little, I didn’t lose much weight. (This itself was kind of striking.)
In terms of results, 12 lbs isn’t nothing. But over 147 days, it’s only about 0.08 lbs lost per day. That’s not very much.
I take this as evidence in favor of the hypothesis that high doses of potassium are part of why the potato diet causes weight loss. Even on only 6,600 mg/day K, I experienced many of the effects of the potato diet (reduced appetite, weird anxiety) and I did lose some weight, though not much.
But I also think my results suggest that potassium may not be enough, and that the “potato weight loss effect” really comes from something like high doses of potassium plus something else in potatoes / with potatoes—maybe high doses of magnesium, maybe sufficient sodium to balance the potassium, etc.
The brine seemed to work, but my rate of weight loss was really slow. It seemed like it was time to try the potato diet. In addition to hopefully losing more weight, I saw two benefits.
First, I could compare the effect of the brine directly to the effect of the potato diet, to see if I was already losing weight as fast as I could, or if there was something missing from the formula.
Second, I could test out the success of Potatoes + Dairy. The original potato diet was very strict, but by this point you had already reported a few case studies where people had lost a lot of weight on versions of the potato diet where they also ate various kinds of dairy.
My version of Potatoes + Dairy was decadent. Every meal was potatoes, but I always added as much butter, cheese, and sour cream as I wanted, which was usually a lot. For a while I made a lot of scalloped potatoes, but eventually I got lazy and from that point on I mostly ate baked potatoes or turned old baked potatoes into homefries. I didn’t get tired of this because butter is great.
When I didn’t have time to prepare potatoes, I would have cheese, milk, or ice cream as a snack. Yes, I ate as much ice cream as I wanted, and still lost weight (which is in line with the literature).
In case anyone wants to replicate my approach, my mainstays were:
Despite this decadence, I lost about 40 lbs more over 187 days.
Looking closer, the weight loss really happened over two spans, one before the 2024 December holidays, and one after. I first lost about 16 lbs over 75 days, gained about 8 of that back during late December and January, then lost about 28 lbs over the next 86 days. At the point of greatest descent (early March 2025), I lost 10 lbs in two weeks.
I wasn’t very strict and I did cheat pretty often. My notes mention times and places that I had pizza, candy, or sometimes burritos. Sometimes I had cheat meals where I would go out to lunch or get hot pot with friends. Sometimes I went on dates, where I ate normal food. This mostly didn’t make a difference as long as I also kept up with the potatoes.
You might think that potatoes are a neutral food, and they just help you survive while your body returns to normal, or something. But my sense is that potatoes actively cause the weight loss. On days where I didn’t prepare potatoes, and mostly just snacked on ice cream and cheese, I didn’t seem to gain much weight back, but I didn’t lose it, either.
This leads to another counterintuitive recommendation: the potato diet can really reduce your appetite, sometimes to the point where you don’t want to eat. But I think that you actually lose more weight on days where you eat potatoes than on days where you don’t eat at all. So if your goal is to lose weight, don’t assume that not eating is a good strategy—eat your taters.
I’m pretty confident that the potato diet was causing the weight loss, in part because I started losing weight right when I switched from brine to potatoes. Also, when I cheated for more than just a meal or two, it was obvious on the graph. Halloween, Thanksgiving week, and the December Holidays stand out in particular. Here’s version of the graph with those days singled out:
My holiday weight re-gain continued well into January because I was travelling and helping to organize some professional conferences, and I wasn’t able to keep up with the potatoes very well. As soon as I got back on potatoes around Jan 20, my weight started dropping again, this time faster than before.
I was pretty surprised when I blew past not only 220 lbs, but 210 lbs. I had thought that 220-210 might be the healthy range for me, and expected the diet to stall out there. But instead I blew past those milestones. Turns out that 220 lbs is at least 20 lbs overweight for me. I had no idea, because I felt pretty healthy at 220, but I guess I had forgotten what it was like to be a normal weight.
I first dropped below 200 lbs on March 20, 2025. Soon after that, my weight started to plateau, never falling much below 200 lbs but showing no signs of increasing.
I also noticed that I suddently started craving foods that weren’t potatoes, something that I hadn’t experienced on the previous 170 days. First I started craving fruit, and the next day, I started seriously craving Mexican food. Soon I was craving broccoli and chocolate.
This made me think that I might have reached a plateau, possibly my “natural” weight. According to BMI I am still “overweight” at < 200 lbs, and I am definitely not “lean”. But I do feel trim, and the girl I’ve been dating keeps putting her hands on my chest and talking about how good I look, so I’ll take this as some evidence that “just under 200 lbs” is a reasonable weight for me.
Because I already seemed to have hit a plateau, I decided to spend the last 31 days on a run-out period to see what would happen as I eased off the diet. During this time I still ate potatoes pretty often, but I started bringing in other foods, and I went whole days without eating any potatoes at all. Somewhat surprisingly, I didn’t gain back the weight as I relaxed the diet.
I do kind of wonder if my weight would have fallen even further if I had remained on Potatoes + Dairy, but the fact that I was developing cravings for other food suggests to me that I had encountered a real state change. It might have been possible to force my weight lower, but the magic of the potato diet is that the weight loss happens without any force. If you start forcing things, you’re back in the territory of restriction diets.
I officially ended the experiment on May 12, 2025, 365 days after I started, weighing 198.8 lbs. This was down from an original high of 247.6 lbs, and my all-time low was 194.4 lbs on April 22nd.
I’ll probably keep eating a diet high in potatoes, since even after several months, I still love them very much (and you wouldn’t believe how much I’ve saved in groceries). But I seem to have reached a plateau and a healthy weight, and also, while potatoes are powerful, they come at a terrible cost (mostly joking but read on).
