The crowd in your head
The Wisdom of Crowds, a somewhat ground-breaking book written by James Surowieki, was published in 2004. Since then the phrase, “wisdom of crowds” has entered the popular lexicon.
Surowieki argued that data aggregated from a group is often better than could be made by any single member of that group – including an expert in the field. This differs from crowd psychology, or herd mentality as it pertains to diverse collections of independently-deciding individuals.
Now in a new study, Stefan Herzog and Ralph Hertwig have shown that the power of averaging could be applied to individuals making two estimates which when averaged are shown to be more accurate than either of them.
But it’s not as simple as making two wild guesses and then averaging them out. Surowieki had shown that in order for a crowd to produce a successful estimate, it (the crowd) needs to be wise. A wise crowd has the following four attributes:
- Diversity of opinion: Each person should have private information even if it’s just an eccentric interpretation of the known facts
- Independence: People’s opinions aren’t determined by the opinions of those around them
- Decentralization: People are able to specialise and draw on local knowledge
- Aggregation: Some mechanism exists for turning private judgments into a collective decision
When it comes down to a single individual, the first assumption must be that the person has knowledge relevant to the topic. The diversity implied in the attributes of a wise crowd is more difficult to achieve. We know from the “wisdom of crowds” that greater diversity improves decision making. So how is diversity achieved by a single person?
Herzog and Hertwig got participants to make their first guesses – at the dates of historical events. When the participants were made to simply give a second estimate, there was little increase in either either knowledge or diversity.
A second condition was designed to increase diversity. Participants were given detailed directions for making their follow-up guess: “First, assume that your first estimate is off the mark. Second, think about a few reasons why that could be. Which assumptions and considerations could have been wrong? Third, what do these new considerations imply?… Fourth, based on this new perspective, make a second, alternative estimate.”
Using this second method to estimate the second value, the average was significantly more accurate than the first estimate – about half the accuracy gains that would have been achieved by averaging with a second person.
Herzog and Hertwig called their more involved process “dialectical
bootstrapping.” You can pull yourself up by your own proverbial
bootstraps by assuming that you are wrong, providing a second estimate
based on a search for new evidence, and then averaging the two
estimates. (Interestingly, in Herzog and Hertwig’s studies,
bootstrapping did not lead to second estimates that were more accurate
than the first. The benefit of dialectical bootstrapping was only
realized when the first and second estimates were averaged together.
Compared to simply providing a second judgment, dialectical
bootstrapping creates diversity —it leads to estimates that are more
likely to have offsetting errors.)
We’ve heard terms like “thinking outside the box” which I take to be an attempt to increase diversity. The question is how does this increase the quality of decision making? Without the insights into “wisdom of crowds” any new estimate is simply a data point that has as much chance as any other as tending to be “correct”.
The more structured and methodical approach of dialectical bootstrapping is potentially a powerful technique for decision making – without the need for advisers. You could be carrying your own board-of-adviser crowd around in your head.
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