Altruism, at a large scale, often hinges on a chain of assumptions/requirements, such as:

A & B & C & D & E

One broken link in the chain means it looks like you’re doing good but you’re not really doing it.

For example, to help the world by delivering medicine, the chain might look like this:

The medicine reliably cures the disease

& the side effects are not worse than being ill

& many people are ill with the disease in that area

& you can deliver the medication to them cheaply

& they take the medicine

& they don’t already have access to an effective medication

A deep causal understanding of the problem you’re trying to solve, and a frequent refocusing on the value you’re trying to produce (not getting lost in intermediate goals), is really important when it comes to actually producing a broad positive impact.

This piece was first written on September 11, 2020, and first appeared on my website on June 24, 2026.

1. Parkinson’s Law: Work expands so as to fill the time available for its completion.
2. Hofstadter’s Law: It always takes longer than you expect, even when you take into account Hofstadter’s Law.
3. Gates’ Law: Most people overestimate what they can do in one year and underestimate what they can do in ten years.
4. Goodhart’s Law: When a measure becomes a target, it ceases to be a good measure.
5. Hanlon’s Razor: Never attribute to malice that which is adequately explained by stupidity (or, don’t invoke conspiracy when ignorance and incompetence will suffice, as conspiracy implies intelligence).
6. Acton’s Dictum: Power tends to corrupt, and absolute power corrupts absolutely.
7. Amara’s Law: We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.
8. Benford’s Law: In a diverse collection of unrelated statistics, a given statistic has roughly a 30% chance of starting with the digit 1.
9. Betteridge’s Law: Any headline which ends in a question mark can be answered by the word ‘no’.
10. Brooks’ Law: Adding manpower to a late software project makes it later.
11. Chesterton’s Fence: Reforms should not be made until the reasoning behind the existing state of affairs is understood.
12. Claasen’s Law: Usefulness = log(technology).
13. Clarke’s First Law: When a distinguished elderly scientist states that something is possible, they are almost certainly right, but when they state something is impossible, they are probably wrong.
14. Cromwell’s Rule: Nothing but logical impossibilities have a prior probability of 0 or 1.
15. Cunningham’s Law: The best way to get the right answer on the Internet is not to ask a question, it’s to post the wrong answer.
16. Doctorow’s Law: When someone puts a lock on a thing you own, against your wishes, and doesn’t give you the key, they’re not doing it for your benefit.
17. Dunbar’s Number: Most people can’t maintain stable social relationships with more than 150 people.
18. Eroom’s Law: Drug discovery is becoming slower and more expensive over time, despite improvements in technology.
19. Gell-Mann Amnesia Effect: You’ll believe articles outside your area of expertise, even after acknowledging that neighboring articles in your area of expertise are completely wrong.
20. Gibson’s Law (or the Expert Witness Law): For each PhD (to use as an expert witness for one side) there’s an equal and opposite PhD.
21. Godwin’s Law: As an online discussion grows longer, the probability of a comparison involving Nazis or Hitler approaches one.
22. Morley-Souter’s Law (Rule 34): There is porn of it (no exceptions).
23. Greenspun’s Tenth Rule: Any sufficiently complicated C program contains an ad hoc, informally specified, bug-ridden, slow implementation of half of Common Lisp.
24. Hebb’s Law: Neurons that fire together wire together.
25. Hubble’s Law: Galaxies recede from an observer at a rate proportional to their distance to that observer.
26. Hume’s Guillotine (Is-Ought Problem): Normative statements (about what’s moral/immoral/right/wrong) cannot be deduced exclusively from descriptive statements.
27. Humphrey’s Law: Conscious attention to a task normally performed automatically can impair its performance.
28. Kranzberg’s Law: Technology is neither good nor bad; nor is it neutral.
29. Lamarck’s Principle (or “Use it or Lose it”): Use it or lose it (evolutionarily speaking, but also in the brain).
30. Lewis’s Law: The comments you’ll inevitably find on any article about feminism justify feminism.
31. Littlewood’s Law: Individuals can expect miracles to happen to them, at the rate of about one per month.
32. Maes–Garreau Law: Favorable predictions about future technology will fall at the latest possible date they can come true and still remain in the lifetime of the predictor.
33. Metcalfe’s Law: The value of a system grows as approximately the square of the number of users of the system.
34. Miller’s Law: To understand what another person is saying, you must assume that it is true and try to imagine what it could be true of.
35. Moore’s Law: Computation per dollar grows exponentially (or: number of transistors per circuit doubles roughly every 24 months).
36. Murphy’s Law: Anything that can go wrong will go wrong.
37. Alder’s Law: What cannot be settled by experiment is not worth debating.
38. O’Sullivan’s Law: All organizations that are not actually right-wing will over time become left-wing.
39. Pareto’s Principle (80/20 Rule): For many phenomena 80% of consequences stem from 20% of the causes.
40. Peter’s Principle: In a hierarchy, every employee tends to rise to his level of incompetence.
41. Poisson’s Law (or Law of Large Numbers): For independent random variables with a common distribution, the average tends to the mean as sample size increases.
42. Pournelle’s Iron Law of Bureaucracy: In bureaucracy, those devoted to the bureaucracy get control, those devoted to what it’s supposed to achieve lose influence.
43. Putt’s Law: Technology is dominated by two types of people: those who understand what they do not manage and those who manage what they do not understand.
44. Rosenthal Effect (Pygmalion Effect): High expectations lead to an increase in performance, low expectations to a decrease in performance.
45. Schneier’s Law: Any person can invent a security system so clever that she or he can’t think of how to break it.
46. Shermer’s Law: Any sufficiently advanced extraterrestrial intelligence is indistinguishable from God.
47. Zipf’s Law: The frequency of use of the nth-most-frequently-used word in any natural language is approximately inversely proportional to n (few words are used often, most are used rarely).
48. Wirth’s Law: Software gets slower more quickly than hardware gets faster.
49. Sturgeon’s Law: Ninety percent of everything is crud.
50. Stigler’s Law: No discovery is named after its original discoverer, including this one.

