Making group judgements better than individual judgements

One of my former students, Tracy Jenkin, worked on the way novel knowledge is found and processed by organisations (her thesis here). As part of her work, she carried out an experiment comparing several different ways in which decisions are made about what novel ideas to pursue. One of the most interesting results was that an automated collaborative filtering-like tool ranked highly ideas that the group of humans, using a group decision making tool, had let drop off their radar. In other words, as they anonymously ranked and commented on ideas, and then had an open discussion about these ideas, they ‘forgot’ an idea that they had all considered to be of high quality. It wasn’t that they had second thoughts and discounted the idea as not as good as they had (all) initially thought — they just didn’t get around to revisiting it.

This suggests that automated tools for rating ideas might be an important supplement to group decision making. This applies especially to intelligence analysts who are almost always working with concepts that are novel, and where the evidence for the quality of each idea is nebulous or worse.

There’s a difficult tradeoff between the wisdom of crowds on the one hand, and groupthink (and the resulting blind spots) on the other. Adding an automated tool to group decision making may be a helpful way to add some objectivity into the mix without losing any of the benefits of the collective brainpower of a group of humans.


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