Firstly, I wonder how this would apply to the “meta-ness” of skills. The first kind of dimensionality is for the distinct skills, e.g. macroeconomics, tennis, cooking, etc. Another kind of dimensionality is for how meta the skills are, I.e. how foundational and widely applicable they are across a skills “hierarchy”. If you choose to improve the more foundational skills (e.g. computing, probabilistic reasoning, interpersonal communication) then you’ll be able to have really high dimensionality by leveraging those foundational skills efficiently across many other dimensions.
Secondly, I wonder how we might reason about diminishing returns in terms of the number of dimensions we choose to compete on. I can choose to read the Wikipedia overviews of 1,000,000 different fields, which will allow me to reach the Pareto frontier in this 1,000,000-dimensional graph. However, this isn’t practically useful.
PS: this was an excellent post and explained a fascinating concept well. I’ve been binge-reading a lot of your posts on LessWrong and finding them very insightful.
I can choose to read the Wikipedia overviews of 1,000,000 different fields, which will allow me to reach the Pareto frontier in this 1,000,000-dimensional graph. However, this isn’t practically useful.
That… actually sounds extremely useful, this is a great idea. The closest analogue I’ve done is read through a college course catalogue from cover to cover, which was extremely useful. Very good way to find lots of unknown unknowns.
To both of you, I say “useful relative to what?” Opportunity cost is the baseline for judging that. Are you excited to read N field overviews over your next best option?
Good points by both of you. I like the idea of discovering unknown unknowns.
I should’ve clarified what I meant by ‘useful’. The broader point I was going for is that you can always become Pareto ‘better’ by arbitrarily choosing to compete along evermore dimensions. As you said, once we define a goal, then we can decide whether competing along one more dimension is better than doing something else or not.
Firstly, I wonder how this would apply to the “meta-ness” of skills. The first kind of dimensionality is for the distinct skills, e.g. macroeconomics, tennis, cooking, etc. Another kind of dimensionality is for how meta the skills are, I.e. how foundational and widely applicable they are across a skills “hierarchy”. If you choose to improve the more foundational skills (e.g. computing, probabilistic reasoning, interpersonal communication) then you’ll be able to have really high dimensionality by leveraging those foundational skills efficiently across many other dimensions.
Secondly, I wonder how we might reason about diminishing returns in terms of the number of dimensions we choose to compete on. I can choose to read the Wikipedia overviews of 1,000,000 different fields, which will allow me to reach the Pareto frontier in this 1,000,000-dimensional graph. However, this isn’t practically useful.
PS: this was an excellent post and explained a fascinating concept well. I’ve been binge-reading a lot of your posts on LessWrong and finding them very insightful.
That… actually sounds extremely useful, this is a great idea. The closest analogue I’ve done is read through a college course catalogue from cover to cover, which was extremely useful. Very good way to find lots of unknown unknowns.
To both of you, I say “useful relative to what?” Opportunity cost is the baseline for judging that. Are you excited to read N field overviews over your next best option?
Good points by both of you. I like the idea of discovering unknown unknowns.
I should’ve clarified what I meant by ‘useful’. The broader point I was going for is that you can always become Pareto ‘better’ by arbitrarily choosing to compete along evermore dimensions. As you said, once we define a goal, then we can decide whether competing along one more dimension is better than doing something else or not.