> The reason meritocracies work so well, is not because they are fair, but because they produce peak performance.
This is short-sighted. It optimizes for the "local maximum", the "today's maximum".
Yes, if today you don't choose the best candidate based purely on their results, you are technically losing, because you could do better. But here's the thing, if you choose a candidate that is not the best, but that can have a more meaningful impact in the long term, you are optimizing for the future.
For example, candidates who are coming from underrepresented groups can have a huge impact on kids who will find it easier to believe they can repeat such success, because someone who looks like them did it. That can unlock a huge pool of candidates who can outperform others in the future, but who would not be available if we didn't choose the n-th best candidate instead of the best one in the first place.
It doesn't even require generational returns. Underrepresented groups can bring a perspective to the project that you otherwise lack. Disabled team members can help you discover "curb cut effects" that improve usability for everybody. Women and minorities can point out hidden biases and opportunities. All of them can reveal assumptions you didn't even realize you were making in the way you run your team.
That goes far beyond "how fast can you write code" by any measurement because your end goal isn't to write code but to deliver a product -- as a team. Bringing in a diversity of ideas about the end product helps today, not just in the future. If you think of your team just as a bunch of high-performing individual code writers, you will miss opportunities to hit the real goal.
I like that your comment aligns with game theory. It is in the best interest of individual corporations to hire the best candidate. It is in the best interest of the industry to create a strong pool of candidates. An industry consists of individual corporations that act self-interested unless they cooperate to achieve long term goals together.
This dovetails with the free rider problem too. A corporation does not want to train (invest in) a subpar individual and then lose them to a free rider corporation in the industry that only hires the best candidates.
Ask yourself if you want the medic doing surgery on you, or to a less dramatic example the electrician working on your house, to be the best you can buy and you will quickly understand why in reality no one optimizes for the system's efficiency and everyone optimizes for own interest.
This is short-sighted. It optimizes for the "local maximum", the "today's maximum".
Yes, if today you don't choose the best candidate based purely on their results, you are technically losing, because you could do better. But here's the thing, if you choose a candidate that is not the best, but that can have a more meaningful impact in the long term, you are optimizing for the future.
For example, candidates who are coming from underrepresented groups can have a huge impact on kids who will find it easier to believe they can repeat such success, because someone who looks like them did it. That can unlock a huge pool of candidates who can outperform others in the future, but who would not be available if we didn't choose the n-th best candidate instead of the best one in the first place.