When you lose a lot of weight very quickly, you often lose some hair. I’d never heard of this before but apparently it’s common knowledge among women. Who knew? It’s called “telogen effluvium” and it definitely happened to me. In early January, after my first period of intense Potato + Dairy weight loss, I noticed my hair was seriously thinning on top and in the back.
The good news is that hair lost in this way usually grows back on its own, though it can take a couple of months. That seems to be happening for me too. My hair is clearly thicker now than it was in January. And it’s pretty weird: looking at my scalp, I can see short hairs and even some very short hairs mixed in among the long ones. While my head hasn’t returned to normal yet, the hair is clearly growing back.
So in the end this doesn’t seem to be a serious concern. And it’s not specific to the potato diet, this just happens when you lose weight really fast. Even so, anyone who wants to copy my results should be aware that this might happen, but also that it’s usually temporary.
Some people get really intense negative feelings of fear or anxiety while on the potato diet. This also happened to me.
I’m glad I read Birb’s account of her experience with the potato diet before trying it for myself, because it really prepared me for my own experience. Here’s what she said:
To anyone who wants to do this diet, or is considering it after the benefits I described above: I encourage you to do it, but please be extra cautious that your mental state might be altered and that you are not necessarily in your right mind. The feelings you experience during this diet may not be how you actually feel.
Like I said above, potato diet is fucking weird. I mention this and the above because towards the end of the third week, I found myself crying every day. I was having actual meltdowns… five days in a row.
I am not talking “oh I am so sad, let a single tear roll down my cheek while I stare out of a window on a rainy day” levels of gloom and general depression. I am talking “at one point I couldn’t fold some of my laundry in a way that was acceptable to me, and this made me think I should kill myself, so I started crying”.
Is this a really dark to drop in the middle of a sort of lighthearted post about potato diet? Yes. I am sorry if you are uncomfortable reading it. Personally, I think I have a responsibility to talk about it, because the mentally weird aspect of this diet cannot be stressed enough.
My experience was somewhat different from Birb’s, manifesting more as a sense of overwhelming dread or doom than as a feeling of depression. And unlike Birb, I didn’t start to seriously feel this way until several months into the diet. But I definitely recognize her description.
As far as I could tell, these feelings were somewhat related to how quickly I was losing weight, though maybe not in the way you expect. The faster I was losing weight, the more of an overwhelming sense of doom I felt. Hooray. That said, it wasn’t a very strong relationship. I still felt the doom during times when I was cheating on the diet, and even when I was losing a lot of weight, I sometimes felt ok.
I suspect that these feelings may have something to do with how the body uses epinephrine and norepinephrine to release energy from adipose tissue, which would explain why you feel so crazy anxious and such intense dread when actively losing the most weight, but I’m not a doctor
.
The feelings might also be the result of a vitamin or mineral deficiency. We know that the potato diet is deficient in Vitamin A, and while I wasn’t rigorous about testing this, I found that eating some sweet potatoes (high in vitamin A) often made me feel better. I also found during the run-out period that eating mushrooms (selenium?), broccoli, and spinach (iron?) maybe helped as well. So if you’re having a bad emotional time on the potato diet, think about trying sweet potatoes or one of these other foods.
It’s interesting to me that these feelings of doom got stronger the further along I got in my weight loss. Maybe this is just because I was losing weight faster over time. But another (kind of crazy) possibility is that something is stored in our fat reserves and as I dug deeper into them, I released more of it. Or in general that something is flushed out from somewhere? I don’t know if I believe this but I wanted to mention it.
That’s just my speculation. It could also have been ordinary anxiety from other causes that happened to line up with the weight loss. I’ve got some personal things going on in my life right now, maybe the anxiety is coming from those. Plus, a few friends have recently had similar feelings of dread, and they’re not losing extreme amounts of weight on a highly unusual diet.
My results make me very confident that Potatoes + Dairy works. The potato diet makes you lose weight, and that still works even if you add dairy, including butter and ice cream, no matter if you’re eating as much of it as you want.
While my data can’t speak to how well Potatoes + Dairy will work for anyone else, I hope this ends the idea that the potato diet works because it’s unpalatable. I lost 50 lbs and every meal was delicious. I also hope this finishes the idea that the potato diet works because it’s a “mono diet”. You can’t reasonably call something a mono diet when it includes potatoes, sour cream, and ice cream with tiny peanut butter cups.
I also think this is some evidence for the potassium hypothesis. I lost weight when I was taking high doses of potassium, though not nearly as much as on the potato diet. Maybe this was because I was taking too small of a dose, and a higher dose would have caused a similar amount of weight loss as what I eventually saw on the potato diet.
But I suspect this is because the potato effect doesn’t come from potassium alone, but from an interaction between potassium and something else, possibly other electrolytes like sodium and magnesium.
If you could find the right mixture, maybe you could reproduce the potato effect in a brine. But if so, I wasn’t able to find it. For now, the state of the art is Potatoes + Dairy.
2025-05-08 23:11:00
[PROLOGUE – EVERYBODY WANTS A ROCK]
[PART I – THERMOSTAT]
[PART II – MOTIVATION]
[PART III – PERSONALITY AND INDIVIDUAL DIFFERENCES]
[PART IV – LEARNING]
[PART V – DEPRESSION AND OTHER DIAGNOSES]
[PART VI – CONFLICT AND OSCILLATION]
[PART VII – NO REALLY, SERIOUSLY, WHAT IS GOING ON?]
[INTERLUDE – I LOVE YOU FOR PSYCHOLOGICAL REASONS]
[PART VIII – ARTIFICIAL INTELLIGENCE]
[PART IX – ANIMAL WELFARE]
[PART X – DYNAMIC METHODS]
[PART XI – OTHER METHODS]
“Alright, gang, let’s split up and search for clues.”
