2025-12-12 04:40:06
A lot of psychological terms don’t mean what people think they mean (at least, not according to psychologists).
There’s an increasing drift between how they get used colloquially in everyday language and the commonly accepted definitions among psychologists. There’s a sense in which the lay usage is “wrong” (in that it doesn’t match more scientific, precise, or technical usage), but of course, language has always been and always will be in flux. At the end of the day, a word does mean what people widely use it to mean. So I think it’s useful to be aware of both definitions for psychological concepts. The everyday concept helps us understand others, whereas the more technical definition is usually more helpful for helping us understand the way the world works. Here’s a list of examples:
1) Gaslighting
Everyday usage: Someone invalidating your perspective or lying to you in order to manipulate you
Precise usage: Manipulation that specifically causes someone to doubt their own senses or their ability to reason
2) Negative reinforcement
Everyday usage: Something bad happens when you do a behavior, so you do it less
Precise usage: Removal of an aversive stimulus after a behavior is engaged in, causing that behavior to increase (not a form of punishment). This is in contact with positive reinforcement, which adds a desirable stimulus after a behavior (which is a different way to get a behavior to increase).
3) OCD
Everyday usage: being a neat freak or someone who needs things done in a specific way
Precise usage: A disorder involving repetitive, intrusive obsessions and/or compulsions (behaviors performed to reduce anxiety) that are time‑consuming or impair function.
4) Depression
Everyday usage: feeling sad a lot
Precise usage: an ongoing near-daily pervasive depressed mood (sadness, emptiness, and/or hopelessness) or loss of interest or pleasure, that coincides with symptoms like fatigue, suicidality, poor concentration, weight change, or feelings of worthlessness.
5) Antisocial
Everyday usage: a desire to avoid being around other people
Precise usage: a personality disorder (ASPD) involving pervasive disregard for or violation of the rights of others, typically involving deceit, manipulativeness, aggression, and a lack of empathy/remorse.
6) Narcissist
Everyday usage: someone who is self-centered or very vain
Precise usage: a personality disorder (NPD) involving a grandiose sense of self-importance and superiority, need for admiration, and reduced empathy.
7) Trauma
Everyday usage: A very upsetting experience
Precise usage: Exposure to someone dying, serious injury, or sexual violence (DSM), or another extremely threatening or horrific event that has a long-lasting negative impact on a person’s mental function.
While there’s a time for going with the flow of culture, and using words however people casually use them, there’s an important role for more technically precise terminology as well. In the cases above, I believe the technical versions of these words are worth knowing about and understanding.
This piece was first written on November 7, 2025, and first appeared on my website on December 11, 2025.
2025-12-12 03:14:22
When you’re predicting how much a variable changes over time using a regression, do you tend to add the baseline value of that variable as a predictor to control for it? If you do, you can end up with misleading results.
For example, if you’re trying to predict change in anxiety in 2025 vs. last year (anxiety in 2025 – anxiety in 2024), you’ll get misleading results if you enter anxiety in 2024 as one of the predictor variables. If this sounds counterintuitive to you, read on. I’m interested in how many researchers might do this and how widely it’s known that this is a problem.
Quite a few papers have found a negative correlation between the signed change in the variable and its baseline value (e.g., see here, here, here, and here). For the reasons we outline below, such results can be expected even if there are no actual changes in x during the study, as long as: (1) the measurements for x1 and x2 are sufficiently noisy, and (2) there isn’t some mechanism whereby higher values of x1 somehow facilitate larger increases (or smaller decreases) in x.
You can grasp the result intuitively by looking at the formula for Δx:
Δx = x2 – x1
The larger x1 happens to be due to noisy measurements, then, as long as the noise associated with measuring x2 is independent of the noise affecting x1, the lower the value of the signed difference, (x2 – x1), will be. And the smaller x1 happens to be, the greater the value of (x2 – x1) will be. In other words, due to regression to the mean, if you take two noisy measurements and calculate the signed difference between them, you can expect that x2 – x1 will be inversely correlated with x1. But in case the intuitive explanation doesn’t work for you, we explain the result in other ways below. We also explain why this result might be a problem.
The Issue:
The issue comes into play for longitudinal studies when the outcome of interest is a signed change in some quantity (e.g., “income in 2020 – income in 2019” or “post-intervention anxiety scores minus pre-intervention anxiety scores”), specifically in situations where you try to control for the baseline value of the same variable (e.g., you include “2019 income” or “pre anxiety scores” as an independent variable in the regression).
