Sometimes we say things that we think are true—perhaps even things that _are_ true—which end up causing others to conclude something false. It's tempting to relate to such a situation primarily in terms of maintaining the innocence of one's soul—to say, fine, my readers became more wrong, but I'm not to be [judged](https://zackmdavis.net/blog/2025/Oct/the-relationship-between-social-punishment-and-shared-maps/) for it because I believed what I was saying; I wasn't _being misleading_ just because the people who believed me were thereby led into falsehood.
-The temptation reflects a confusion as to the nature of the judgment. Mostly, people don't care about judging the innocence of your soul; they care about whether they'll be led into falsehood the next time they take the risk of believing what you say—if there is a next time. If you want there to be a next time and you're going to have social emotions about it, the most productive emotion is _embarrassment_ rather than defensiveness. Visibly embarrassed people can be counted on to work hard to make sure that people won't regret believing what they say next time. Defensive people won't, because, well, why would they? They didn't do anything wrong.
+The temptation reflects a confusion as to the nature of the judgment. Mostly, people don't care about judging the innocence of your soul; they care about whether they'll be led into falsehood the next time they take the risk of believing what you say—if there is a next time. If you want there to be a next time and you're going to have social emotions about it, the most productive emotion is _embarrassment_ rather than defensiveness. Visibly embarrassed people can be counted on to work hard to make sure that people won't regret believing them next time. Defensive people won't, because, well, why would they? They didn't do anything wrong.
-Once, I suspected an ideological rival of misrepresenting a citation: the text of their claim linked to a webpage featuring an embedded PDF of an essay, but when I used my browser's "Ctrl-F" search functionality with appropriate search terms to see what in the paper justified the claim, I came up empty. When considering whether to escalate to complaining more loudly about my rival over this (after the rival didn't respond to a blog comment and a Discord DM), I mentioned the matter to a third party—who pointed out that the essay _did_ contain my search term! On further testing, it appeared that my web browser's Ctrl-F behavior depended on which page element had focus: if the user had last clicked inside the embedded PDF viewer, the search returned results inside the PDF, but not if the user had last clicked elsewhere on the page.
+Once, I suspected an ideological rival of misrepresenting a citation: the text of their claim linked to a webpage featuring an embedded PDF of an essay, but when I used my web browser's "Ctrl-F" search functionality with appropriate search terms to see what in the paper justified the claim, I came up empty. When considering whether to escalate to complaining more loudly about my rival over this (after the rival didn't respond to a blog comment and DM), I mentioned the matter to a third party—who pointed out that the essay _did_ contain my search term! On further testing, it appeared that my web browser's Ctrl-F behavior depended on which page element had focus: if the user had last clicked inside the embedded PDF viewer, the search returned results inside the PDF, but not if the user had last clicked elsewhere on the page.
-I was _so embarrassed._ I was embarrassed even though I knew I was innocent in my soul: the browser UX bug wasn't my fault, and if the browser hadn't been buggy, then my initial search would have succeeded and I never would have complained.
+I was _so embarrassed_.
+To be clear, I knew I was innocent in my soul: the browser UX bug wasn't my fault, and if the browser hadn't been buggy, then my initial search would have succeeded and I never would have complained. I [certainly didn't _lie_](https://zackmdavis.net/blog/2019/Dec/firming-up-not-lying-around-its-edge-cases-is-less-broadly-useful-than-one-might-initially-think/). (I didn't say that I read the essay and verified that it didn't support the claim, which was false; I said the Ctrl-F search came up empty, which was true.)
+But the innocence of my soul didn't matter. I knew that raising a suspicion that turned out to be false _looked bad for me_, even if there was ultimately a perfectly reasonable explanation for my actions. If I didn't want to look bad, I couldn't count on everyone hanging around to listen to my perfectly reasonable explanation for why it was all the Firefox developers' fault. I would need to make some sort of generalizable change to my policy—perhaps, reading the entire PDF myself next time before raising the suspicion that an ideological rival was misrepresenting it.
+(Recounting this seven years later, I went back and downloaded the PDF. Excluding the title page and the endnotes, it was six pages.)
+Another time, a journalist wrote an article paraphrasing a source as saying that journalists "discussing both critics and supporters" of some controversial public figure "could be unfair" and should instead "somehow prove statistically which side was right." I was familiar with the source's work, and the paraphrase didn't sound like something she would say, so I asked her about it. She said she had told the journalist that she "wasn't a huge fan of 'both sides' journalism, where you just find someone with one opinion and someone with the other opinion" rather than trying to figure out the truth and had given suggestions for data sources that might bear on claims about the public figure.
