Disclaimer: This is mostly me trying to articulate my current understanding of some CF concepts. (IOW, it’s not authoritative definitions.) I assume there’s heaps of errors in here. Please let me know if you notice any (or if you have any other feedback or ideas about how to better learn CF, etc., etc.) as my goal is to learn.
Dimensions
A dimension is a distinct property/trait/factor/aspect of an idea/solution that is qualitatively different (incommensurable) from other traits of that same idea. A dimension/trait of an idea can be measured or evaluated.
For example, imagine you want a pet. Your ideas/solutions are: dog, cat, hamster, snake.
Some dimensions/traits:
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Can you take the pet hiking? (Yes or no?)
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Does it have fur? (Yes or no?)
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Size. (Big or small?)
Goals are requirements for a specific dimension/trait. E.g., you want the pet to be big, have fur, and able to go hiking. Not small, furless, or unable to go hiking.
Qualitative vs quantitative, digital (including binary) vs analog, discrete vs degree
Some dimensions are qualitative. Some dimensions are quantitative.
Qualitative (Discrete/Digital): Dimensions that consist of different categories. E.g., color (red or blue?), shape (triangle or circle?), able to go hiking (yes or no?).
Quantitative (Degree/Analog): Dimensions that exist on a spectrum. E.g., height, weight, quantity.
I could try to understand this better. I could also seek more clarity about the differences between qualitative/quantitative vs discrete/degree vs digital/analog.
I saw this post, which made me think that maybe I should study qualitative vs quantitative more (and ditto for other CF concepts!):
Also, if I take The 10% Rule seriously, then I’ve got a whole lot more work to do.
Pessimism/optimism is an example of a degree spectrum:
Breakpoints
(Disclaimer: I made up these two terms.)
Categorization breakpoint: a point on a spectrum at which there is a relevant qualitative difference.
There can be a small number of these on a given spectrum. (E.g., shirt sizes, or BMI categories, e.g., the point at which a person’s BMI goes from merely overweight to clinically obese.)
Decision (or pass/fail) breakpoint: a breakpoint that separates success from failure.
Often there’s only one of these on a given spectrum. (E.g., the point at which a price exceeds your budget, or the number of soldiers needed to win a battle of attrition.)
But sometimes there can be two (e.g., not too hot but not too cold) or even more (e.g., a layover that is either very short or long enough to leave the airport and explore the city but not in the awkward zone where it’s long enough to be boring but too brief to leave the airport).
Purpose of breakpoints: Breakpoints allow you to turn a spectrum into discrete categories. The most important breakpoint is between pass and fail. This is important because success and action are binary: an idea either succeeds or fails, and you either do it or you don’t.
There’s other reasons that breakpoints are important: people can’t think in real numbers, and ditching analog prevents measurement errors from accumulating.
Rankings obscure the binary nature of action and criterion-satisfaction…
Even if you rank your ideas, you usually still end up only acting on one. E.g., even if you rank colleges from best to worst, you’ll usually still only attend one.
Even if you attempt to rank movies by, e.g., creating a top 100 movies of all time list, at any given moment in time, you’re only going to watch one movie. Also, I guess for each individual slot, you can answer: “Is this the number one best movie of all time? Yes or no? Is this the second best movie of all time? Yes or no?” Besides, if you gave the movies scores (e.g., 7.5 out of 10), that’s somewhat meaningless since you either watch it or you don’t. You can’t act on a 7.5 out of 10. You either act or not.
If you rank books into three tiers (e.g., ET’s FI book list), those tiers are discrete categories. E.g., putting a book in tier one means that the book satisfied the criterion of it being necessary to read in order to be “in a good position to have productive, intellectual discussions.”
…whereas CF exposes one’s reasons for rejecting stuff to scrutiny
Rankings also obscure decisive criticism. E.g., if I pick Movie A and reject others, then there’s a reason why I’m rejecting those others (they failed to pass some breakpoint that Movie A passed). There’s a reason why those other movies were not as good as Movie A for the current moment. Rankings allow people to avoid stating their reasons for rejecting stuff by just saying it’s lower on the list or just not as good in some vague way.
CF thinking, by contrast, makes one’s reasons for rejecting stuff explicit. This, in turn, exposes one’s reasons for rejecting stuff to scrutiny. Because making them explicit enables them to be examined. This is a way in which CF thinking can root out hidden biases and make the world more lucid/rational. I find this prospect extremely exciting.
I wonder if CF thinking might also have psychological benefits. Knowing exactly why one rejected Option A and went with Option B might make one feel less conflicted. Whereas rankings might make one feel unhappily torn between two almost equal options.
Generic breakpoints: rounding and maximizing (including constrained maximizing)
Rounding
One generic breakpoint is to use rounding to break up a spectrum into discrete categories (with each category having ”a distinguishable, noticeable amount more than the previous category”). E.g., categorizing people who are 5’9 vs 5’10 vs 5’11 (rather than worrying about fractions of an inch). Or rounding the price of homes that one is considering buying to the nearest $10k.
Why does this matter?
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People can’t think in real numbers (cf. crow epistemology)
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Worrying about small differences often doesn’t affect one’s goal
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People can have the goal of not wasting mental energy on low-impact differences (e.g., a $6.95 and a $6.98 jar of peanut butter can both be rounded to $7—and then one can focus on more significant stuff such as which brand’s jar looks yummier or what else to buy).
Maximizing (and minimizing)
A breakpoint between the best option and everything else. (Or, in the case of minimizing: breakpoint between the minimum and everything else.)
Constrained maximizing
Maximize given some constraints. E.g., I want the fastest car that is under 100k and has a 5-star safety rating. From the presentation: "maximize X while succeeding at requirement Y”.