We think this problem has implications for how we interpret the results of any papers that predict changes in a variable in this way. We explain the issue in detail below.
Suppose your goal is to study the signed change in some quantity over time. To keep things simple and concrete, let’s suppose you want to know what traits were associated with people becoming more anxious from 2019 to 2020 (on a self-reported anxiety scale). Hence, you might define your primary outcome of interest to be Δanxiety, the signed change in anxiety across time, like this:
Δanxiety = 2020_reported_anxiety – 2019_reported_anxiety
Now, you run a linear regression predicting Δanxiety using various factors to see what is linked to people’s anxiety changing. However, a person’s initial level of anxiety in 2019 (i.e., 2019_reported_anxiety) could be linked to how much their anxiety changes. For instance, if you don’t have a particularly high level or low level of anxiety in 2019, then maybe we should expect it not to change very much, or maybe if you have very extreme 2019 anxiety, we should expect a greater likelihood of it changing. Therefore, in your linear regression, you include as a control (i.e., an additional independent variable) 2019_reported_anxiety.
—
This all sounds very sensible (it’s precisely what we did in a recent study). You may think that controlling for the baseline value is a best practice. The unfortunate thing is that this can seriously bias your results for very subtle reasons!
Before we explain why this is a problem, please consider this puzzle and see what you think the answer is. Note that only 21% of my Twitter followers got this question correct!
—
A test of your math intuition: we use a very noisy but unbiased scale (accurate to +-40 pounds) to measure the weight of 1000 18-yr-old men on Monday and again on Tuesday. By noisy, we mean that each time you use the scale, you can think of it as giving the real weight plus random noise. By unbiased, we mean that on average, the scale gives the right answer (so if you weighed the same person repeatedly hundreds of times and took the average result, it would be very accurate).
Let
Δweight = Tue_weight – Mon_weight
What do you predict for the value of this correlation:
r = Correlation(Mon_weight, Δweight)
Option 1: r ≈ 0.00
Option 2: 0.1 < r < 0.9
Option 3: -0.9 < r < -0.1
Option 4: r ≈ 1.00
—
Answer: once you’ve thought about the question above, here is the answer (turn your phone upside down to read it):
ɹǝʍsuɐ ʇɔǝɹɹoɔ ǝɥʇ sᴉ ǝǝɹɥʇ ɹǝqɯnu uoᴉʇdO
—
Despite the issue we’ve outlined, it seems not uncommon for papers to predict the signed change in a variable using a set of variables that includes the baseline value of that variable. They don’t seem to discuss this problem, either. For example, see here, here, here, and here.
—
Why, if you are predicting a signed change in a variable, is it not okay to include the baseline value of that variable in linear regression?
The issue is that the signed change in a variable (e.g., Δweight = Tue_weight – Mon_weight) and the baseline value of that variable (e.g., Mon_weight) are going to be negatively correlated automatically in the absence of other factors, just as a result of how those two variables are defined (not due to any empirical fact about the world). So including both in a regression not only gives a misleading coefficient (i.e., it may show a negative relationship between them even when empirically one does not exist), but it may cause your whole regression to be misleading (e.g., p-values don’t have the interpretation you expect).
The negative correlation might lead some to conclude, for example, that the higher someone’s anxiety was prior to some intervention, the more their anxiety level dropped after the intervention – yet such a negative correlation (between baseline anxiety and the [anxiety at time point 2 – anxiety at time point 1] value) could arise even if there are no real changes in anxiety from one time point to the next!
—
The intuition here is that this is due to a form of regression to the mean. We usually think of regression to the mean as occurring when you purposely select for some subset of a population (e.g., those who perform best on a test), and then in the next time period, we expect to mean reversion. In this case, though, measurements that, due to chance, happen to be high will tend to fall (due just to regression to the mean), meaning the signed change between the two years will tend to be negative. And measurements at time one that happened to be smaller than normal due to noise will tend to rise the next time period (again due to regression to the mean), meaning the second value minus the first value will tend to be higher. So high time period one values will tend to have negative changes, and low time period one values will tend to have positive change values, leading to a negative correlation between the two of them.