+[TODO—
+I thought the paraphrase in the article was misleading. ("Somehow prove statistically which side was right" leads readers who aren't familiar with the source's work to imagine that she has an unreasonable faith)
+
+"Is that necessarily what she said to me?" he said.
* "Yeah, well, what I meant was that I ctrl-F'd for it" would not be a good excuse
* If the person hadn't been my enemy, would I have been more likely to find it
* journalist who mis-paraphrases someone's actual views and then says, "But I wasn't there; is that what she said to me?" Even if we can't prove that he's mis-paraphrasing what she actually said, the journalist should be embarrassed that the paraphrase doesn't match actual views
+]
\ No newline at end of file
--- /dev/null
+Title: "So You Don't Trust Me?"
+Date: 2027-01-01
+Status: draft
+Category: philosophy
+Tags: honesty
+
+One of my favorite passages from _Atlas Shrugged_ is this one, when [Cherryl is beginning to have second thoughts about her marriage to James Taggart](http://zackmdavis.net/blog/2023/Jul/justice-cherryl/#iii):
+
+> It was his sudden, angry "so you don't trust me?" snapped in answer to her first, innocent questions that made her realize she did not—when the doubt had not yet formed in her mind and she had fully expected that the answers would reassure her. She had learned, in the slums of her childhood, that honest people were never touchy about the matter of being trusted.
+
+The logic here might be worth explaining in case it's not obvious. One might object: if you're honest (and therefore deserve to be trusted), _shouldn't_ you be touchy about people incorrectly not trusting you? Not trusting you is a _mistake_ that harms your interests and the other's. That's terrible! Why wouldn't you be touchy about it?
+
+The problem is that in order to be trusted, it's not enough to be trustworthy; the other needs to _know_ that you're trustworthy. You could try telling them, "Hey, you can trust me," but that doesn't work if a dishonest person could just as easily say the same thing.
+
+A solution, if there is one, has to take the form of [saying something that a dishonest person couldn't just as easily say](https://www.lesswrong.com/posts/ybG3WWLdxeTTL3Gpd/communication-requires-common-interests-or-differential).
+
+----
+
+Economists call the kind of situation in which it's possible for one kind of agent to say something that a different kind couldn't just as easily say a _separating equilibrium_. To understand separating equilibria, imagine two types of owners of spherical cats on a frictionless plane shopping for cat insurance: those with healthy cats, and those with sick cats. Insurance companies on the frictionless plane can't tell the difference between healthy and sick cats, and therefore face an [adverse selection](https://en.wikipedia.org/wiki/Adverse_selection) problem, where the very fact that someone is willing to buy insurance implies that they're less profitable to insure in expectation (because sick cats are in more need of cat insurance).
+
+Depending on some math that we don't have time for, there can be situations in which the adverse selection problem is solved by the different types of cat owners having incentives to buy different policies. Sick cats face a greater fraction of possible worlds in which they file a claim than healthy cats, so making those worlds worse for the policyholder by decreasing the policy benefit payout, decreases the expected value of the policy more for sick cats than healthy cats.
+
+As a corollary, the owners of healthy cats are willing to accept a smaller discount on premium to take out a smaller-benefit policy rather than a larger-benefit one. We end up in a situation where the healthy-cat owners pay a lower premium for a lower-benefit policy and the sick-cat owners pay a higher premium for a higher-benefit policy. The choice of policy becomes a signal that distinguishes the cats; neither type has an incentive to send the signal of the other. That's our separating equilibrium.
+
+But depending on some more math that we don't have time for, there are other situations in which we instead get a _pooling equilibrium_ in which everyone buys the same policy. The insurance company treating everyone in a pooling equilibrium the same amounts to treating healthy cats quantitatively more like sick cats and _vice versa_, because the company has no way to tell the difference. All the cats are mixed together and can't be distinguished in the fog of the market.
+
+There is a crucial asymmetry. Owners of sick cats would prefer that the insurance company falsely believe that their cats are healthy, whereas owners of healthy cats want their cats to be seen as they are. Pooling equilibria generally benefit the former at the expense of the latter. The existence of sick cats makes healthy cats shoulder the burden of more risk: the healthy-cat owners would prefer to transfer more risk to the insurance company by buying a policy with higher benefits, but the insurance company can't sell it to them, because then the sick-cat owners would buy it, too.
+
+(As it turns out, there are pooling equilibria that are better for the owners of healthy cats than some separating equilibria—but that's only because the cost they'd pay in reduced benefits-per-unit-premium to separate themselves from the owners of sick cats isn't worth it. They'd be even better off if cats never got sick.)