This piece was first written on July 6, 2020, and first appeared on my website on May 30, 2026.

I suggest running experiments every month or two to find new ways to improve your life. The basic procedure is simple:

(1) Think of something important you’d like to try to improve (e.g., your fitness, sleep, anxiety, dating life, friendships, productivity, happiness at work, etc.).

(2) Come up with a few ideas for something safe you could start doing (or start doing differently) that you think may have a reasonable chance of substantially improving the situation. (Don’t aim for things where the best case is that they would only very slightly help.) Pick from among them the one that you think is most likely to work.

(3) Do that new thing for long enough that you have a reasonably reliable guess of whether it caused an improvement (usually 1-6 weeks, depending on what you’re trying).

MORE ABOUT HOW TO DO SELF EXPERIMENTS WELL

It’s usually smart to limit yourself only to experiments that are very unlikely to cause a significant amount of harm. Otherwise, if you do enough of these trials, then eventually, you may be likely to significantly harm yourself. Remember that if you do N experiments, each with an approximate probability, p, of causing you significant harm (where p is smallish), then you’ll have roughly an N * p probability of significantly harming yourself at least once. So you’ll want to keep p (the probability of significant harm) very small if you make N (the number of experiments you conduct) large!

As I mentioned, it’s also usually a good idea to focus your experiments on interventions that could plausibly cause moderate to large impacts since you probably won’t be able to tell the difference between no effect and a slight effect, given the amount of day-to-day variation we usually experience. For instance, if something improves your mood by 2%, my guess is you won’t notice it unless the effect occurs within seconds. And if something improves your mood by 5%, my guess is you won’t notice unless it happens within 30 minutes. So unless the effects of an intervention are immediate each time you do the thing, I suggest you stick to looking for reasonably large effects.

With more careful data tracking, you can try to detect more subtle effects as well, but this is quite tricky and time-consuming to get right (it could take 1-3 months of careful data collection, and even then, you may not be able to tell what caused what, only that certain correlations exist). So I think it’s usually not worth it unless you enjoy tracking data, or the problem you’re working to solve is serious (e.g., you get terrible migraines once per week, and you want to pinpoint the cause, or you have started to experience an unpleasant chronic condition that varies in intensity day-to-day, and you want to figure out what might be causing it to be worse on some days).

TRACKING FOR SERIOUS PROBLEMS

In cases where you are trying to track something serious, consider recording all the relevant variables you can think of every morning and evening, and even consider randomizing behaviors that you think might be a cause (e.g., flip a coin to decide whether you do or don’t eat that food that you think might be a migraine trigger). You’ll want to choose a consistent method for measuring outcomes. For instance, if you are recording migraines, you might want to rate whether you have a headache or not, and also how bad it is on a “1=mild” to “5=severe” scale.