If that’s still not intuitive for you, consider the opposite relationship – the one between the value of a variable at time point 2 and the signed change, calculated as (value at time point 2 – value at time point 1). It is true (and hopefully also intuitive for you) that larger values at time point 2 will be positively correlated with larger improvements from time point 1 to time point 2. (And, similarly, if time point 2 happens to be worse, then (value at time point 2 – value at time point 1) will be negative.)
—
What can be done about this?
There seem to be a few ways to resolve this issue.
(i) Instead of predicting the signed change in a variable, predict the final (time point 2) values. Then it’s okay (and often advisable!) to control (i.e., include as an independent variable) the baseline value. The issue discussed above is only a problem if you’re predicting the signed change in a variable, not if you’re predicting the value of the variable at time point two.
(ii) If it’s important to predict the signed change value (for instance, because that’s what you fundamentally care about), then it’s better not to control for the baseline value at all than to control for it and distort your results.
(iii) Several other approaches are summarized in the following paper: Chiolero et al. 2013
—
Thanks for reading – we’d love to hear your thoughts about this issue! Please comment below or contact us directly if you have any thoughts.
—
Some time after we wrote this, we later came across some papers talking about this phenomenon. (For an overview and some approaches to responding to it, see: Chiolero et al. 2013: https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2013.00029/full)
__
Acknowledgements:
I noticed this phenomenon in a dataset and my colleague Clare hypothesized that this phenomenon was to blame. We then confirmed this together. I wrote most of this post, and she added examples from the literature and the Chiolero et al. paper.
2025-12-03 03:07:39
I have a number of intrinsic values, but two of my most important intrinsic values are happiness and the lack of suffering for conscious beings. While these are fairly common intrinsic values, I suspect many people actually value them more than they realize. In other words, upon careful reflection, many people would realize that happiness and lack of suffering are stronger intrinsic values to them than they previously were aware of.
With that in mind, here are seven thought experiments related to happiness and suffering that might make you see your intrinsic values a bit differently:
— we don’t necessarily know our values —
Unfortunately, our deepest values are not something we automatically know about ourselves. The conscious side of our mind doesn’t have direct access to the rest of our mind. And much of what we care about lies in the subconscious, meaning that our explicit beliefs about our values may not be comprehensive or even accurate. So this at least opens the possibility that we might subconsciously value increasing strangers’ well-being more than we realize.
— our values are affected by our beliefs —
Some of what we value hinges on our beliefs about what’s true. And so if some of our relevant beliefs are false, or we haven’t fully explored all the implications of those beliefs (e.g., two things we believe imply a third thing but we haven’t realized that), then what we think we value may be, in a certain sense, “wrong”. So this at least opens the possibility that we might hold beliefs that are false or that contradict each other, such that, once they are corrected or the contradictions are resolved, we may end up caring more about increasing the well-being of strangers than we think we do now.
— our understanding of our values evolves —
We figure out our own values over time as we carefully introspect, discuss our values with others, compare options, notice and resolve contradictions, refine our understanding of the truth, flesh out the implications of what we already think is true, and infer things about ourselves from our own reactions. Hence, it is not that strange to think that our understanding of our values may change as we engage in reflection.
— a growing ember of classical utilitarianism —
So we may not fully understand what we value.
And I am proposing that through thought experiments about values, if carefully considered and reflected upon, quite a lot of people may realize that they care more about working to increase happiness or reduce suffering than they had originally thought. That many people are *partly* classical utilitarians in their values, even if they haven’t realized it, and that thought experiments can expose this.
— the thought experiments —
Warning: references to intense suffering and very difficult tradeoffs
(1) Suffering is bad, and not just for me
Remember that time when you felt really intense physical suffering (e.g., maybe you had a really nasty stomach flu)? Don’t dwell on that time, because I don’t want you to suffer now, but remember it just for a moment. Remember how much that suffering sucked?
Now take a few seconds to imagine a stranger. Someone you’ve never met and never will meet, but perhaps you passed them on the street at some point in your life. Take a moment to picture their face.
Now, suppose that right now this stranger is suffering in that same exact way that you recalled yourself suffering a moment ago. Assume this person is not someone who has done something terrible to deserve that suffering.
How do you feel about a state of the world where this stranger is suffering? Contrast it to a state of the world where that person is happy. I bet you think the latter world is better than the former.