— Fred Jones, Scooby-Doo
This has been our proposal for a new paradigm for psychology.
If the proposal is more or less right, then this is the start of a scientific revolution. And while we can’t make any guarantees, it’s always good to plan for success. So in case these ideas do turn out successful, then: welcome to psychology’s first paradigm, let’s discuss what we do from here.
In looking for a paradigm, we’re looking for new ways to describe the mysteries that pop up on the regular. When a good description arrives, some of those mysteries will become puzzles, problems that look like they can be solved with the tools at hand, that look like they will have a clear solution, the kind of solution we’ll recognize when we see it. Because a shared paradigm gives us a shared commitment to the same rules, standards, and assumptions, it can let us move very quickly.
All that is to say is that if this paradigm has any promise, then there should be a lot of normal science, a lot of puzzle-solving to do. A new paradigm is like an empty expert-level sudoku: there’s a kind of internal logic, but also a lot of tricky blanks that need filling in. So, we need your help. Here are some things you can do.
First, experimentalists can help us develop methods for figuring out how many cybernetic drives people have, what each drive controls, and different parameters of how they work. In the last two sections we did our best to speculate about what these methods might look like, but there are probably a lot of good ideas we missed.
Then, we need people to actually go out and use these methods. The first task is probably to discover all of the different drives that exist in human psychology, to fill out the “periodic table” of motivation as completely as we can. Finding all of the different drives will generate many new mysteries, which will lead to more lines of research and more discoveries.
We will also want to study other animals. There are a few reasons to study animals in addition to humans. First of all, most animals don’t have the complex social drives that humans do. The less social an animal is, the easier it will be to study its non-social drives in isolation. Second, it’s possible to have more control over an animal’s environment. We can raise an animal so that it never encounters certain things, or only encounters some things together. Finally, we can use somewhat more invasive techniques with animals than we can with humans.
Computational models will be especially important for developing a better understanding of depression, anxiety, and other mental illnesses. With a model, we can test different changes to the design and parameters, and see which kinds of models and what parameter values lead to the behaviors and tendencies that we recognize as depression. This will ultimately help us determine how many different types of depression there are, come to an understanding of their etiology, and in time develop interventions and treatments.
Computational models should provide similar insight into tendencies like addiction and self-harm. The first step is to show that models of this kind can give rise to behavior that looks like addiction. Then, we see what other predictions the model makes about addictive behavior, and about behavior in general, and we test those predictions with studies and experiments.
If we discover more than one computational model that leads to addictive behavior, we can compare the different models to real-world cases of addiction, and see which is more accurate. Once we have models that provide a reasonably good fit, we can use them to develop new approaches for treatment and prevention.
Those of you who tend more towards biology or neuroscience can help figure out exactly how these concepts are implemented in our biology. Understanding the computational side of how the mind works is important, but the possible interventions we can take (like treating depression) will be limited if we don’t know how each part of the computation is carried out in an organism.
For example: every governor tracks and controls some kind of signal. The fear governor tracks something like “danger”. This is a complicated neurological construct that probably doesn’t correspond to some specific part of biology. But other governors probably track biological signals that may be even as simple as the concentrations of specific minerals or hormones in the bloodstream.
For example, the hormone leptin seems to be involved in regulating hunger. Does one of the hunger governors act to control leptin levels in our blood? Or is leptin involved in some other part of the hunger-control process? What do the hunger, thirst, sleep, and other basic governors control, and what are their set points?
Biologists may be able to answer some of these questions. Some of these questions may even have already been answered in neuroscience, biology, or medicine, in which case the work will be in bundling them together under this new perspective.
Running studies and inventing better methods sounds very scientific and important, but we suspect the most important contributions might actually come from graphic design.
The first “affinity table” was developed in 1718 by Étienne François Geoffroy. Substances are identified by their alchemical symbol and grouped by “affinity”.
At the head of each column is a substance, and below it are listed all the substances that are known to combine with it. “The idea that some substances could unite more easily than others was not new,” reports French Wikipedia, “but the credit for bringing together all the available information into a large general table, later called the affinity table, goes to Geoffroy.”
Here is a later affinity table with one additional column, the Tabula Affinitatum, commissioned around 1766 for the apothecary’s shop of the Grand Duke of Florence, now to be found in the Museo Galileo:
These old attempts at classification are charming, and it’s tempting to blame this on the fact that they didn’t understand that elements fall into some fairly distinct categories. But chemical tables remained lacking even after the discovery of the periodic law.
Russian chemist Dmitri Mendeleev is often credited with inventing the periodic table, but he did not immediately give us the periodic table as we know it today. His original 1869 table looked like this:
And his update in 1871 still looked like this:
It wasn’t until 1905 that we got something resembling the modern form, the first 32-column table developed by Alfred Werner:
They tried a lot of crazy things on the way to the periodic table we know and love, and not all of these ideas made it. We’ll share just one example here, Otto Theodor Benfey’s spiral periodic table from 1964:
When a new paradigm arrives, the first tools for thinking about it, whether tables, charts, diagrams, metaphors, or anything else, are not going to be very good. Instead we start with something that is both a little confused and a little confusing, but that half-works, and iterate from there.
The first affinity table by Étienne François Geoffroy in 1718 was not very good. It was missing dozens of elements. It contained bizarre entries like “absorbent earth” and “oily principle”. And it was a simple list of reactions, with no underlying theory to speak of.