+
+----
+
+Or imagine a woman and a man in a recently-formed romantic relationship.
+
+[TODO:
+
+"I learned from a previous relationship not to teach people how to tell me things I want to hear."
+
+"I respect your security posture."
+
+]
+
+----
+
+And that's why honest people are never touchy about the matter of being trusted.
+
+They know that they have to pay a price to distinguish themselves from dishonest people,
+
+
+
+++ /dev/null
-Title: Trust Requires the Possibility of Distrust
-Date: 2027-01-01
-Status: draft
-Category: philosophy
-Tags: honesty
-
-One of my favorite passages from _Atlas Shrugged_ is this one, when [Cherryl is beginning to have second thoughts about her marriage to James Taggart](//zackmdavis.net/blog/2023/Jul/justice-cherryl/%23iii):
-
-> It was his sudden, angry "so you don't trust me?" snapped in answer to her first, innocent questions that made her realize she did not—when the doubt had not yet formed in her mind and she had fully expected that the answers would reassure her. She had learned, in the slums of her childhood, that honest people were never touchy about the matter of being trusted.
-
-The logic here might be worth explaining in case it's not obvious. One might object: if you're honest (and therefore deserve to be trusted), _shouldn't_ you be touchy about people incorrectly not trusting you? Not trusting you is a _mistake_ that harms your interests and the other's. That's terrible! Why wouldn't you be touchy about it?
-
-The problem is that in order to be trusted, it's not enough to be trustworthy; the other needs to _know_ that you're trustworthy. You could try telling them, "Hey, you can trust me," but that doesn't work if a dishonest person could just as easily say the same thing.
-
-A solution, if there is one, has to take the form of [saying something that a dishonest person couldn't just as easily say](https://www.lesswrong.com/posts/ybG3WWLdxeTTL3Gpd/communication-requires-common-interests-or-differential). Economists call the kind of situation in which this is possible a _separating equilibrium_.
-
-----
-
-To understand separating equilibria, imagine two types of owners of spherical cats shopping for cat insurance on a frictionless plane: those with healthy cats, and those with sick cats. Insurance companies on the frictionless plane can't tell the difference between healthy and sick cats, and therefore face an adverse selection problem, where the very fact that someone is willing to buy insurance implies that they're less profitable to insure in expectation (because sick cats are in more need of cat insurance).
-
-Depending on some math that we don't have time for, there can be situations in which the adverse selection problem is solved by the different types of cat owners having incentives to buy different policies. Sick cats face a greater fraction of possible worlds in which they file a claim than healthy cats, so making those worlds worse for the policyholder by decreasing the policy benefit payout, decreases the expected value of the policy more for sick cats than healthy cats.
-
-As a corollary, the owners of healthy cats are willing to accept a smaller discount on premium to take out a smaller-benefit policy rather than a larger-benefit one. We end up in a situation where the healthy-cat owners pay a lower premium for a lower-benefit policy and the sick-cat owners pay a higher premium for a higher-benefit policy. The choice of policy becomes a signal that distinguishes the cats; neither type has an incentive to send the signal of the other. That's our separating equilibrium.
-
-But depending on some more math that we don't have time for, there are other situations in which we instead get a _pooling equilibrium_ in which everyone buys the same policy. The insurance company treating everyone in a pooling equilibrium the same, amounts to treating healthy cats quantitatively more like sick cats and _vice versa_, because the company has no way to tell the difference. All the cats are mixed together and can't be distinguished in the fog of the market.
-
-There is a crucial asymmetry. Owners of sick cats would prefer that the insurance company falsely believe that their cats are healthy, whereas owners of healthy cats want their cats to be seen as they are. Pooling equilibria generally benefit the former at the expense of the latter. The existence of sick cats makes healthy cats shoulder the burden of more risk: the healthy-cat owners would prefer to transfer more risk to the insurance company by buying a policy with higher benefits, but the insurance company can't sell it to them, because then the sick-cat owners would buy it, too.
-
-(As it turns out, there are pooling equilibria that are better for the owners of healthy cats than some separating equilibria—but that's only because the cost they'd pay in reduced benefits-per-unit-premium to separate themselves from the owners of sick cats isn't worth it. They'd be even better off if cats never got sick.)
-
-----
-
-[TODO: relationship example]
-
-----
-
-And that's why honest people are never touchy about the matter of being trusted.
-
-They know that they have to pay a price to distinguish themselves from dishonest people,
projects / An_Algorithmic_Lucidity.git / commitdiff