I ran a survey asking people about their intrinsic values, that is, those things they value that they would continue to value even if no other consequences occurred as a result of that thing. In it, 49% of people (from the general U.S. mechanical Turk population that seemed to understand the question) reported that “people I don’t know suffer less than they do normally” is an intrinsic value, and 50% reported that “people I don’t know feel happy” is an intrinsic value.
It’s tough to measure people’s intrinsic values, and this is not a population that is fully representative of the U.S. population, so the exact numbers should be taken with a grain of salt. But these results suggest to me that many people do care about the suffering of strangers.
But now, the next question is, what properties should your caring about strangers have?
—
(2) Your friends care about the suffering of their friends
You presumably want the world to contain more of what your friends value (and less of what they disvalue) insofar as these values don’t conflict with your own.
Well, there’s a very good chance that one of the things your friends value is that their friends don’t suffer. Another thing your friends probably value is that their own friends get the things they value too, which presumably includes not wanting the friends of their friends (who are the friends of your friends’ friends) to suffer.
In other words, just by caring about the values of your friends, you may also care about the suffering of a whole host of other strangers. Not necessarily all strangers, but a lot of people you will never meet.
—
(3) More suffering is worse (a.k.a. scope sensitivity)
Suppose that 1 innocent person experiences a painful electric shock for one hour. How bad do you feel that is? Now suppose that instead of 100 innocent people, each experiences the same electric shock for one hour. How much worse does that seem to you? Take a moment to consider it.
Now 10,000 people. How bad is that? Now 1,000,000 people. How bad is that?
At first, you may feel on a raw gut level that the 1,000,000 suffering is not that much worse than 1 person suffering. But are you really taking into account how many people 1,000,000 is? That’s about the entire population of San Francisco.
Notice how, when you really think about it, and you really try to get the enormity of the large numbers, 1,000,000 innocent people each experiencing a painful electric shock for one hour is way, way, way worse than 1 person experiencing it. Not just, say, twice as bad. But MUCH worse.
That implies that, for instance, eradicating a common and horribly debilitating disease that ten million people would otherwise get is not just a little bit more valuable than helping, say, 1000 people live slightly easier lives. It’s way, way, way more valuable!
I’m not saying you necessarily value a reduction in 1 million units of suffering as being 1 million times more valuable than a reduction in one unit of suffering, just that you probably do think it’s MUCH more valuable.
—
(4) Selfishness does not dominate
What’s the thing you value most in the world? Your life, maybe? Or your happiness? Or maybe something involving another person? My guess is that no matter how much you value this, there is an amount of suffering you’d be willing to give this up to alleviate.
For instance, if you had to give up your life to prevent all future suffering on earth, I bet you would do it, as terrible and unfair a choice as it would be to make.
—
(5) We should help suffering strangers when it is easy (a version of the famous drowning child thought experiment that Peter Singer has popularized)
Suppose a stranger you’re walking behind suddenly teeters and then collapses in front of you. The person is now lying on the ground, clearly in tremendous pain. You are the only person nearby.
I think most of us feel that even though we didn’t cause this person to be ill, we still have a moral obligation to try to help them. That is, (a) not being the cause of suffering doesn’t make us totally off the hook with regard to trying to relieve that suffering.
Furthermore, suppose that it would be a small inconvenience for us to help this person (e.g., we might have to show up 15 minutes late to a fairly important work meeting). I think most of us would still help this person (and would feel that it is the right thing to do). If true, that suggests that (b), if the size of the potential reduction of suffering to another person is much greater than our own loss by our helping them, we probably should help.
Finally, suppose that instead of this being a stranger right in front of us, we imagine that this is a stranger who we happened to have accidentally just Skype called by accident (by entering our friend’s user ID incorrectly). Assuming we don’t believe the person on the other end is faking, shouldn’t we still try to figure out some way to help this person (assuming it is feasible), even though they are far away? Of course, if we have no way to help them, obviously, we have no obligation to help. But suppose we can think of an easy way to help, shouldn’t we do it? This suggests that (c) our obligation to help doesn’t depend on how far away someone is, only on our ability to help that person.
We must then remember, of course, that there are people we could help around the world at little inconvenience to ourselves.
Even if you agree with (a), (b), and (c), that doesn’t mean that you think you should devote all your time and money to helping people who are suffering. But if you do agree with those points, then I suspect your value system tells you that you should expend at least some of your resources helping reduce suffering in others, if you have the means to do so without too much sacrifice.
