Let’s get back to our story of Thomas Quick. Quick was sentenced for eight murders before he stopped cooperating in 2001. Without Quick’s confessions, there was little to do—remember, there was no hard evidence in any of the murder cases. It took almost ten years for the true story to unfold.
What had happened was that Thomas Quick was treated with a pseudoscientific version of psychotherapy back in the 1990s. The therapists managed to restore what they thought were recovered memories. (Note that the scientific support for such memories is weak at best.) The methods they used are almost identical to how you implant false memories. (See The Paradox of False Memories.) Quick also received heavy dozes of benzodiazepines, drugs that may make their users more suggestible.
The murder investigation started when the therapists told the police about Quick’s confessions. Convinced by the therapists’ authority that repressed memories were a valid scientific theory, the lead investigators started to interrogate Quick.
These interrogations were, well, peculiar. When Quick gave the wrong answers, he got help from the chief detective. After all, Quick was fighting with repressed memories and needed all the support he could get. Eventually, Quick got enough clues to the case that he could put together a coherent story. That was how he was convicted.
By now, you can probably see where the Thomas Quick story is heading. Do you recognize any social biases in it? To us in the software world, the most interesting aspects of this tragic story are in the periphery. Let’s look at them.
Once the Quick scandal with its false confessions was made public, many people started to speak up. These people, involved in the original police investigations, now told the press about the serious doubts they’d had from the very start. Yet few of them had spoken up ten years earlier, when Quick was originally convicted.
The social setting was ideal for pluralistic ignorance—particularly since the main prosecutor was a man of authority and was convinced of Quick’s guilt. He frequently expressed that opinion and contributed to the groupthink.
From what you now know about social biases, it’s no wonder that a lot of smart people decided to keep their opinions to themselves and play along. Luckily, you’ve also got some ideas for how you can avoid having similar situations unfold in your own teams. Let’s add one more item to that list by discussing a popular method that often does more harm than good—brainstorming.
If you want to watch process loss in full bloom, check out any brainstorming session. It’s like a best-of collection of social and cognitive biases. That said, you can be productive with brainstorming, but you need to change the format drastically. Here’s why and how.
The original purpose of brainstorming was to facilitate creative thinking. The premise is that a group can generate more ideas than its individuals can on their own. Unfortunately, research on the topic doesn’t support that claim. On the contrary, research has found that brainstorming produces fewer ideas than expected and that the quality of the produced ideas may suffer as well.
The are several reasons for the dramatic process loss. For example, in brainstorming we’re told not to criticize ideas. In reality, everyone knows they’re being evaluated anyway, and they behave accordingly. Further, the format of brainstorming allows only one person at a time to speak. That makes it hard to follow up on ideas, since we need to wait for our time to talk. In the meantime, it’s easy to be distracted by other ideas and discussions.
To reduce the process loss, you need to move away from the traditional brainstorming format. Studies suggest that a well-trained group leader may help you eliminate process loss. Another promising alternative is to move to computers instead of face-to-face communication. In that setting, where social biases are minimized, electronic brainstorming may actually deliver on its promise. (See Idea Generation in Computer-Based Groups: A New Ending to an Old Story [VDC94] for a good overview of the research.)
Now you know what to avoid and watch out for. Before we move on, take a look at some more tools you can use to reduce bias.