But it was still good enough for Fourcroy, a later chemist, to write:
No discovery is more brilliant in this era of great works and continued research, none has done more honor to this century of renewed and perfected chemistry, none finally has led to more important results than that which is relative to the determination of affinities between bodies, and to the exposition of the degrees of this force between different natural substances. It is to Geoffroy the elder … that we owe this beautiful idea of the table of chemical ratios or affinities. … We must see in this incorrect and inexact work only an ingenious outline of one of the most beautiful and most useful discoveries which have been made. This luminous idea served as a torch to guide the steps of chemists, and it produced a large number of useful works. … chemists have constantly added to this first work; they have corrected the errors, repaired the omissions, and completed the gaps.
It took about two hundred years, and the efforts of many thousands of chemists, to get us from Geoffroy’s first affinity table to the periodic table we use today. So we should not worry if our first efforts are incomplete, or a little rough around the edges. We should expect this to take some effort, we should be patient.
Better tools do not happen by accident. We do not get them for free — someone has to make them. And if you want, that someone can be you.
That’s all, folks!
Thank you for reading to the end of the series! We hope you enjoyed.
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2025-05-01 23:11:00
[PROLOGUE – EVERYBODY WANTS A ROCK]
[PART I – THERMOSTAT]
[PART II – MOTIVATION]
[PART III – PERSONALITY AND INDIVIDUAL DIFFERENCES]
[PART IV – LEARNING]
[PART V – DEPRESSION AND OTHER DIAGNOSES]
[PART VI – CONFLICT AND OSCILLATION]
[PART VII – NO REALLY, SERIOUSLY, WHAT IS GOING ON?]
[INTERLUDE – I LOVE YOU FOR PSYCHOLOGICAL REASONS]
[PART VIII – ARTIFICIAL INTELLIGENCE]
[PART IX – ANIMAL WELFARE]
[PART X – DYNAMIC METHODS]
There’s a fascinating little paper called Physiological responses to maximal eating in men.
The researchers recruited fourteen men (mean age: 28 years old) and invited them back to the lab to eat “a homogenous mixed-macronutrient meal (pizza)”. The authors note that “this study was open to males and females but no females signed up.”
They invited each man to visit the lab two separate times. On one occasion, the man was asked to eat pizza until “comfortably full”. The other time, he was asked to eat pizza until he “could not eat another bite”.
When asked to eat until “comfortably full”, the men ate an average of about 1500 calories of pizza. But when asked to eat until they “could not eat another bite”, the men ate an average of more than 3000 calories.
The authors view this as a study about nutrition, but we saw it and immediately went, “Aha! Pizza psychology!”
While this isn’t a lot of data — only fourteen men, and they only tried the challenges one time each — it shows some promise as a first step towards a personality measure of hunger and satiety, because it measures both how hungry these boys are, and also how much they can eat before they have to stop.
When asked to aim for “could not eat another bite”, the men could on average eat about twice as much pizza compared to when they were asked to aim for “comfortably full”. But there was quite a lot of variation in this ratio for different men:
All the men ate more when they were asked to eat as much as they could, than when they were asked to eat as much as they liked. But there’s a lot of diversity in the ratio between those two values. When instructed to eat until they “could not eat another bite”, some men ate only a little bit more than they ate ad libitum. But one man ate almost three times as much when he was told to go as hard as he can.
People have some emotions that drive them to eat (collectively known as hunger), and other emotions that drive them to stop eating (collectively known as satiety). While these pizza measurements are very rough, they suggest something about the relationship between these two sets of drives in these men. If nothing else, it’s reassuring to see that for each individual, the “could not eat another bite” number is always higher.
It’s a little early to start using this as a personality measure, but with a little legwork to make it reliable, we might find something interesting. It could be the case, for example, that there are some men with very little daylight between “comfortably full” and “could not eat another bite”, and other men for whom these two occasions are like day and night. That would suggest that some men’s hunger governor(s) are quite strong compared to their satiety governor(s), and other men’s are relatively weak.
The general principle of personality in cybernetic psychology is “some drives are stronger than others”. So for personality, we want to invent methods that can get at the question of how strong different drives are, and how they stack up against each other. Get in loser, we’re making a tier list of the emotions.
We may not be able to look at a drive and say exactly how strong it is, since we don’t yet know how to measure the strength of a drive. We don’t even know the units. When this is eventually discovered, it will probably come from an unexpected place, like how John Dalton’s work in meteorology gave him the idea for the atomic theory.
But we can still get a decent sense of how strong one drive is compared to another drive. This is possible whenever we can take two drives and make them fight.
Some drives are naturally in opposition — this pizza study is a good example. The satiety governor(s) exist specifically to check the hunger governor(s). Hunger was invented to start eating, and satiety was invented to make it stop. So it’s easy to set up a situation where the two of them are in conflict.
Or somewhat easy. We think it’s more accurate to model the pizza study as the interaction between three (groups of) emotions. When asked to eat until “comfortably full”, the hunger governor voted for “eat pizza” until its error was close to zero, then it stopped voting for “eat pizza”, so the man stopped. That condition was simple and mainly involved just the one governor.
The other condition was more complex. When asked to eat until they “could not eat another bite”, the hunger governor first voted for “eat pizza” until its error was close to zero. Then, some kind of “please the researchers” governor(s) kept voting for “eat pizza” to please the researchers.
At some point this started running up against the satiety governor. The satiety governor tracks something like how full you are, so as the man started to get too full, the satiety governor started voting against “eat pizza”. The man kept eating until the vote from the “please the researchers” governor(s) was just as strong as the vote from the satiety governor, at which point the two votes cancel out and the man could not eat another bite.
This reveals the problem. In one sense, hunger and satiety are naturally in opposition. Hunger tries to make you eat enough and satiety tries to make sure you don’t eat enough too much. But in a healthy person, there’s plenty of daylight between the set points of these two drives, and they don’t come into conflict.