—
(6) Other values may seem to diminish when happiness is even slightly reduced as a consequence of them
Suppose that you happen to have found out that (through no action on your part) certain people have a false belief about a certain topic. Furthermore, you know they would believe you if you corrected this belief.
The problem is that these people would all be slightly less happy if they knew the truth about this thing, and in fact, nobody would benefit in any way from this truth being known.
Would you tell these people? Well, you may think truth is important (I do too), but you may feel that it substantially takes the wind out of the sails of truth if all people involved are less happy because of it, and nobody benefits. I think in this case, some people will say, “What is the point of the truth if everyone suffers slightly more because of it?” In other words, they might feel the value of truth is reduced to almost nothing.
This isn’t just about truth. For instance, you can do a version of this thought experiment about equality (what if, in a particular group of people, you could make the group more equal in some dimension, but every single member of the group would be slightly less happy as a result). Or you can do it for almost any other value.
My guess is that these other values seem quite a bit less valuable (and perhaps to some not even valuable at all) when everyone is slightly less happy as a consequence, highlighting the potential importance of happiness in your value system.
Note that you may not necessarily feel this property is symmetrical with other values. For instance, suppose that someone reduces suffering a significant amount, but in doing so causes the people involved in the situation to have slightly less accurate beliefs. You may not feel that the slight reduction in accurate beliefs makes the reduction in suffering itself any less valuable.
—
(7) We can at least agree on suffering
Some people like apples and others like oranges. Some want to spread atheism, and others want to spread theism. Some people think you should obey authorities, while others value freedom of thought. But one of the few dimensions we are just about all similar on is that we don’t want to suffer ourselves, and we don’t want the people we love to suffer.
Some people are perhaps exceptions (e.g., Christopher Hitchens claimed Mother Teresa believed suffering to be at least sometimes good, quoting her as saying “I think it is very beautiful for the poor to accept their lot, to share it with the passion of Christ. I think the world is being much helped by the suffering of the poor people.”) I’m not sure what she meant by that or whether she would apply that to her own suffering or that of her loved ones, but it’s a possible exception.
That being said, though, disagreement on the badness of suffering seems really rare. Nearly everyone seems to find suffering bad, at least when it happens to themselves or their loved ones.
So if we all had to work as a species to reduce one thing, suffering seems like a pretty good contender. It’s hard to think of another thing we all dislike more.
— final thoughts —
Taken together, these thought experiments suggest (insofar as you buy into them) that you may believe:
(1) Suffering is bad when it happens to strangers
(2) You at least somewhat care about the suffering of many strangers by virtue of caring about the values of those people you care about
(3) More suffering of strangers is worse than less, and way, way more suffering is much worse still
(4) Your own self-interest is not more valuable than the potential for reducing all the suffering in the world
(5) We should put at least a little effort into reducing the suffering of strangers if it’s not too costly for us to do so, and we should not care whether those strangers are far away or near
(6) Most other values don’t seem as great if the result of producing them is to cause everyone involved to suffer slightly more, with no one benefiting, and these other values may even seem to lose their value in these cases
(7) We can all at least agree that suffering is bad and work together to reduce it
These points are not the same as classic utilitarianism, but they point in roughly the same direction as it does, I think. And anecdotally, some people seem to be quite impacted in their ethical views by thought experiments like these (though of course we can’t be sure it’s because they are revealing their deeper values as opposed to actually reshaping those values).
I don’t think that increasing the happiness of and/or reducing the suffering of conscious beings is the ONLY thing you care about. Nor do I think you SHOULD only care about those things.
But perhaps these thought experiments will make you realize that you care more about them than you thought you did, or that you’re more of a classic utilitarian than you realized.
This piece was first written on June 2, 2018, and first appeared on my website on December 2, 2025.
2025-11-19 09:48:22
A lot of psychological terms don’t mean what people think they mean (at least, not according to psychologists).
