Swarm scholarship and the fundamental epistemology of the collective method

Abstract

While it seems trivially true that adding additional scholars to study something should increase our knowledge, it is not clear exactly how they do so. Why should we think that something like ‘swarm’ scholarship would be successful? In this essay, I identify three basic ways in which studying a domain using a group of scholars could enhance our knowledge in ways traditional epistemologists could appreciate. One way is when each of number of individuals adds to the number of beliefs (or justification of beliefs) so the total amount of justified true beliefs we have increases. A second family is when something combines the beliefs claimed by different individuals into some kind of superior synthesis. A third family is when group members do things to help other group members add justified beliefs, creating a kind of multiplier effect.

Keywords:

• social epistemology
• wisdom of crowds
• aggregate

Notes

1. One of the earliest demonstrations of the accuracy of aggregating was given by the Marquis de Condorcet in 1785. Here, he proved that if people were better than chance at guessing the right outcome in a binary choice, as the number of people guessing increases, the chance that the majority will choose the right outcome with their aggregated votes approaches 100 percent. More recently, List and Goodin (2001) showed that when there are more than two choices available, the likelihood that the group's plurality choice will be correct is good even if individual choosers make the wrong choices more than 50 percent of the time. There can be, of course, circumstances in which averaging will not tend to produce an accurate result. Two such circumstances are:

a.	Where most of the people in a group are prone to systematically making the same type of error – keeping the various errors from canceling each other out.
b.	Where an initial chooser chooses wrongly, and others tend to imitate him (and/or each other).

So if we want to get more accurate information by aggregating the judgments of a group of scholars, we need to try to make sure they are as diverse and independent as possible. (See Surowiecki's The Wisdom of Crowds for a good discussion of these issues.)

2. Of course, there are various and sundry other ways that some group members can facilitate other group members adding justified beliefs. If people are able to conduct research better when they feel loose and limber, some group members giving backrubs to other group members could contribute to the group's ability to add to our pool of knowledge.

3. Even if human thought is not computational, AI programs are. If certain kinds of individual human thought can not be describable as a computer program, then that doesn't mean groups of people couldn't simulate knowledge-producing AI programs that are. Furthermore, if we find out that certain kinds of knowledge-producing thinking is not based on certain kinds of general symbol manipulation, but is dependent on certain kinds of ‘hardware’ (e.g., salmon using certain kinds of ‘magnets’ in their brains to locate their spawning grounds based on the earth's magnetic fields), we could still look for ways in which organized groups of people could mimic the utilization of this ‘hardware’ of this sort to produce kinds of knowledge.