Problem is, for GEM purposes, elbow room matters. Maybe I’m the on the pareto frontier of Bayesian statistics and gerontology, but if there’s one person just little bit better at statistics and worse at gerontology than me, and another person just a little bit better at gerontology and worse at statistics, then GEM only gives me the advantage over a tiny little chunk of the skill-space.
I notice the converse of a multi-dimensional skillset is multi-dimensional assessment. In the same way it is hard to hire good programmers without knowing anything about programming, it will be hard for anyone else to assess a pareto-optimal product or skillset along multiple dimensions simultaneously.
It seems to me this challenge is pareto legibility. The more dimensions on the frontier, the noisier the assessment will necessarily be. This introduces a meta-problem where one of the skills on which you want to get good-enough is making your pareto frontier position legible enough for others to benefit from it.
As a practical matter this doesn’t seem like that big a deal for consumer goods like books, where even laypeople can take reviews of “X about this book was so good” and “I liked Y about this book” and round this off into a feeling of “muchly good.” By contrast, legibility seems exceptionally important for something like the econometric modeling applied to proteomics example.
In Being The Pareto Best In The World you mention the problem of elbow room:
I notice the converse of a multi-dimensional skillset is multi-dimensional assessment. In the same way it is hard to hire good programmers without knowing anything about programming, it will be hard for anyone else to assess a pareto-optimal product or skillset along multiple dimensions simultaneously.
It seems to me this challenge is pareto legibility. The more dimensions on the frontier, the noisier the assessment will necessarily be. This introduces a meta-problem where one of the skills on which you want to get good-enough is making your pareto frontier position legible enough for others to benefit from it.
As a practical matter this doesn’t seem like that big a deal for consumer goods like books, where even laypeople can take reviews of “X about this book was so good” and “I liked Y about this book” and round this off into a feeling of “muchly good.” By contrast, legibility seems exceptionally important for something like the econometric modeling applied to proteomics example.