The target of criticism

Looking at my past two months of blogging, I seem to be talking a lot about critical thinking–i.e. how to argue. Why break the pattern now? My bloggy friend Coyote also likes talking about how to argue, and today I would like to borrow one of their ideas.

So, here’s the problem. Suppose I have a friend who just did a thing that annoyed me–they linked to a news story where a celebrity they dislike was swindled out of their money. To me, this is victim blaming–con artists often rely on victims being too embarrassed to admit they were swindled. So I vent by writing something on Twitter or Facebook about how much I hate victim blaming. But I don’t want to specifically call out my friend so I keep it general. My friend sees and cheerfully agrees with my post, but fails to realize that I was talking about them; they thought it was about sexual assault or something.

As Coyote put it:

If you want to tell people “this belief is wrong” or “this practice won’t do what you think it will” then the first step is making sure you can precisely and accurately describe the belief/practice in the first place, where “accurately” here is assessed by your audience (not you), because if nobody can see themselves in the flawed behavior as you’ve described it, then your criticism might as well be addressed to nobody.

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Fractals from Newton’s Method

This is a repost of an article I wrote in 2008, over ten years ago!  This is the one that explains where my avatar comes from.

Today, I will explain how I created this:

Three-colored fractal

This is a fractal. A fractal is a pattern that contains smaller versions of itself. But it’s not just any fractal. It’s a fractal I created from something called Newton’s method.

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In meta news

In case you missed it, PZ Myers launched a FTB Discord server.  As part of that, several blogs started dedicated channels, and I started one as well.  My channel’s currently quiet, which suits me fine, but if chatrooms are a format that appeals to you, then you’re invited to join.

I’d also like to mention that last week I touched up my banner so it’s less blurry, and added a favicon.  Not sure how many people knew this, but there is a puzzle embedded in the banner, which I personally designed and am quite attached to.

On subversivism

This has been crossposted to The Asexual Agenda.

“Subversivism”, according to Julia Serano, is

the practice of extolling certain gender and sexual expressions and identities simply because they are unconventional or nonconforming. In the parlance of subversivism, these atypical genders and sexualities are “good” because they “transgress” or “subvert” oppressive binary gender norms.

Serano criticizes subversivism because it creates a double-standard, where people who are perceived as having less transgressive experiences are excluded or othered.

Subversivism was established in Serano’s book, Whipping Girl, and further discussed in Excluded. Although, I admit that I have not read these books, and have instead gotten the short version from Serano’s blog. I refer to subversivism often enough that it seems useful to write up my own thinking about it, and discuss its applications to my own area of activism.

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Word count

As someone with a number of idiosyncratic opinions, and as someone who has extensively elaborated on my opinions, I think a great deal about length. If I take 2000 words to explain why X is wrong, then: A) how can I realistically expect anyone to read it? and B) how can I realistically expect anyone to go through the same thought process themselves, and end in the same place?

Realistically, I can’t expect any individual to read any of my writing. Most people don’t, you know. I have site statistics, I have the population of the world. I know a lot of people prefer different kinds of media… videos, memes, IRL conversations, collections of one-liners… I don’t judge. Or maybe they just don’t give a shit about whatever mother of all niches I have chosen to write about today.

And independent of whether people read what I say, it’s unrealistic to expect them to follow the same path. I’ve been blogging for long time, I know that not even I come to the same conclusions each time I address the same subject. I also like to think I put some sort of work and cleverness into forming my opinions. Well, if I’m so clever, how can I judge others for being less clever? Aren’t I kind of a high bar?

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Link Roundup: January 2020

I’m back from break, and I bring you links.

Christmas With The Kranks Is A Movie About Cults | Jack Saint (video) – Christmas with the Kranks is a Christmas comedy about a couple that decides to take a vacation on Christmas, but then the village gets wind of them and turns against them.  I’m pretty sure the movie is just taking the side of the creepy village, but Jack Saint ignores this interpretation for humorous effect, and explains a different reading.  I was thinking about this when PZ showed a real letter he received citing him for Christmas violations.

Music for Grocery Stores | Tris Mamone – Tris proposes that we should play more ambient music in public spaces.  I enjoyed this because it felt like a synthesis of two things I have written about: the ethical question of music in public spaces, and the appeal of drone music.  I think there’s a case to be made here–ambient music is the one thing in my library that my husband can stand despite having no appreciation for it.  Although, one thing that has developed out of my interest in ambient music is an ability to actively dislike some of the stuff, so even if everyone else shrugged off the mild piano of Music For Airports, I have to say it might offend my own sensibilities!

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Ethics of accuracy

Andreas Avester summarized Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil. Now, I’m not sure how many readers remember this, but I’m a professional data scientist. Which doesn’t really qualify me as an authority to talk about data science, much less the ethics thereof, but, hey, it’s a thing. I have thoughts.

In my view there are two distinct1 ethical issues with data science: 1) our models might make mistakes, or 2) our models might be too accurate. As I said in Andreas’ comments:

The first problem is obvious, so let me explain the second one. Suppose you found an algorithm that perfectly predicted people’s healthcare expenses, and started using this to price health insurance. Well then, it’s like you might as well not have health insurance, because everyone’s paying the same amount either way. This is “fair” in the sense that everyone’s paying exactly the amount of burden they’re placing on society. But it’s “unfair” in that, the amount of healthcare expenses people have is mostly beyond their control. I think it would be better if our algorithms were actually less accurate, and we just charged everyone the same price–modulo, I don’t know, smoking.

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