For interventions that have effects shorter than 24 hours (i.e., you expect little or none of the effect to spill over from day-to-day), you can try alternating or randomizing which days you do the intervention to make it a bit easier to tell if they’re working. Randomizing whether or not to try something on a given day makes it dramatically easier to determine causality (since otherwise there may be confounding variables that correlate both with the outcome you’re measuring and with whether you decided to try that thing). For instance, does sleeping late actually make you feel crappy, or do you just decide to “try out” the intervention of sleeping late when you’ve been drinking the night before, and it is alcohol that makes you feel crappy? Randomizing when you choose to sleep late will pull apart the two effects, so you can tell if it’s actually sleeping late that is causing you to feel bad.

A FEW EXAMPLE EXPERIMENTS

I try to run such an experiment on myself every month or two. Some of these are flops (they don’t make my life better or even make it slightly worse for that period). But when that happens, I stop, and it’s not a big deal since I usually avoid risky experiments. On the other hand, some of the experiments succeed, which means I’ve learned something new and potentially quite beneficial. At that point, I usually try to integrate whatever succeeded into my daily life as a more permanent change.

For instance, here are a few of the experiments I’ve tried just on my own sleep to give you some examples of what self-experiments can look like:
(1) Using a night mask when I sleep at night: makes me sleep longer, but I don’t seem to feel less tired afterward, so it seems to make me slightly worse off.
(2) Using earplugs when I sleep: I get woken up less often by random noises, so it seems worth it.
(3) Alternate using a pillow and not using one: I actually find it more pleasant not to use a pillow, as it turns out.
(4) Using small pieces of black tape to cover about 80% of every electronic light in the bedroom to make them less bright: I can’t tell the difference, but since the tape is already there and looks fine, I might as well leave it.

If that comes to pass, we’re going to be in trouble unless we also reach a better understanding of our own values and resolve the inconsistencies in them. We don’t have sufficient clarity on our values to say what the ideal world looks like. So if we ever have the power to truly redesign the world and ourselves, we can’t be sure what we should work toward. The options would be incredibly different (even potentially insane or nightmarish to some) depending on personal philosophies and values.

WHAT WE CAN AGREE ON

Suppose that (as is the case today) we have only a little power to change the world for the better. Say, only enough to fix a handful of problems in our world. While humanity is very complex, with many differing values, there are several changes that we can pretty much all agree would make the world better, the “easy to agree on” portion of world optimization.

For instance, nearly everyone can agree that, all else being equal, it’s better if:

-fewer people go hungry
-there is less disease
-murder rates fall
-fewer people are depressed
-more people know how to read
-people who want work can find work to do

While people certainly disagree about how we should best make these changes, we’d likely all celebrate such changes.

WITH GREAT POWER COMES GREAT CONFUSION

If incredibly advanced technology gives humans enormous power to reshape our environment (e.g., somehow tapping into nearly endless supplies of energy) and what we are like (e.g., brain modification or more impactful education and training), we will easily tackle the above issues. Once the world has transitioned from its current state to a state of where mutual priorities have been addressed, its unclear where to go from there. In other words, there are endless valuable optimizations to the world, but values differ so much that we can lack clear direction. What seems an optimization to one person may be the opposite to another.

POSSIBILITIES

Consider these possibilities for an “optimal” world, each of which holds up a different human value as its optimization goal:

1. Utilia : what truly matters is that the beings that exist are as happy as possible, so we should have a really small population and throw all resources into making each being happy by whatever means necessary (e.g. even if it means massively restricting the freedom of those beings, for instance preventing nearly all procreation, or keeping each being in a never ceasing state of bliss that it can’t get out of).

2. Utilon : what truly matters is the total sum of all happiness, so making the ideal world involves maximizing population growth while making sure that living beings are just happy enough so that the number of beings times the happiness per being is as large as possible (even if this means having incredibly large numbers of barely happy or minimally conscious but still slightly happy beings, or having all beings live highly restrictive existences in happiness generating machines).

3. Libertia : what truly matters is individual freedom, so what we should optimize for is giving every being the maximal choice for self determination (so long as it doesn’t come at the expense of other being’s freedom to self-determine). This means, presumably that we should create technology for each person to fully alter their own environment, body, face, personality, and values. It also means, presumably, that people should ideally be free to choose what they spend all their time doing, including choosing to do things that are very harmful to themselves or persuading others to (freely choose) to do things that are very harmful for those others.

4. Honoria : what truly matters is that people act in virtuous ways, so we should optimize the world to produce future generations that are maximally kind, honest, wise, courageous, fair, forgiving, humble, etc. Furthermore, if you think it’s not enough to be virtuous in a world with no temptation (since with no temptation anyone can be virtuous), and therefore that temptation is necessary for virtue to count, then we should also optimize the world to have numerous opportunities for sin, but train or modify humanity to be so virtuous that almost no one ever takes these opportunities to act un-virtuous. Furthermore, we may have to purposely built adversity into the world, so that certain virtues (e.g. courage or empathy) can be demonstrated.