There’s an increasing drift between how they get used colloquially in everyday language and the commonly accepted definitions among psychologists. There’s a sense in which the lay usage is “wrong” (in that it doesn’t match more scientific, precise, or technical usage), but of course, language has always been and always will be in flux. At the end of the day, a word does mean what people widely use it to mean. So I think it’s useful to be aware of both definitions for psychological concepts. The everyday concept helps us understand others, whereas the more technical definition is usually more helpful for helping us understand the way the world works. Here’s a list of examples:
1) Gaslighting
Everyday usage: Someone invalidating your perspective or lying to you in order to manipulate you
Precise usage: Manipulation that specifically causes someone to doubt their own senses or their ability to reason
2) Negative reinforcement
Everyday usage: Something bad happens when you do a behavior, so you do it less
Precise usage: Removal of an aversive stimulus after a behavior is engaged in, causing that behavior to increase (not a form of punishment). This is in contact with positive reinforcement, which adds a desirable stimulus after a behavior (which is a different way to get a behavior to increase).
3) OCD
Everyday usage: being a neat freak or someone who needs things done in a specific way
Precise usage: A disorder involving repetitive, intrusive obsessions and/or compulsions (behaviors performed to reduce anxiety) that are time‑consuming or impair function
4) Depression
Every day usage: feeling sad a lot
Precise usage: an ongoing near-daily pervasive depressed mood (sadness, emptiness, and/or hopelessness) or loss of interest or pleasure, that coincides with symptoms like fatigue, suicidality, poor concentration, weight change, or feelings of worthlessness.
5) Antisocial
Everyday usage: a desire to avoid being around other people
Precise usage: a personality disorder (ASPD) involving pervasive disregard for or violation of the rights of others, typically involving deceit, manipulativeness, aggression, and a lack of empathy/remorse.
6) Narcissist
Everyday usage: someone who is self-centered or very vain
Precise usage: a personality disorder (NPD) involving a grandiose sense of self-importance and superiority, need for admiration, and reduced empathy.
7) Trauma
Everyday usage: A very upsetting experience
Precise usage: Exposure to someone dying, serious injury, or sexual violence (DSM), or another extremely threatening or horrific event that has a long-lasting negative impact on a person’s mental function
While there’s a time for going with the flow of culture, and using words however people casually use them, there’s an important role for more technically precise terminology as well. In the cases above, I believe the technical versions of these words are worth knowing about and understanding.
This piece was first written on November 7, 2025, and first appeared on my website on November 18, 2025.
2025-11-18 06:54:53
There are a ton of false narratives that circulate widely in and about the US. To help combat that, here’s a list I’ve been compiling of facts that contradict common narratives related to the US that many people believe. In some cases, these facts contradict common beliefs that most Americans hold, whereas in other cases, they contradict beliefs held mainly just by some subgroups (e.g., subgroups on the far right or far left).
While I’ve spent time fact-checking these, I’m very interested in correcting any mistakes I may have inadvertently made. If you catch any mistakes, please let me know what I’m wrong about and what’s actually true.
Facts about the US that contradict commonly believed narratives:
1) Regarding political violence, the majority of Americans see it as…a big problem in society and as being “never justified” (liberals and conservatives agree on this), and the substantial majority view it as “always or usually unacceptable” to be happy about a public figure’s death.
2) The majority of murderers have…prior criminal history (e.g., arrests or convictions), and the substantial majority of homicides are committed by men under 45.
3) More than half of murder victims who were not murdered by a family member also have prior criminal histories (though, of course, this doesn’t mean that they deserve to be murdered).
4) The majority of homicides are committed due to personal arguments or are related to drug or gang activity, rather than random acts of violence.
5) School shootings kill…vastly fewer children annually than prosaic dangers like unsafe driving (though it’s a horrifying tragedy each time school shootings occur).
6) Mass murders (where 3 or more people are murdered at the same event) are most often… familicide, where a person kills their family, usually committing suicide afterward.
7) Regarding violence, since the 1990s, America has gotten…far less violent (while there was an uptick during the pandemic around 2020, it is still well below the 1990s peak).
8) Compared to alcohol, homicide leads to the death of…very few people (though it’s terrible whenever homicide occurs).
9) The majority of gun-related deaths are…suicides, not homicides.
10) In rural areas, the suicide rate (per million people) is…highest (urban areas actually have lower rates).
11) The vast majority of reported disappearances of children are…relatives taking a child (e.g., custody disputes) or runaways (rather than kidnappings).
12) Most rapes are carried out by someone the victim already knows (though in about 1 in 5 cases, the perpetrator is a stranger).