Same thing with hot and cold — the drive that tries to keep you warm is in some sense “in opposition” to the drive that tries to keep you from overheating, but they don’t normally fight. If you have a sane and normal mind, you don’t put on 20 sweaters, then overheat, then in a fit of revenge take off all of your clothes and jump in a snowbank, etc. These drives oppose each other along a single axis, but when they are working correctly, they keep the variable they care about in a range that they agree on. Hunger and satiety, and all the paired governors, are more often allies than enemies.
But any two drives can come into conflict when the things they want to do become mutually exclusive, or even just trade off against each other. Even if you can do everything you want, the drives will still need to argue about who gets to go first. Take something you want, anything at all, and put it next to a tiger. Congratulations, fear is now in conflict with that original desire.
Many people experience this conflict almost every morning:
This is actually a more complicated situation, where the governors have formed factions. The pee governor wants to let loose on your bladder. But your hygiene governor votes against wetting the bed. Together they settle on a compromise where you get up and pee in the toilet instead, since this satisfies both of their goals (bladder relief + hygienic).
But the governor that keeps you warm, the sleep governor (who wants to drift back into unconsciousness), and any other governors with an interest in being cozy, strenuously oppose this policy. They want you to stay in your warm, comfy bed. So you are at an impasse until the bladder governor eventually has such a strong error signal — you have to take a leak so bad — that it has the votes to overrule the cozy coalition and motivate you to get up and go to the bathroom.
The point is, the bladder governor, warmth governor, and sleep governor don’t fundamentally have anything to do with each other. They all care about very different things. But when you have to pee in the middle of the night, their interests happen to be opposed. They draw up into factions, and this leads to a power struggle — one so universal that there are memes about it. And as is always the case in politics, a power struggle is a good chance to get a sense of the relative strength of the factions involved.
If you met someone who said they didn’t relate to this — they always get up in the middle of the night to pee without any hesitation or inner struggle — this would suggest that their bladder governor is very strong, or that their warmth and/or sleep governors are unusually weak. Whatever the case, their bladder governor wins such disagreements so quickly that there doesn’t even appear to be a dispute.
In contrast, if your friend confesses that they have such a hard time getting up that they sometimes wet the bed, this suggests that their bladder governor, and probably their hygiene governor, are unusually weak compared to the governors voting for them to stay in bed.
To understand these methods, we have to understand the difference between two kinds of “strength”.
In general when we say that a drive is strong, we mean that it can meet its goals, it can vote for the actions it wants. This is why we can learn something about the relative strength of two drives by letting them fight — we can present the organism with mutually exclusive options (truth or dare?) and see which option it picks. If we have some reasonable idea which drive would pick which option, we know which drive is stronger from which option is picked.
However! Another way a drive can be strong is that it can have a big error signal in that moment. If you are ravenously hungry, you will eat before anything else. If you are in excruciating pain, you will pull your hand off the stove before doing anything else. This kind of urgency tells us that the current error is big, but it doesn’t tell us much about the governor.
A drive does get a stronger vote when its variable is further off target. But it’s also true that for a given person, some drives seem stronger in all situations.
The normal sense of strength gets at the fact that a governor can be stronger or weaker for a given error. Some people can go to sleep hungry without any problem. For other people, even the slightest hint of appetite will keep them awake. When we talk about someone being aggressive, we mean that they will drop other concerns if they see a chance to dominate someone; if we talk about someone being meek, we mean the opposite.
The current strength of any drive is a function of the size of its current error signal and the overall strength or “weight” of the governor. Unfortunately, we don’t know what that function is. Also, it might be a function of more than just those two things. Uh-oh!
Ideally, what we would do is hold the size of the error constant. If we could make sure that the error on the salt governor is 10 units, and the error on the sweet governor is 10 units, then we could figure out which governor is stronger by seeing which the person would choose first, skittles or olives. This is based on the assumption that the strength of the vote for each option is a combination of the size of the errors and the strength of the governor itself. Since in this hypothetical we know that the strength of the errors is exactly the same, the difference in choice should be entirely the result of the difference in the strength of the governors.
Unfortunately we don’t know how to do that either. We don’t know how to measure the errors directly, let alone how to hold the size of the errors constant.
But we can use techniques that should make the size of some error approximately constant, and base our research on that. The closer the approximation, the better.
The important insight here is that even when we can’t make measurements in absolute terms, we can often make ordinal comparisons. “How strong is this drive” is an impossible question to answer until we know more about how strength is implemented mechanically, but we can make very reasonable guesses about which of two drives is stronger, what order their strengths are in, i.e. ordinal measurements.
We can do this two ways: we can compare one of your drives to everyone else’s version of that same drive, or we can compare one of your drives to your other drives.
The first is that we can compare one of a person’s drives to the same drive in other people.
It’s reasonable to ask if your hunger, fear, pain, or shame drive is stronger or weaker than average. To do this, we can look at two or more individuals and ask if the drive is stronger for one of them or for the other.
This will offer a personality measure like: your salt governor is stronger than 98% of people. You a salty boy.
Again, to get a measure of strength, we need to make everyone’s errors approximately constant. One way we can make errors approximately constant is by fully satisfying the drive. So if we identify a drive, like the drive for salt, we can exhaust the drive by letting people eat as much salt or salty food(s) as they want. Now all their errors should be close to zero. Then we can see how long it takes before they go eat something salty again. If someone goes to get salty foods sooner, then other things being equal, this is a sign that their salt governor is unusually strong.
