In “Blink: The Power of Thinking without Thinking” Malcolm Gladwell writes about how many of the choices that we make are made in an instant and often are better than the choices that we make after a great deal of reflection and study.
While he writes that some instantaneous decisions can be disastrous (such as the shooting of Amadou Diallo in 1999 by several policemen), the main interest in his book comes from those times that people make very quick decisions that turn out to be very good decisions.
One example he uses is about the decision of the Getty Museum to purchase a sixth century B.C. kouros (a sculpture). The decision was not made until a great deal of scientific study was done. However, a number of art historians and curators took one look at it and immediately thought that something was amiss. The kouros turned out to be a fake.
In litigation, perhaps the most crucial moment when fast decisions are called for is in the jury selection process. Often the decision about who to strike must be made in a matter of minutes or even seconds. What is often at war is the “gut” feeling of the attorney and the scientific data that have been collected, analyzed, and turned into a juror profile. Which is better: the “gut” feeling or the scientifically developed juror profile?
One important point that Gladwell makes is that decisions made in a “blink” are more likely to be good decisions when the decision-maker has a great deal of experience with and knowledge of the subject matter about which he or she is deciding (as in the psychologist John Gottman’s ability to predict the future success of a marriage after listening to only five minutes of conversation between a husband and wife).
There could be a huge range in the quality of the “gut” feeling of an attorney who has picked dozens of juries for the same type of case and the attorney who is doing this for the first time. Gladwell also points out that under certain circumstances the quality of a decision can be affected by having too much information.
I have often seen attorneys that get so caught up in the minutiae of a complex juror profile that they fail to pay attention to the gestalt–the whole–of the person being profiled. It must also be remembered that a juror profile is never one hundred percent valid. In fact, a very good profile is one that is good two-thirds of the time.
There are also differences between bad and good jury profiles. A bad profile will simply be a list of characteristics that have been shown to be statistically related to verdict predisposition (although there are powerful statistical models like logistic regression that can generate ideas about the predispositions of potential jurors).
A good jury profile is built on a theory of what will determine a verdict predisposition. Here you will have a sense of the type of person who will be predisposed to decide one way or another. It does not depend on discrete characteristics, but how those characteristics hold together to describe a person.
Indeed, it could be argued that it is extremely difficult to make a good jury selection decision using any method. As my colleague, Ross Laguzza, has pointed out, jury selection is about trying to predict the decision that will be made by an almost complete stranger at some distant point in the future–a task that would be difficult to do even with someone you know very well.
In the end, the best jury selection decision will be made by an experienced attorney who has internalized a good jury profile (that is, he or she believes it and intuitively understands it).
When we work with attorneys in the jury selection process, we make a point of telling them not to ignore their “gut” and to factor it into their actions. How much it should be factored in depends on the amount of experience the attorney has in selecting juries in the past and how successful that experience has been.
But, in the end, our clients are the ones who will be held responsible for the decisions they make.
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* Dr. Mausam (University of Washington) discusses the basic concepts for decision theory including the expected monetary value, regret, and expected value of perfect information. He ends with touching on the utility theory.
Grad Course in AI (#10): Decision Theory