Just Shower Thoughts

"race is a social construct": a bit harder to swallow for some but still reasonable

It is absolutely immoral, completely counterproductive to the goal of learning things, and turns out incredibly subpar work.

This is a form of backdoor bigotry from both normative facts (there are more straight than gay relationships) and well represented bigoted beliefs (men are superior to women).

I HAVE FOUND MY FAVOURITE POST ON THE INTERNET

Laypeople (and also a concerning number of scientists) have often got the idea that unethical human experimentation is some sort of ultra-effective super science that would fix all the disease and discover all of the medicine and we only don't do it because it isn't nice (see: every science fiction show ever). No! Jumping straight from abstract theory to human trials is a terrible way to do science. It produces incoherent results and useless observations and nonsensical conclusions. We have pages and pages of historical precedent demonstrating this.

And lots of people have got the idea that totalitarianism is some sort of magic super-government that does all the government stuff really effectively abd efficiently and we only don't do it because it isn't nice. No!!!! "Let's put one idiot in charge and do whatever dumb shit they say" is the worst way to organize any project at all, let alone an economy and a political machine. Fascist regimes are models of corruption, waste, and inefficiency.

Person: And that sucks and it's a real shame but that just means that we need to be stricter about community justice and make sure that the accusations are actually true.

It also goes without saying that bioessentialism inherently can’t be trans inclusive no matter how hard you try. “All men including trans men—” probably not. “This is only a woman’s issue—” is it really? “Afabs only—” why? “All trans men are like—” what? what are they like? finish the sentence i dare you.

“You’re killing me,” I said. “I can’t take any more of that!”

Now serious, she said it was clear to her that none of that stuff about Mary’s clothes mattered, at least if her clothes weren’t the point. What mattered most about the image was that Mary was holding her diploma and smiling. “But,” she wondered, “do I say, Mary has a huge smile on her face as she shows her diploma or Mary has an exuberant smile or showing her teeth in a smile and her eyes are crinkled at the edges?”

It’s simple. Mary has a huge smile on her face is the best one. It’s the don’t-second-guess-yourself option. My thinking around this issue is enriched by the philosopher Brian Massumi’s concept of “esqueness.” He exemplifies it by discussing a kid who plays a tiger:

One look at a tiger, however fleeting and incomplete, whether it be in the zoo or in a book or in a film or video, and presto! the child is tigerized… The perception itself is a vital gesture. The child immediately sets about, not imitating the tiger’s substantial form as he saw it, but rather giving it life—giving it more life. The child plays the tiger in situations in which the child has never seen a tiger. More than that, it plays the tiger in situations no tiger has ever seen, in which no earthly tiger has ever set paw.

Just as the child and an actual tiger are not one bit alike, the words Mary has a huge smile on her face have nothing in common with the picture of Mary holding her diploma. Yet the tiger announces something to the world, its essence, and a kid can become tiger-ized and be tiger-esque, their every act shouting, I am a tiger. The picture of Mary at her graduation is shouting something, and the words Mary has a huge smile on her face are also shouting something. It is at the level beyond each actuality, in the swirl that each stirs up, that the two meet.

My husband and I have drilled into Pen the same thing that was drilled into both of us from a very young age (now mind you she's 4 so like, she's still learning things)

A recent analysis conducted by the AI startup Oumi at the behest of The New York Times found that the AI-generated summaries, which appear above Google search results, are accurate around 91 percent of the time.  In a sense, that may sound like an impressive figure. But here’s an even more impressive one: five trillion. That’s roughly the number of search queries that Google processes every year, translating to tens of millions of wrong answers that the AI Overviews are providing every hour — and hundreds of thousands every minute, the analysis calculated. In other words, Google has created a misinformation crisis. Studies have shown that people tend to trust what an AI tells them without question, with one report finding that only 8 percent of users actually double checked an AI’s answer. Another experiment found that users still listened to AI when it gave them the wrong answer nearly 80 percent of the time — a grim trend the researchers dubbed “cognitive surrender.” Large language models adopt an authoritative tone and can confidently present fabricated information as fact when it can’t immediately glean a straight answer. Add the convenience that Google’s AI Overviews offer, and it’s easy to imagine untold numbers of users taking its summaries at their word.