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[Ultimately_Untrue_Thought.git] / content / drafts / if-clarity-seems-like-death-to-them.md

diff --git a/content/drafts/if-clarity-seems-like-death-to-them.md b/content/drafts/if-clarity-seems-like-death-to-them.md
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--- a/content/drafts/if-clarity-seems-like-death-to-them.md
+++ b/content/drafts/if-clarity-seems-like-death-to-them.md
@@ -318,6 +318,14 @@ _Good_ criticism is hard. _Accurately_ inferring authorial ["intent"](https://ww
 
 -----
 
+While visiting Valinor one evening in September 2019, Merlin Blume (almost age 3) asked me, "Why are you a boy?"
+
+After a long pause, I said, "Yes," as if I had misheard the question as "Are you a boy?"
+
+I think I would have preferred to say, "Because I have a penis, like you." But it didn't seem appropriate.
+
+-----
+
 On 3 November 2019, I received an interesting reply on my philosophy-of-categorization thesis from MIRI researcher Abram Demski. Abram asked: ideally, shouldn't all conceptual boundaries be drawn with appeal-to-consequences? Wasn't the problem just with bad (motivated, shortsighted) appeals to consequences? Agents categorize in order to make decisions. The best classifer for an application depends on the costs and benefits. As a classic example, it's very important for evolved prey animals to avoid predators, so it makes sense for their predator-detection classifiers to be configured such that they jump away from every rustling in the bushes, even if it's usually not a predator.
 
 I had thought of the "false-positives are better than false-negatives when detecting predators" example as being about the limitations of evolution as an AI designer: messy evolved animal brains don't bother to track probability and utility separately the way a cleanly-designed AI could. As I had explained in "... Boundaries?", it made sense for _what_ variables you paid attention to, to be motivated by consequences. But _given_ the subspace that's relevant to your interests, you want to run an epistemically legitimate clustering algorithm on the data you see there, which depends on the data, not your values. The only reason value-dependent gerrymandered category boundaries seem like a good idea if you're not careful about philosophy is because it's _wireheading_. Ideal probabilistic beliefs shouldn't depend on consequences.
@@ -647,7 +655,9 @@ _ex cathedra_ statement that gender categories are not an exception to the rule,
 
 And really, that _should_ have been the end of the story. At the trifling cost of two years of my life, we finally got a clarification from Yudkowsky that you can't define the word _woman_ any way you like. I didn't think I was entitled to anything more than that. I was satsified. I still published "Unnatural Categories Are Optimized for Deception" in January 2021, but if I hadn't been further provoked, I wouldn't have occasion to continue waging the robot-cult religious civil war.
 
-[TODO: psychiatric disaster, breakup with Vassar group, this was really bad for me]
+[TODO: psychiatric disaster, breakup with Vassar group, this was really bad for me
+[As it is written](https://www.alessonislearned.com/), "A lesson is learned but the damage is irreversible."
+]
 
 [TODO: "Unnatural Categories Are Optimized for Deception"