Averaging the responses provided from a group increases accuracy by canceling out a number of errors made across the board (such as over- and under-estimating the answer).
What happens when we are on our own? What if there is no one else around to consult with before making a judgment - how can we be confident that we are giving a good answer? Psychologists Stefan M. Herzog and Ralph Hertwig from the University of Basel wanted to know if individuals could come up with better answers using a technique they designed and called "dialectical bootstrapping."
Dialectical bootstrapping is a method by which an individual mind averages its' own conflicting opinions, thus simulating the "wisdom of the crowd." In other words, dialectical bootstrapping enables different opinions to be created and combined in the same mind. For example, in this study, participants were asked to identify dates of various historical events. After they gave their initial answer, the participants were asked to think of reasons why the answer may be wrong and were then asked to come up with an alternative second (dialectical) answer.
The results, reported in Psychological Science, a journal of the Association for Psychological Science, reveal that the average of the participants' first answer with the second answer was much closer to the correct answer, compared to the original answers on their own. In addition, the dialectical bootstrapping method (that is, thinking about why your own answer might be incorrect and then averaging across estimates) resulted in more accurate answers compared to simply making a second guess without considering why the first answer may be wrong.
These findings suggest that dialectical bootstrapping may be an effective strategy in helping us come up with better answers to many types of problems. The researchers note that while it may be frustrating going back and forth between two different answers, "as dialectical bootstrapping illustrates, being of two minds can also work to one's advantage." They conclude, "Once taught about the tool, people could make use of it to boost accuracy of their estimates across a wide range of domains."