This won’t be perfectly the same, and other things will not be perfectly equal. Some people’s salt error may increase more quickly than others’, like maybe they metabolize salt faster, or something. So after 5 hours without salty foods, some people’s error may be much bigger than others’. But it should be approximately equal, and certainly we would learn something important if we saw one guy who couldn’t go 10 minutes without eating something salty, and someone else who literally never seemed to seek it out.
When we say things like, “Johnnie is a very social person. If he has to spend even 30 minutes by himself he gets very lonely, so he’s always out and spending time with people. But Suzie will go weeks or even months without seeing anyone,” this is a casual version of the same reasoning, and we think it’s justified. It may not get exactly at the true nature of personality, but it’s a start.
When we figure out what the targets are for some governors, we’ll be able to do one better. For example, let’s imagine that we find out that thirst is the error for a governor that controls blood osmolality, and through careful experimentation, we find out that almost everyone’s target for blood osmolality is 280 mOsm/kg. Given the opportunity, behavior drives blood osmolality to 280 mOsm/kg and then stops.
If we measure people’s blood osmolality, we can dehydrate them to the point where their blood osmolality is precisely 275 mOsm/kg. We know that this will be an error of 5 mOsm/kg, because that’s 5 units less than the target. Then we would know almost exactly what their error is, and we could estimate the relative strength of their thirst governor by measuring how hard they fight to get a drink of water.
On that note, it’s possible that a better measure than time would be effort. For example, you could take a bunch of rats and figure out the ideal cage temperature for each of them. Separately, you teach them that pushing a lever will raise the temperature of their cage by a small amount each time they press it.
Then, you set the cage temperature 5 degrees colder than they prefer. This should give them all errors of similar magnitude — they are all about 5 degrees colder than they’d like. Then you give them the same lever they were trained on. But this time, it’s disconnected. You count how many times they press the lever before they give up. This will presumably give you a rough measure of how much each rat is bothered by being 5 degrees below target, and so presumably an estimate of the strength of that governor. If nothing else, you should observe some kind of individual difference.
The second approach is to ask how your drives compare to each other, basically a ranking. We can look at a single person and ask, in this person, is drive A stronger than drive B?
The main way to do this is to give the person a forced choice between two options, one choice that satisfies governor A, and the other that satisfies governor B. This doesn’t have to be cruel — you can let them take both options, you just have to just make them choose which they want to do first.
This would offer a personality measure like: you are more driven by cleanliness than by loneliness, which is why you keep blowing off all your friends to stay in and scrub your toilet.
There are some drives that make us want to be comfortable and other drives that make us want to be fashionable; there are at least some tradeoffs between comfort and fashion; if you reflect on each of the people in your life, it’s likely that you already know which coalition of drives tends to be stronger in each person.
Every time you see someone skip work to play videogames, refuse to shower even when it ruins all their friendships, blow up their life to have an affair with the 23-year-old at the office, or stay up late memorizing digits of pi, you are making this kind of personality judgment implicitly. People have all kinds of different drives, and you can learn a lot about which ones are strongest by seeing which drives are totally neglected, and which drives lead people to blithely sacrifice all other concerns, as though they’re blind to the consequences.
The Bene Gesserit, a sect of eugenicist, utopian nuns from the Dune universe, use a simplified version of this method in their famous human awareness test, better known as the gom jabbar. Candidates are subjected to extreme pain and ordered not to pull away, at penalty of taking a poisoned needle in the neck. In his success, Paul demonstrates that some kind of self-control governor is much stronger than his pain governor, even when his pain error is turned way up.
But no shade to the Bene Gesserit, this is not a very precise measure. By turning the pain governor’s error extremely high, they can show that a candidate has exceptional self-control. But this doesn’t let them see if self-control is in general stronger than pain, because the error gets so huge. To compare the strength of governors, you ideally want the error signals to be as similar as possible.
As before, the best way to get at strength is to take two drives, try to make their errors as similar as possible, and then see which drive gets priority. Other things being equal, that drive must be stronger.
When we were trying to compare personality between people, this was relatively easy. If nothing else, we were at least looking at the same error. We can’t get an exact measure of the error, but we could at least say, both of these people have gone 10 hours without eating, or 20 hours without sleep, or are ten degrees hotter than they find comfortable. These are the same kinds of things and they are equal for both people.
But to compare two governors within a single person, we are comparing two different errors, and we have no idea what the units are. So it may be hard to demonstrate differences between the strength of the governors when those differences are small. If one error is ten times stronger than the other, then we assume that the governor behind that error will win nearly all competitions between the two of them. If one error is 1.05 times stronger than the other, that governor has an edge, but will often get sidelined when there are other forces at play.
But like the common-sense examples above, it should be possible to make some comparisons, especially when differences are clear. For example, if we deprive a person of both sleep and food for 48 hours (with their consent of course), then offer them a forced choice between food and sleep, and they take the food, that suggests that their drive to eat may be stronger than their drive to sleep. This is especially true if we see that other people in the same situation take the option to sleep instead.
If we deprive the person of sleep for 48 hours and food for only 4 hours, and they still choose the food over sleep, that is even better evidence that their drive to eat is stronger than their drive to sleep, probably a lot stronger.
While these methods are designed to discover something inside an individual person, they might also shed some light on personality differences between people. For example, we might find that in most people, the sugar governor is stronger than the salt governor. But maybe for you, your salt governor is much stronger than your sugar governor. That tells us something about your personality in isolation (that one drive is stronger than another), and also tells us something about your personality compared to other people (you have an uncommon ordering of drives).
The pizza study is interesting because it kind of combines these techniques.
Each person was compared on two tasks — “comfortably full” and “could not eat another bite”, which gives us a very rough sense of how strong their hunger and satiety governors are. If you ate 10 slices to get to “comfortably full” and only 12 slices to get to “could not eat another bite”, your satiety governor is probably pretty strong, since it kicks in not long after you ate as much as you need. (There could be other interpretations, but you get the gist.)
