Response to Dr. Collier on AI

I obviously watch a lot of youtube video essays, so I frequently get recommended thinkpieces about the problems with AI. And I don’t watch them because I am literally a professional in the field and I don’t need some vlogger to ramble at me about something I generally understand better than they do. But I watched one of these videos, and I disagree on some points, and now you’re going to hear about it.

The video is “AI does not exist but it will ruin everything anyway” by Dr. Angela Collier. It is not necessarily the best example to highlight (it’s an hour of rambling, I respect that most readers will not want to watch that), but it’s the one I watched, okay? I’m going to structure this as a list of items, starting with the most fact-based items, moving towards my more contentious opinions.

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Theories of “mind” for corporations

Jack Saint recently made a video remarking on Netflix, and how Netflix appeared to be criticizing itself. He was talking about the show Dahmer, which Jack Saint felt was exploitative. And then an episode of Black Mirror appeared to make the same point by portraying an exploitative documentary that was obviously in reference to Dahmer. I will not comment on either show because I don’t like TV enough to watch the stuff, and I only really enjoy watching youtubers talk about TV I don’t watch.

However, I do have an opinion on the supposed hypocrisy of Netflix, for putting out two television shows that thematically contradict each other. When a corporation like Netflix is hypocritical, that’s obviously quite unlike individual hypocrisy. It’s not a single individual saying something and then doing a different thing. It’s two groups of individuals who disagree with each other despite their common affiliation. The Dahmer creators don’t think it’s exploitative (or don’t care), and the Black Mirror creators do. The executives above them don’t care enough to intervene either way. There’s no real hypocrisy on an individual level.

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Semi-cooperative board games and the win/loss binary

In Twilight Struggle, if you cause nuclear war, your opponent wins and you lose. Twilight Struggle is a two-player strategy game that simulates The Cold War. As you know, in the real world, if there is a nuclear war then everyone loses. But in Twilight Struggle, nuclear war leads to one winner and one loser. This speaks to limitations in what a strategy board game can effectively simulate.

Twilight Struggle is simulating a semi-cooperative situation, which means it combines cooperative and competitive elements. A semi-cooperative game is one that allows one player to get ahead of the other, but also allows outcomes which are good for both players or bad for both players.  Note that ties don’t count, because they aren’t good or bad for both players!  A semi-cooperative game requires at least three distinct outcomes, outside of ties. In Twilight Struggle, the three outcomes are USA wins, the Soviet Union wins, or there is nuclear war. This is challenging to adapt to a board game format, because players are accustomed to only two non-tie outcomes: winning or losing.

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Link Roundup: July 2023

First, I’ll plug this month’s Ace Journal Club, which discussed a paper about Female Sexual Interest/Arousal Disorder and the “responsive” sexuality model.

AI Is a Lot of Work | The Verge – This article is about “annotators” or “taskers”, people paid to label data to train machine learning models.  You can think of this as people who are paid to do captcha codes endlessly.  Or imagine Papers Please, but it’s real.  As you might imagine, it does not pay very well.

From the data scientist end, this is a well-known process, although I don’t have direct experience with it.  Typically, you’d go through an intermediary, such as Amazon’s Mechanical Turk, and never learn anything about the workers themselves.  Despite workers being paid poorly, it’s an inherently expensive process, and requires a lot of controls.

Games that Don’t Fake the Space | Jacob Geller (video, 31 min) – Video games often use tricks and illusions to make a virtual space seem bigger than it is, but not every game.  Some really are that big.  Now the question I always have about measuring video game spaces is, what’s the measuring stick?  Could we make the world bigger by making the character smaller or slower, or simply lowering the camera closer to the ground?  I feel like virtual spaces should be measured in square minutes instead of square miles.  I have to put a word in for The Longing, which has a big world by virtue of its protagonist walking very very slowly.  You tell the protagonist to walk somewhere, and then you quit and come back later, that’s how slow he is.  It’s not a conventionally “fun” experience, but it’s interesting to see games do big/slow once in a while.

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Affirmative Action vs Fair Lending

The term “affirmative action” was originally created by John F. Kennedy in 1961, in the context of the employment of government contractors. But affirmative action has been very unpopular in the US, and was backed into a corner until it came to only refer to university admissions. Prior to the recent Supreme Court decision against affirmative action, the idea was already only hanging by a thread.

Now that the thread has been cut, I encourage people to imagine other possibilities. Previously, we could only ever talk about affirmative action in elite universities, because that was the only politically viable option. Now, none of the options are politically viable, so we might as well talk about the possibilities we forgot.

What if we had affirmative action… in hiring? Salaries? Political representation? Affirmative action tax breaks! If you’re outside the US, help me out here, what sort of affirmative action do they have in your country?
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Origami: Koi

Koi

Koi, by Robert Lang, with some adjustments by me.

This is a model from Origami Design Secrets–actually, it’s on the cover of the book.  It is a demonstration of the technique of pattern grafting, where you fold a flat pattern into the paper before going on to fold the general shape.

Robert Lang’s design is well and good, but I have a tendency to work with 15 cm paper at largest.  It’s not ideal for a lot of types of models, but it is my self-imposed constraint.  So, in my version, I made the scales very large relative to the size of the paper.  In Lang’s version, the scales are one quarter the size in both directions, meaning there are 16 times as many scales.  Lang’s version is more realistic, while mine mostly just evokes the idea of scales.

So the funny story was, I was thinking about how I could adjust the model to work with 15 cm paper, and I woke up one night thinking, “Of course!  I should just fold the paper into a 29×29 grid!  Then the proportions can remain the same and all the math works out!”  It turns out that my dream math isn’t very good, and 29×29 makes very little sense.  But it worked out anyway.