13) Women experiencing sexual assault are not…at all uncommon (more than 20% of adult women have been sexually assaulted at some point in their lives).
14) The most dangerous activity that is very common for people under 30 to engage in on a daily basis is…driving in cars.
15) Commercial airline crashes are…incredibly rare (despite the media attention), and commercial flights are far safer than driving per mile (whereas per hour they are closer to being on par).
16) For adults 25 to 35, the biggest killer is…accidental poisoning (which mostly consists of drug overdoses), not car accidents, and considering the whole adult population, opioid related deaths exceed deaths from motor vehicles.
17) Most personal bankruptcy is related to…sudden job loss or illness (which can simultaneously lead to large medical bills and loss of work).
18) The significant majority of federal taxes that the government collects come from…the top 20% of earners.
19) The percent of Americans who pay no federal income tax is…about 35% (though they still pay payroll taxes and sales taxes, and may pay property taxes and state taxes).
20) Regarding health insurance, the vast majority of Americans…are insured (about 90%), and while some people get extremely screwed by the system by being stuck with huge bills they can’t afford due to unavoidable medical challenges, most Americans say they are satisfied with their health insurance, even though they usually also say that the system overall is substantially flawed and needs significant reforms.
21) Most US federal government spending goes to…social security, health care (e.g., Medicaid/Medicare), military-related expenses (e.g., staff costs, veterans, vehicles), and interest payments on national debt (since interest rates have risen).
22) On average, legal immigrants commit crimes…at a lower rate than natural-born citizens.
23) Where immigration status is reliably recorded, undocumented immigrants have an incarceration rate…lower than that of U.S.-born residents.
24) It’s extremely rare that trans people…get murdered (of course, it’s a horrible tragedy when it does occur, and there are uncertainties around data collection); but current data indicates that suicide is a vastly more common life-threatening risk to trans people, and also, that trans people experience a substantially elevated risk of non-fatal violence compared to cis people.
25) Unarmed Black people who are stopped or engaged by the police have…an extremely low chance of being killed by those police (of course, it’s a horrendous tragedy when it does occur); however, Black people are substantially more likely than white people to be stopped by police without clear cause, and are far more likely than white people to be murdered by criminals.
26) Black Americans mostly want the level of police presence in their area…to stay unchanged (i.e., neither be decreased nor increased), with only about 1 in 5 wanting less policing, though most Black Americans do want other major changes to policing to be made.
27) Currently, much of the recycling that occurs…ends up being wasteful once you factor in all extra fuel burned in order to recycle those materials, the amount of “recycled material” that fails to actually be recycled, and alternative enviromental efforts goverment money spent on recyclying could have gone to instead; whether recycling is effective depends on the region as well as the type of material being recyled (e.g., aluminum is especially useful to recycle, whereas plastic recycling tends to be inefficient).
28) Our landfills are…mostly not close to running out of capacity (and when there are shortages, they are almost always local issues).
29) From a danger perspective, nuclear power is…extremely safe (especially when compared to many other sources of power, like coal), as well as very environmentally friendly (with almost no emissions and reliable solutions for storing the toxic waste produced); new reactor designs are dramatically safer than past ones, yet, nuclear power largely is stopped from being cost-effective due to excessive regulations that are extremely costly to comply with.
30) Almost all suffering that humans cause to domesticated land animals is due to…practices at large farms, such as tiny cages that animals spend almost their whole lives in, or being densely packed together in unpleasant conditions with little to no outdoor access and limited ability to engage in their natural behaviors.
31) Most individuals who experience homelessness are homeless for less than 12 months, but most of the people you see living on city streets, who are typically the most visible homeless people, are experiencing longer-term homelessness.
32) The majority of people who experience chronic homelessness are either experiencing a drug addiction or a significant mental health challenge, or both (though for some of these people, the addiction or mental health challenge occurred after homelessness began); a non-negligible percent (perhaps 20%, but estimates differ substantially) have neither challenge.
33) The primary causes of high housing prices are…factors that increase the costs of building new housing or that completely prevent it from being built (such as zoning, excessive regulations, lengthy approval processes, and local opposition), as well as, for popular places like New York City, net migration into those areas.
34) The majority of people in prison in the US at any given moment are there for…violent crimes, not non-violent drug-related crimes or victimless offenses – while the substantial majority of convictions are for non-violent crimes (since most crime is non-violent), violent crime typically carries much longer sentences.