Another type of constrained maximizing is Maximizing Up to a Point. An example from the presentation: "maximize X up to 60”. From a slide from the presentation:
You could make it more complicated. Maximize X up to 60, but also minimize X down to 90. 60-90 is the preferred range. If no solutions are in that range, then only the closest solution (and anything that ties it) would pass at this sub-goal
You could asymmetrically value closeness for too low or too high
E.g., to avoid going over project budget.
Maybe I should try to come up with examples of all of these types of maximizing.
Degree criticism, praise, decisive criticism
Degree criticism
A degree criticism says why an idea deserves a low score, has low goodness, is weak or kinda bad or mediocre.
But degree criticism doesn’t necessarily cross a pass/fail breakpoint. E.g., a degree criticism might say that a laptop is worse because it has 1 hour less battery life. But if it already has enough battery life for one’s needs, then 1 hour extra battery life is irrelevant.
Praise
Praise says why an idea deserves a high score, has high goodness, is strong or has merit.
But once again, praise doesn’t necessarily cross a pass/fail breakpoint. E.g., you might praise a meal for looking very appetizing, but if the meal has poison in it, then the praise is irrelevant. Or—when interviewing candidates for a job—you might praise one of the candidates for being very friendly, but if they’re inept, then that praise doesn’t matter. Or someone might praise communism for allegedly having a cool anthem (The Internationale) (or they might praise fascism for allegedly having cool aesthetics), but if one values freedom, then that praise doesn’t matter.
An additional reason why praise isn’t very useful: success requires that every (critical) part of a system works, but failure requires only one (critical) part of a system fail. So praising one part doesn’t mean much.
Are informal logical fallacies a species of DCOP (degree criticism or praise)?
E.g., if I criticize the moral character of an idea’s originator (ad hominem) or praise an idea’s popularity (appeal to popularity), that fails to explain whether the idea is true or not. I’m criticizing or praising stuff that’s irrelevant. But perhaps such fallacies are different from DCOP because presumably DCOP would address a relevant dimension of the idea itself (but ignore breakpoints) rather than address totally irrelevant stuff. So I guess there’s no overlap between DCOP and informal logical fallacies.
Decisive criticism
A decisive criticism is a reason/explanation of why an idea fails at a specific goal (in a specific context). I think it’s synonymous with a refutation or identifying an error.
Converting DCOP into decisive criticism
DCOP can be converted into decisive criticism by reframing the DCOP as a dealbreaker or requirement.
Praise can be converted into decisive criticism by reframing the merit as a requirement and rejecting all rivals that lack it.
A degree criticism can be converted into a decisive criticism reframing the weakness as a dealbreaker and rejecting all ideas that possess it.
E.g.: Imagine you’re considering two laptops. One has an 11 hour battery life, the other has a 12 hour battery life. Instead of praising the laptop with 12 hours of battery life or assigning a lower overall score to the laptop with 11 hours of battery life, you could say that one of your goals is to be able to use your laptop on a 12 hour flight. The laptop with only 11 hours of battery life fails to achieve your goal of being able to use it for the full duration of a 12 hour flight.
Tables: The relationship of IGC success to decisive criticism and DCOP
The relationship between decisive criticism and IGC success
| IGC Works | IGC Fails | |
|---|---|---|
| A Decisive Criticism Is True | FAIL: It is IMPOSSIBLE for the IGC to work because the IGC has a known error. | The IGC FAILS as expected because the decisive criticism is true. |
| All Proposed Decisive Criticisms Are False | The IGC WORKS as expected because it has no known errors. | The IGC FAILS because of a hitherto unknown error. |
The relationship between degree criticism and IGC success
| IGC Works | IGC Fails | |
|---|---|---|
| Degree Criticism Is True | The IGC WORKS because the deficit mentioned by the degree criticism didn’t cross the breakpoint. | The IGC FAILS because either the deficit mentioned by the degree criticism did cross the breakpoint or something else went wrong. |
| Degree Criticism is False | The IGC WORKS. | The IGC FAILS because of some other error. |
The relationship between praise and IGC success
| IGC Works | IGC Fails | |
|---|---|---|
| Praise Is True | The IGC WORKS because the total system (including the non-praised parts) meets the breakpoint. | The IGC FAILS because praising one part (or all parts) of the system doesn’t mean that the total system crosses the breakpoint. |
| Praise Is False | The IGC WORKS because either the praise targeted an irrelevant property or the property that was falsely praised still crossed the breakpoint. | The IGC FAILS because either the false praise was breakpoint-relevant or something else went wrong. |
Meta problem solving technique
If you want to do X, but you’re stuck on Y, what should you do? You can ask how to proceed given that situation.
If two ideas that disagree, and you don’t know the answer, what should you do? You can ask how to proceed given that situation. (Rather than waiting for the conflicting ideas to be resolved (which might take centuries of scientific research), you can figure out how to proceed given your current knowledge or situation.)
Meta problem solving chain
If one uses the meta problem solving technique but then gets stuck again, one can use the technique again for the new situation that you’re stuck in. For example:
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Given I want to do A and I’m stuck on B and I’m stuck on C, then what should I do?
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Given I want to do A and I’m stuck on B and I’m stuck on C and I’m stuck on D, then what should I do?
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Ad infinitum.
It should get easier each time because each question is easier and less ambitious. You should be able to come up with something to do in your life rather than being 100% stuck.
Is the meta problem solving technique (MPST) a little bit like an intrapersonal version of impasse chains?
I think the MPST a bit different from impasse chains because with impasse chains (AFAIK, I’m not that familiar with impasse chains) one actually tries to solve the impasses. But with the MPST, one just treats being stuck on X as a given (for now).