In addition, each person can be compared to all the other people. Some men could eat only a little more when they were asked to get to “could not eat another bite”. But one man ate almost three times as much as his “comfortably full”. This man’s satiety governor is probably weaker than average. There are certainly other factors involved, but it still took a long time before that governor forced him to stop eating, suggesting it is weak.
A final note on strength. The strength of a governor is probably somewhat innate. But it may also be somewhat the result of experience. If someone is more motivated by safety than by other drives, some of that may be genetic, but some of that may be learned. It would not be ridiculous to think that your mind might be able to tune things so that if you have been very unsafe in your life, you will pay more attention to safety in the future.
Even the part that’s genetic (or otherwise innate) still has to be implemented in some specific way. When one of your governors is unusually strong, does that governor have a stronger connection to the selector? Does it have the same connection as usual, but it can shout louder? Does it shout as loud as normal, but it can shout twice as often? We don’t know the details yet, but keep in mind that all of this will be implemented in biology and will include all kinds of gritty details.
People can differ in more ways than just having some of their drives be stronger than others. For example, some people are more active than other people in general, more active for every kind of drive. They do more things every single day.
Some people seem to get more happiness from the same level of accomplishment. For some people, cooking dinner is a celebration. For others, routine is routine.
Some people seem more anxious by default. Even a small thing will make them nervous.
These seem like they might be other dimensions on which people can differ, and they don’t seem like they are linked to specific governors.
Studying the strength of the governors is nice because the governors are all built on basically the same blueprint, so the logic needed to puzzle out one of them should mostly work to puzzle out any of the others. The methods used to study one governor should work to study all of them, only minor tweaks required. If you find techniques to measure the strength of one governor, you should be able to use those techniques to measure the strength of any governor.
But other ways in which people differ seem more idiosyncratic. They are probably the result of different parameters that tune features that are more global, each of which interacts with the whole system in a unique and different way. So we will probably need to invent new methods for each of them.
That means we can’t yet write a section on the different methods that will be useful. These methods still need to be invented. And we might only get to these methods once we have learned most of what there is to know about the differences in strength between the governors, and have to track down the remaining unexplained differences between people. But we can give a few examples to illustrate what some of these questions and methods might look like.
Every governor has to have some way of learning which behaviors increase/decrease their errors. We don’t know exactly how this learning works yet, but we can point to a few questions that we think will be fruitful.
For example, is learning “both ways”?
The hot governor (keeps you from getting too hot) and the cold governor (keeps you from getting too cold) both care about the same variable, body temperature. Certainly if you are too cold and you turn on a gas fireplace, your cold governor will notice that this corrects its error and will learn that turning on the gas fireplace is a good option. So when you get too cold in the future, that governor will sometimes vote for “turn on the gas fireplace”.
But what if you are too hot and you turn on the gas fireplace? Well, your hot governor will notice that this increases its error, and will learn that this is a bad option, which it will vote against if you’re in danger of getting too hot.
What does your cold governor learn in this situation? Maybe it learns the same thing your hot governor does — that the gas fireplace increases temperature. The hot governor thinks that’s a bad outcome, but the cold governor thinks it’s a good outcome. If so, then next time you are cold, the cold governor might vote for you to turn on the gas fireplace.
But maybe a governor only learns when its error is changed. After all, each governor only really cares about the error it’s trying to send to zero. And if that error isn’t changed, maybe the governor doesn’t pay attention. If the error is very small, maybe that governor more or less turns off, and stops paying attention, to conserve energy. Then it might not do any learning at all.
If this were the case, the cold governor shouldn’t learn from any actions you take when you’re too hot, even when these actions influence your body temperature. And the hot governor shouldn’t learn from anything you do when you’re too cold, same deal.
You could test this by putting a mouse in a cage that is uncomfortably hot, and that contains a number of switches. Each switch will either temporarily increase or temporarily decrease the temperature of the cage. With this setup, the mouse should quickly learn which switches to trip (makes the cage cooler) and which switches to avoid (makes the cage even more uncomfortably hot).
Once the mouse has completely learned the switches, then you make the cage uncomfortably cold instead, and see what happens. If the cold governor has also been learning, then the mouse should simply invert its choice of switches, and will be just as good at regulating the cage temperature as before.
But if the cold governor wasn’t paying close attention to the hot governor’s mistakes, then the mouse will have to do some learning to catch up. If the cold governor wasn’t learning from the hot governor’s mistakes at all, then the mouse will be back at square one, and might even have to re-learn all the switches through trial and error.
We definitely might expect the former outcome, but you have to admit that the latter outcome would be pretty interesting.
Or consider the possibility that happiness might drive learning.
This would explain why happiness exists in the first place. It’s not just pleasant, it’s a signal to flag successful behavior and make sure that it’s recorded. When something makes you happy, that signals some system to record the link between the recent action and the error correction.
This would also explain why it often feels like we are motivated by happiness as a reward. We aren’t actually motivated by happiness itself, but when something has made us happy, we tend to do it more often in the future.
Previously we said that happiness is equal to the change in an error. In short, when you correct one of your errors, that creates a proportional amount of happiness. This happiness sticks around for a while but slowly decays over time.
That’s a fine model as a starting point, but it’s very simple. Here’s a slightly more complicated model of happiness, which may be more accurate than the model we suggested earlier. Maybe happiness is equal to the reduction in error times the total sum of all errors, like so:
happiness = delta_error * sum_errorsIf happiness is just the result of the correction of an error, then you get the same amount of happiness from correcting that error in any circumstance. But that seems a little naïve. A drink of water in the morning after a night at a five-star hotel is an accomplishment, but the same drink of water drawn while hungry and in pain, lost in the wilderness, is a much greater feat. Remembering the strategy that led to that success might be more important.
