In this article, Simson L. Garfinkel explores Wikipedia’s epistemology and discovers that, far from being the free-for-all its detractors portray it as, the world’s most popular reference is decidedly rigid. In its effort to ensure accuracy, Wikipedia relies entirely on “verifiability,” requiring that all factual claims include a citation to another published source (preferably online, preferably in English). As a result, Garfinkel argues, “on Wikipedia, truth is received truth: the consensus view of a subject.”
There are, of course, times when the consensus view and the truth align perfectly. The problem is how to determine when this is the case. In an essay for TR published in April 1956, the former head of the MIT mathematics department, H. B. Phillips, described one method for doing so. Since Phillips was a mathematician, it’s little wonder he appealed to the laws of probability for a solution.
Here … is the objective criterion determining whether we know or do not know. When nearly all agree who claim to know, it is reasonable to assume that the majority view is correct. The answer may still be wrong, but if a decision is necessary the probability of error in such a case does not justify hesitation.
Although Phillips referred to his criterion as “objective,” it in fact takes an agnostic attitude toward the truth. It doesn’t matter whether we have fully established the truth of any given statement, because if the relevant experts are unanimous in their opinion, we can proceed as if we had. However, Phillips realized that unanimity on anything is difficult to achieve, and that we are often left to evaluate conflicting claims.
The problem is then what to do when agreement is not practically unanimous. This problem has been handled in several ways. One method is to leave the decision to a dictator. In primitive societies that was probably not a bad solution, but one that is now completely obsolete. Another method is to leave the decision to the intellectually superior. When the experts are in substantial agreement, as in science and engineering, that is certainly the correct solution. But when there is considerable difference of opinion, there is no evidence that the intellectuals supply any better answers than ordinary people. …
These methods all have a common defect, namely, that they lead to a single solution, and when the experts do not agree any single solution is a matter of chance and therefore probably wrong. Some would say there is as much chance that such a decision would be right as wrong. But this is not correct. The choice is not one out of two, but one out of many. It is as if one should say, “I don’t know how much two times three is, so I’ll take a chance and say it is seven.” Such guesses are almost certain to be wrong.
Phillips once again advocated a probabilistic solution, reasoning in this case that the more freedom people have to answer a question or propose a solution to a problem, the greater the chances that any one of them will have success.
If any single solution is probably wrong, the only way of increasing the chance of success is to try simultaneously a large number of solutions. The probability of including a correct solution will increase with the number of choices, and will be greatest if each individual makes his own choice. …
When the proper course is known, action can be directed by rule or law. But when the proper course is not known, each individual should be free to go his own way to provide the greatest diversity of action and therefore the greatest probability that somebody will be right.
This diversity of thought and action is what Wikipedia has tried to harness in building its vast and ever-expanding knowledge base. By letting anyone contribute, regardless of his or her credentials, it runs the risk that absurdities, inconsistencies, and misinformation will flourish. But a free society, as Phillips argued, must allow each of its members “the privilege of being wrong.”
Five poems about the mind
Work reinvented: Tech will drive the office evolution
As organizations navigate a new world of hybrid work, tech innovation will be crucial for employee connection and collaboration.
Investing in people is key to successful transformation
People-related factors like talent attraction and retention and clear top-down communication will determine whether your transformation progresses or stalls.
The way forward: Merging IT and operations
Digital transformation in any industry begins with bridging the gap between two traditionally separate teams.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.