Note: These are comments on the longest/”main” video in the Yes/No educational product, and specifically on the content starting at the 30 min mark and continuing until around the 60 minute mark. This is a selective summary/discussion of items and will omit many points and details, which you will have to pay for the whole product to get!
Part 1 of Video
(continued from previous post which also discussed Part 1)
Elliot says all correct arguments are decisive.
There’s two types of crit: false crits, and decisive crits which settle the matter by completely refuting an idea.
Elliot notes some people gather a bunch of bad arguments and think the collection of bad arguments is worth something. But it’s not.
J’s Comment: Yeah like, people will do spaghetti arguments in favor of some kinda conspiracy theory and have 20 args. And suppose you quickly refute five, they’ll still be like “BUT SURELY THERE MUST BE SOMETHING HERE!!! I HAVE FIFTEEN MORE!”
And if you refute the fifteen more they’ll just make minor variations or come up with more new bad stuff!
Elliot gives an example of someone thinking they’ve discovered a planet and it turns out there’s candy on their lens. The theory that they discovered a new planet is thus totally refuted, not 50% refuted.
Elliot says medium arguments don’t exist.
Part 2 of Video
Elliot says that Yes/No only uses negative arguments (criticisms), though positive args which can be rephrased into an equivalent negative argument are okay.
Negative arguments say why an idea doesn’t work. People think an idea can work but have a negative side effect — Elliot gives the example of a useful app costing money.
J’s Comment: From an economics perspective, being willing to buy something means you value it more than the money. Like if you buy a slice of pizza for $3, that means you value the pizza more than the $3. People can be really confused about this though. I guess partially because they don’t have a clear idea of what their values are, so they often don’t buy stuff in a non-coerced way. Like, their attitude isn’t “I’ve made judgments about what’s important given the wealth I have, and am happy to pay accordingly.” It’s more like “I HAVE to buy X, and Y, and Z, and now I can’t buy A, and B, and C, and that sucks.”
Elliot says you gotta think about your problems carefully in the context of your life. An app might do what you want it to do in terms of functionality, but cost too much. It can solve problem X but not X + Y. An app that has some functionality solves one problem — an app with the required functionality, that also costs less than $5, is a different problem.
Elliot gives an extended example involving pets. The main point is when you take a problem and then add some constraint onto it, that’s a different problem. And you need to understand what problem you wanna solve.
Positive arguments (that cannot be restated as negative arguments) are a myth. They are supposed to support ideas, but that’s false.
Elliot gives some examples re: positive arguments that can be restated as negative arguments and those that cannot.
J’s Comment: rather than restating Elliot’s examples, I’ll give my own to ensure understanding.
“I’ll buy a Mac, cuz I want a computer that runs OSX” could be restated as “I will not buy a Windows PC, because it does not run OSX.” So the argument is valid.
“I will buy a Mac, cuz I want a computer with a screen”, if restated as a negative argument, would be something like “I will not buy a Windows PC, cuz those don’t have screens.” That’s false, so the argument is invalid.
Part 3 of Video
Purpose of ideas
Elliot says ideas have a purpose. So one idea can work for one purpose and not for another. And a refutation of an idea relates to the purpose.
J’s Comment: yeah. “buy a calzone” is a good idea for lunch but not for making money.
More On Context
Elliot says people look at flaws out of context. That can be okay as an approximation but not if you need to be precise. And if a flaw doesn’t prevent an idea from succeeding at its purpose, it doesn’t matter.
Elliot says precision about the purpose and context can help when you are having problems figuring something out. With the support type approach, people are being wishy-washy and refusing to make judgments.
You don’t refute idea X. You refute idea X for purpose Y. There’s no out-of-context refutations. Ideas are trying to solve a problem of some sort.
Elliot says limited information is something you can deal with — there’s a best guess to make about how to solve X given not knowing Y.
J’s Comment: and i’d think in principle, even specifying some narrow context, you’re always dealing with limited information.
Like suppose you’re deciding what to have for lunch, and one of your considerations is wait time. You won’t know in advance the wait times down to the nanosecond. That’s no problem though! You don’t need infinite precision to come to a judgment regarding what’s too long a wait time.
Where to put the complexity
Elliot makes a subtle point: he says people often have a really simple problem, like “what dog should i get”, and put all the complexity in the solution. but some of the complexity should be in the solution and some should be in the problem. You can write down what problem you’re trying to solve and have a more sophisticated understanding of what the problem is.
J’s Comment: I think one reason it’d be good to have some of the complexity in the problem is it would help narrow down the field from the very outset and thus save on “search costs.” Like if you are considering a dog, then whether you want a cute pet dog, or a big scary dog to protect your house in a rough neighborhood, or a hunting dog, or a dogshow dog, or a dog to help you navigate cuz you’re blind, etc, (whoa there’s a lot of dog contexts!) is going to dramatically narrow the scope of dogs you’ll have to consider. There’s sort of like, pre-built standard lists of dogs that satisfy these functions, and you can just search through those and then apply your other crits to the candidates within that list instead of having to go through the whole universe of dog possibilities. Is that right? And either way, can you elaborate on the benefits to putting some of the complexity in the problem? I’m a bit fuzzy on that point.
Philosophical Problem Solving
Elliot describes the philosophical method of problem solving (I’m summarizing heavily):
Problems require you to learn the solution (create knowledge).
You learn my brainstorming ideas and criticizing those ideas (and then coming up with similar ideas that address the crit, or dropping the idea). This process is literally (not figuratively) evolution (since ideas are replicators).