35) Almost nobody who is charged with a crime goes to trial (they mostly take plea bargains).
36) The significant majority of people who are charged with a serious crime and go to trial are…convicted.
37) Regarding the US federal minimum wage, very…few people actually get paid that amount (in part due to higher minimum wages that many states have, and in part due to naturally occurring labor market prices that are simply higher than the federal minimum).
This piece was first written on November 2, 2025, and first appeared on my website on November 17, 2025.
2025-11-18 04:41:13
What causes bad things? It sounds like a huge question, but maybe it’s not as big as it seems. Here’s my updated/improved list of high-level causes of bad things in the world. Note that these are not mutually exclusive categories. I’ve also added some potential solutions for each cause.
I’d be interested to know: what is missing from my new list of causes of bad things and potential types of solutions? Thanks to those of you who commented on my prior version!
Causes of bad things in the world:
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1) EXTERNAL CAUSES
1i) Nature or evolution (e.g., malaria, cancer) -> Potential solutions: technological development, such as medical cures
1ii) Bad luck (e.g., landslides, earthquakes, droughts) -> charity, government programs providing social safety nets
1iii) Scarcity (e.g., insufficient food or water in an area) -> migration away from high scarcity areas, technological development to increase food production
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2) FAILINGS OF HUMAN NATURE
2i) Highly selfish actions by non-evil people (e.g., some of the crimes that are committed, some of the manipulation that occurs) -> cultural norms discouraging selfishness, cultural norms to punish those taking highly selfish actions
2ii) Harmful actions taken in highly emotional, confused, or desperate mental states (e.g., crimes of passion, harmful, desperate reactions out of fear, harm caused during extreme mental illness) -> widely available and effective mental health treatment, widespread education/training related to mental health and emotional regulation
2iii) Well-intentioned ideologues who are convinced that their simple but wrong model of the world is the absolute truth (e.g., some of the genocides and wars, many harmful yet well-intentioned policies) -> rationality education/training, a robust culture of respectful disagreement and debate
2iv) Cognitive biases leading to actions with severe negative consequences (e.g., greatly misjudging whether a project will bring enough benefit to be worth the cost, excessive fear towards or devaluing of ‘othered’ outsiders leading to mistreatment or harm to outsiders, lack of preparation for likely occurrences that are not salient) -> rationality education/training, careful design of systems to counteract biases, strong moral norms of respect towards all, moral circle expansion
2v) Retaliation or revenge (e.g., cycles of retribution) -> a culture of forgiveness, effective dispute resolution methods and institutions, reliable enforcement of laws
2vi) Evil people acting alone (e.g., serial murder, child abuse) -> effective police forces, high crime clearance rates, enforcement of laws, scientific investigation into the root causes of evil
2vii) Evil people who rally supporters (e.g., some genocides and wars, some extractive government policies) -> strong norms around truth telling and social punishment for lying, a robust culture of respectful disagreement and debate, a culture of empathy toward and acceptance of those who are different than you, a well-educated and informed citizenry, scientific investigation into the root causes of evil, a strong constitution, a strong independent judiciary, strong norms around maintaining freedom and independence of thought
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3) CHALLENGES OF COORDINATION AND INFORMATION
3i) Negative-sum competition (e.g., fighting over food when there isn’t enough to go around) -> technological innovation to increase abundance, thoroughly enforced laws forbidding negative-sum behaviors
3ii) Unintended side effects of actions that are not innately unethical (e.g., addiction caused by the invention of social media, new promising-seeming medical treatments that turn out to have horrendous side effects) -> a robust and low-transaction cost systems for those who were harmed to be compensated by those who caused the harm, hard to undermine enforced regulation requiring organizations to ameliorate harms once they have been identified
3iii) Collective action problems and negative externalities caused by individually reasonable behavior (e.g., pollution, climate change, overuse of resources) -> methods for assigning prices to negative externalities so that someone bears the cost, regulation to limit negative externalities
3iv) Prisoner’s dilemmas and difficulties of pre-commitment and coordination (e.g., arms races, such as with nuclear weapons) -> technology to facilitate coordination and simultaneous action, public projects by governments and private donors
What other broad causes of bad things or potential types of solutions am I missing?
This piece was first written on November 2, 2025, and first appeared on my website on November 17, 2025.