If you multiply the correction by the total amount of error, then correcting an error when you are in a rough situation overall leads to a much greater reward, which would encourage the governors to put a greater weight on successes that are pulled off in difficult situations. If you correct an error when all your other errors are near zero, you will get some happiness. But if you are more out of alignment generally — more tired, cold, lonely, or whatever — you get more happiness from the same correction.
This might explain fetishes. Why do so many sexual fetishes include things that cause fear, pain, disgust, or embarrassment? Surely the fear, pain, disgust, and embarrassment governors would vote against these things.
We have to assume that the horny governor is voting for these things. The question is, why would it vote for anything more than getting your rocks off? Why would an orgasm plus embarrassment be in any way superior to an orgasm in isolation?
If learning is based on happiness rather than raw reduction in error, then governors will learn to vote for things that have caused past happiness.
And if happiness is a function of total error, not just correction in the error they care about, governors will sometimes vote for things that increase the total error just before their own error is corrected.
The point is, if happiness is a function of total error, governors will actually prefer to reduce their errors in a state of greater disequilibrium. This doesn’t decrease their error any more than in a state of general calm, but it does lead to more happiness, greater learning, and so they learn to perform that action more often. And in some cases they will actually vote to increase the errors of other governors, when they can get the votes.
The horny governor only cares about you having an orgasm. But since it learns from happiness, not from the raw correction in its error, it has learned to vote for you to become afraid and embarrassed just before the moment of climax, because that increases your total error, which increases happiness. And since the horny governor has the votes, it overrules the governors who would vote against those things.
We don’t know how to quantify any of the factors involved, so we can’t test precise models. There are probably constants in these equations, but we can’t figure those out either, at least not yet.
But we can still make reasonable tests of general classes of models. We can make very decent guesses about whether or not something is a function of something else, and we can probably figure out if these relationships are sums or products, whether relationships are linear or exponential, and so on. For example:
happiness = delta_errorThis is the original model we proposed, and it’s the most simple. In this case, happiness is caused when an organism corrects any error, and the amount of happiness produced is a direct function of how big of an error was corrected. Eating a cheeseburger makes you happy because, assuming you are hungry, it corrects that error signal. The cheeseburger error.
Not shown in that equation is the kind of relationship. Maybe it’s linear, but maybe it’s exponential. Does eating two cheeseburgers cause more than twice as much happiness as eating one?
This very simple model has the virtue of being very simple. And it seems like it lines up with the basic facts — eating, sleeping, drinking, and fucking do tend to make us happy, especially if we are quite hungry, tired, thirsty, or horny.
But we should also think about more complex models and see if any of them are any better. For example:
happiness = delta_error * product_errorsIn this case, the correction in an error is multiplied not by the sum, but by the product of all other errors. So eating a cheeseburger while tired and lonely will be much more pleasurable than eating a cheeseburger while merely tired or merely lonely.
This seems pretty unlikely just from first glance. If happiness were dependent on the product of your other errors, that seems like it would be pretty noticeable, because the difference between correcting an error while largely satisfied and largely unsatisfied would be huge and thus obvious. But this is also something that you could test empirically and maybe there could be some kind of truth to it.
Is this a better model? Not entirely clear, but it certainly makes predictions that can be compared to parts of life we’re familiar with, and it can be tested empirically. That’s a pretty good start.
Or another example:
happiness = delta_error / sum_errorsInstead of multiplying the correction to produce happiness, this time we tried dividing it. In this case, happiness is smaller when the total amount of error is bigger. So correcting the same error leads to less happiness if you’re more out of alignment.
This one seems right out. The joy we get from a cup of hot chocolate is greater when we are lonely, not less. Living in extremis seems like it should only magnify the satisfaction of our experiences. It’s possible that this doesn’t stand up to closer inspection, but people certainly find the idea intuitive:
Finally, one more example. You remember this equation from the learning and memory section above:
Another model of happiness is that happiness is proportional to the TD error in the equation above, or the equivalent in whatever system our brain really uses. The TD error is the difference between the current and projected outcome of the action and the expected outcome of the action. So in this model, we get happiness when something corrects an error by more than the governor expects.
Having an especially great sandwich for the first time feels great. This is because you didn’t know how good it would be. But having the same sandwich for the 100th time isn’t as good, even if it corrects the same amount of error. This is because you anticipated it would be that good, so there’s no TD error. In fact, if the sandwich hits the spot less than usual, you’ll be disappointed, even if it’s still pretty good.
In this model, you’d expect that doing the same enjoyable stuff over and over wouldn’t keep you happy for very long. You’d have to mix it up and try new things that correct your errors.
This model does seem to capture something important. But that said, in real life correcting a big enough error usually creates some happiness. So happiness doesn’t seem like it could be entirely based on how unexpected the correction is. Some amount of happiness seems to come from any correction. But it does seem like more unexpected corrections usually make us more happy.
So this is an example of how we can test general models, even before we can make precise measurements. We can think about classes of models, bring them to their limits, ask how the implications of these models compare to other things we already know about life and happiness, things we experience every day.
Just thinking of these questions mechanically, thinking of them as models, prompts us to ask questions like — What is the minimum amount of happiness? Can happiness only go down to zero, or can there be negative happiness? Is there a maximum amount of happiness? Even if a maximum wasn’t designed intentionally, surely there is some kind of limit to the value the hardware can represent? Can you get happiness overflow errors? What is the quantum of happiness? What are the units? — questions that psychologists wouldn’t normally ask.
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