As group size increases you have to spend more and more of your effort getting your ideas heard and keeping up with the worthwhile ideas being proposed by other people, as opposed to coming up with your own good ideas.
Depending on the relevant infrastructure and collaboration mechanisms, it’s fairly easy to have a negative contribution from each additional person in the project. If someone is trying to say something, then someone else has to listen—even if all the listener does is keep it from lowering the signal-to-noise ratio by removing the contribution.
You correctly describe the problems of coordinating the selection of the best result produced. But there’s another big problem: coordinating the division of work.
When you add another player to a huge team of 5000 people, he won’t start exploring a completely new series of moves no-one else had considered before. Instead, he will likely spend most of his time considering moves already considered by some of the existing players. That’s another reason why his marginal contribution will be so low.
Unlike humans, computers are good at managing divide-and-conquer problems. In chess, a lot of the search for the next move is local in the move tree. That’s what makes it a particularly good example of human groups not scaling where computers would.
As group size increases you have to spend more and more of your effort getting your ideas heard and keeping up with the worthwhile ideas being proposed by other people, as opposed to coming up with your own good ideas.
Depending on the relevant infrastructure and collaboration mechanisms, it’s fairly easy to have a negative contribution from each additional person in the project. If someone is trying to say something, then someone else has to listen—even if all the listener does is keep it from lowering the signal-to-noise ratio by removing the contribution.
You correctly describe the problems of coordinating the selection of the best result produced. But there’s another big problem: coordinating the division of work.
When you add another player to a huge team of 5000 people, he won’t start exploring a completely new series of moves no-one else had considered before. Instead, he will likely spend most of his time considering moves already considered by some of the existing players. That’s another reason why his marginal contribution will be so low.
Unlike humans, computers are good at managing divide-and-conquer problems. In chess, a lot of the search for the next move is local in the move tree. That’s what makes it a particularly good example of human groups not scaling where computers would.