Six Specializations Makes You World-Class

There are other points in support of your counter argument too. Defining the boundaries of a “skill” is arbitrary. Are we comparing ourselves to professionals or laypeople, and what counts as a useful level of achievement?

This same objection comes up on this website every time this argument gets made. You can find it in some of johnswentworth’s posts. The motion of the argument is always from the “combinations of skills makes you world-class” -> “the good ones are all taken,” not the other way around.

The central point, unstated here, is that we need to find ways of sparking our imagination to see how we can get beyond imitation and into innovation.

It’s hard to go from a combination of very general skills (cooking, tractor repair, math, stand up comedy, arctic exploration) to a concrete idea for a job, invention, or research project.

Instead, focusing on the most important, tractable ideas pushes people to gain new skills outside their specialty. Those who hyper-specialize limit themselves to projects that are tractable within their current skillset. Those who are willing to learn in an open-ended way to pursue the most interesting goals acquire targeted micro-skills outside their main discipline.

This suggests an association between having a variety of skills and significant, world-class achievement. But it’s not that achievement will consistently follow from arbitrary skill combinations, but rather that the remaining available achievements can only be unlocked by mastering previously unknown skill combinations.

There’s an unstated call to action here. If you’re choosing between a moderately interesting project that’s fully within your skillset, and a very interesting one that requires learning some far-afield skills, choose the latter.

Exactly. Really, the title should be "Six specializations makes you world-class at a combination of skills that is probably completely useless." Really, productivity is a function of your skills. The fact that you are "world class" in a random combination of skills is only interesting if people are systematically under-estimating the degree to which random skills can be usefully combined. If there are reasons to believe that, then I would be interested in reading about it.

Another interpretation of that website would conclude $S=12,000$ (though I think just using the big categories $S=1,388$ works better). Thank you for the link. I originally thought $S=100$ might be too high but now I feel it might be too low.

Looking for pre-existing career paths is doing the opposite of what my article recommends because pre-existing career paths are, by definition, domains with competition. To follow the advice in this article, you usually must discover or "invent a new meaningful combination of skills".

Many meaningful combinations are not being competed on. For example, nobody is writing good Harry Potter Rationalist fanfiction right now and that's just $n=2$ (fiction writing and rationalism).

I think you meant 80,000 people.

Of course you can try and invent a new meaningful combination of skills, but that's just another skill combination, and it's one that a lot of people are already competing on. Caveat: this may not be very true (outside not-completely-incompetent entrepreneurship).

Thank you for the correction. Adding the missing factorial increases the answer from five to six.

You don't need a unique combination. You just need combination nobody else is competing at. If someone has more skills than you then there is a combinatorial explosion in the possibility space available to zem. The odds zir work collides with yours goes down fast as the number of skills your superior has goes up. Ze likely have better things to do than compete with you.

Specialization is typically framed as "narrowness of skill," and I think lsusr and others are pointing out that this is the wrong frame by which to understand it. Instead, I think they're pointing out that "narrowness of problem" is a better way to define specialization. A wide range of skills may easily be necessary to tackle the most valuable problems.

lsusr is also pointing out in the comments that we may not be able to figure out what problems exist until we've gained some relevant skills.

My sense is that it's the arbitrariness of combining skills at random that is bothering a lot of commenters, here and elsewhere. I think that's important. I also think there's a synthesis.

It seems to me that navigating toward interesting problems involves reasoning under uncertainty.

"If I spend another 3 months improving my skills, should I learn something new (say, immunology) or something I already know how to do (say, machine learning)?"

People are making a prediction partly on whether learning immunology or more ML will be useful for the problem they're already focused on. But they're also predicting which investment is more likely to expose them to a new and more valuable problem to solve.

lsusr's arguing that people tend to focus on the problems they already know about. Having 3 months of ML under your belt makes you aware of the problems you could solve with 6 months of ML experience. That may incline you to invest in another 3 months of ML learning. But if you considered all the unknown unknowns you'd be exposed to if instead you spent those 3 months focused on immunology, you might find that broadening your skill base tended to result in counterfactually more valuable exposure to problems and opportunity to create value for others.

So we don't have to imagine that the new skills are chosen arbitrarily. That's sort of what the post implies, but I don't think it's core to the argument. Instead, the new skills can be chosen based on what seems like it offers the most potential for cross-fertilization. Even so, you're still making a choice between acquiring that novel skill, or improving a skill you already possess.

If the choice between investing equal amounts of time into a new vs. old skill seems intuitively to offer about equal value, choose to acquire the new skill. Most of the value in improving the old skill is apparent when you're making the decision. Most of the value of learning the new skill will become obvious only after you've learned it. So there's a systematic bias against broadening your skillset, and it takes a rule like this to overcome that bias.

I don't recognize the exact blog post you reference but in my personal experience the actual number of skills that put me on a useful Pareto frontier is indeed closer to 3-4. To be clear, I don't get there by just learning 3-4 different skills. I learn like 8-10 and then a subset of 3-4 gets me to the Pareto frontier.