5. Deus : what truly matters is obeying the commandments of God (or gods for polytheists), so everyone should be trained to follow God’s commandments as perfectly as possible, and to love/worship god maximally (if the commandments include loving or worshipping god). All temptations to violate God’s commandments should be removed, unless the religion views the act of resisting temptation as good in and of themselves (rather than just acting in accordance with the commandments).

6. Kantar : what truly matters is that everyone lives according to universal principles that can be willed as universal rules for all people to follow, and that no one uses anyone else as a means to an end (only as an end in themselves). Hence, some set of universal non-self defeating rules should be developed (that never involve using other people as ends), and all people in the future should be trained to adhere to these rules as closely as possible, while still having numerous (but almost never taken) opportunities to violate these maxims.

7. Angesia: what truly matters is preventing suffering, so the most important thing to do is to eliminate suffering for all beings (e.g. by redesigning genetics or our brains so that the moment we’re about to experience suffering we experience some distinct but neutral feeling instead – for instance replacing suffering with the experience of hearing the sound of a bell, with loudness proportional to how unpleasant that pain would have been, and the bell sound seeming to emanate from whatever part of us is in pain).

8. Natura : what matters is adherence to the natural law, that is, the pre-existing order of nature. Hence, nature and the animal world should be preserved as pristinely as possible (as it existed in one of its more stable equilibria before humans came along), and humans should be prevented from engaging in any “unnatural” behaviors.

9. Equalia: what truly matters is fairness, so the world should be created so that all beings are exactly equal with exactly the same training and opportunities. To maximize equality, everyone should presumably look the same, or maybe even should be born from the same genetic material (with mutations minimized), and with identical resources proportioned to each person at birth.

10. Evol: evolution itself is what matters, so humanity should compete to optimize genetic fitness (i.e. survival and reproduction of genes), and whichever beings can replicate genes or copies of themselves at the fastest rate will (and should) dominate until perhaps even “fitter” organisms eventually overtake them.

11. Democrus: what truly matters is that people get to collectively choose the way the world is, so all aspects of the world should be put to the vote, and whatever people vote on should determine what world we all live in, even if that world is terrible for the minority (but benefits the majority), and even if some people are highly uniformed about what they are voting into existence.

12. Intellig: what truly matters is maximizing intelligence, hence we should bring into existence the most intelligent beings possible (e.g. by massively changing our neurology, or by building super intelligent A.I.) even if these more intelligent beings end up with values that bear little resemblance to our own, or optimize for goals very different from our own, and even if humanity (as we now know it) forever loses control of the future once these beings exist.

13. Desir: what matters is the satisfaction of human desire, so every person should be able to conjure up any (presumably simulated?) experience at any moment that they want (e.g. to experience the taste of a particular food, or to experience what it’s like to believe you’ve just won the Nobel prize in literature, or to experience intense pleasurable states)

14. Humia: what truly matters are the things that modern human intuitive morality says matter, so we should create a world where people respect authority and social hierarchies, and where bad people are punished and good people rewarded, and where people are taught very effectively to be loyal to those who are loyal to them, and where people act purely (avoiding behaviors that many people’s intuitions would say are degrading or disgusting), and where people experience a minimal (but probably above zero) amount of suffering.

15. Minimi: : we don’t know what world to create, so we should err on the side of caution and only take care of changing the stuff we can mostly agree on (e.g. reduce hunger, disease, depression, etc.) and then we should just stop trying to optimize the world after that, and hope that whatever equilibrium it happens to fall into by chance is a really great one (by virtue of us having taken care of the mutual priorities).

16. Earth: we leave the world as it is, in approximately the same terrible state that it’s in now.

If none of these worlds really seem all that compelling to you, and quite a few of these sound terrible or terrifying, then you and I are on the same page.

The upside of this is: any group that wields power that is sufficiently great (i.e. power to remake the world and to dictate what humanity is like) can’t help but consider philosophy. But philosophy is hard. If you pick any one thing that seems “good” and optimize the world for that, you are likely to end up with something pretty strange that many people might consider a dystopia rather than utopia.

A real utopia would likely involve a mix of many of the aspects from the list above…but which aspects, and in which combinations? In other words: which world do we actually want humanity to eventually live in?

This post was inspired by discussions with Holden Karnofsky about similar topics.