#semiotics

Language does not simply name pre-existing categories; categories do not exist in 'the world'

— Daniel Chandler, Semiotics for Beginners

I read this quote a few years ago, but I don’t think I truly understood it until one day, when I was looking at the wikipedia article for “star” and I thought to check the Japanese article, see if I could get some Japanese reading practice in. I was surprised to find that the article was not titled 「星」, but 「恒星」, a word I’d never seen before. I’d always learnt that 星 was the direct translation for “star” (I knew the japanese also contained meanings the english didn’t, like “dot” or “bullseye”, but I thought these were just auxiliary definitions in addition to the direct translation of “star” as in "a celestial body made of hydrogen and helium plasma").

To try and clear things up for myself, I searched japanese wikipedia for 星. It was a disambiguation page, with the main links pointing to the articles for 天体 (astronomical object) and スター（記号）(star symbol). There was no article just called 「星」.

It’s an easy difference to miss, because in everyday conversation, 星 and star are equivalent. They both describe the shining lights in the night sky. They both describe this symbol: ★. They even both describe those enormous celestial objects made of plasma.

But they are different - different enough to not share a wikipedia article. 星 is used to describe any kind of celestial body, especially if it appears shiny and bright in the night sky. “Star” can be used this way too (like Venus being called the “morning star”), but it’s generally considered inaccurate to use the word like this, whereas there is no such inaccuracy with 星. You can say “oh that’s not actually a star, it’s a planet”, but you CAN’T say 「実はそれは星ではなく惑星だよ」 (TL: that’s not actually a hoshi, it’s a planet). A planet IS a 星.

星 is a very common word, essentially equivalent to “star”, but its meaning is closer to “celestial body”. I haven’t looked into the etymology/history but it’s almost like both english and japanese started out with a simple, common word for the lights in the sky - star/星 , but as we found out more about what these lights actually were, english doubled down on using the common word for the specific scientific concept, while japanese kept the common word generic and instead came up with a new word for the more specific concept. If this is actually what happened, I’d guess that kanji probably had something to do with it - 星 as a component kanji exists inside the word for planet, 惑星, and in the word for comet, 彗星, and in the scientific word for “star”, 恒星, so it makes sense that it would indicate a more general concept when used standalone.

This discovery helped me understand that quote - categories don’t exist in the world, we are the ones who create them. I thought that the concept of “star” was something that would be consistent across all languages, but it’s not, because the concept of “star” is not pre-existing. Each language had to decide how to name each of those similar star-like concepts (the ★ symbol, hot balls of gas, twinkling lights in the sky, planets, comets, etc), and obviously not every language is going to group those concepts under the same words with the same nuance.

How to help the non technical and less online people in your life navigate the latest techbro grift.

I've seen other people say stuff to this effect but it's worth reiterating. Today in class, my professor was talking about a news article where a celebrity's likeness was used in an ai image without their permission. Then she mentioned a guest lecture about how AI is going to help finance professionals. Then I pointed out, those two things aren't really related.

The term AI is being used to obfuscate details about multiple semi-related technologies.

Traditionally in sci-fi, AI means artificial general intelligence like Data from star trek, or the terminator. This, I shouldn't need to say, doesn't exist. Techbros use the term AI to trick investors into funding their projects. It's largely a grift.

What is the term AI being used to obfuscate?

If you want to help the less online and less tech literate people in your life navigate the hype around AI, the best way to do it is to encourage them to change their language around AI topics.

By calling these technologies what they really are, and encouraging the people around us to know the real names, we can help lift the veil, kill the hype, and keep people safe from scams. Here are some starting points, which I am just pulling from Wikipedia. I'd highly encourage you to do your own research.

Machine learning (ML): is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines "discover" their "own" algorithms, without needing to be explicitly told what to do by any human-developed algorithms. (This is the basis of most technologically people call AI)

Language model: (LM or LLM) is a probabilistic model of a natural language that can generate probabilities of a series of words, based on text corpora in one or multiple languages it was trained on. (This would be your ChatGPT.)

Generative adversarial network (GAN): is a class of machine learning framework and a prominent framework for approaching generative AI. In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. (This is the source of some AI images and deepfakes.)

Diffusion Models: Models that generate the probability distribution of a given dataset. In image generation, a neural network is trained to denoise images with added gaussian noise by learning to remove the noise. After the training is complete, it can then be used for image generation by starting with a random noise image and denoise that. (This is the more common technology behind AI images, including Dall-E and Stable Diffusion. I added this one to the post after as it was brought to my attention it is now more common than GANs.)

5-10. Finger counting. Elementary exercises for the deaf. 1821.