This post is a continuation of the theme of when decisions are made and how we delay or wait or decide not to decide. This post is based on a 2014 paper by Teichert, Ferrera, and Grinband, “Humans Optimize Decision-Making by Delaying Decision Onset,” in PLoS ONE. Again, this paper is beyond my understanding at least as to the details. It has some excellent figures and graphics that are pretty, but I do not think that I really understand them. These are my shortcomings. What interests me about this is the contrast with my previous post Deciding not to Decide. This paper examines decision onset and nondecision time while “Deciding not to Decide” suggested an explicit decision to inhibit the decision. I find making an inhibitory decision a more satisfying explanation than delaying decision onset, although they could be the same thing or the situations may be so different that there is no real comparison.
This post is an executive summary of a 2013 paper about deciding not to decide. (“Deciding Not to Decide: Computational and Neural Evidence for Hidden Behavior in Sequential Choice,” by Sebastian Gluth, Jorg Rieskamp, and Christian Buchel, that appeared in PLoS Comput Bio 9(10). Quite frankly the detail of the paper is beyond me, but the general ideas are interesting.
Many decisions are not triggered by a single event but based on multiple sources of information. When purchasing a new computer, for instance, we certainly look at the price, but not without accounting for further aspects like capabilities, quality and appearance. According to Gluth et al, usually, these multi-attribute decisions evolve sequentially, that is, as long as the collected evidence is insufficient to motivate a particular choice we search for more information to resolve our uncertainty. Importantly, such ‘‘decisions not to decide’’ are not directly observable but can promote significant changes in behavior.
David Brooks has a way of irritating me. For some reason, he seems like a very serious person so I cannot dismiss him out of hand. But, on June 16, 2014, he wrote “The Structures of Growth—Learning is no Easy Task,” in the New York Times, about certain human activities having logarithmic learning functions and others as having exponential functions. I realize that I am envious of his being able to push such sloppy work out the door to millions of readers. It is just a column, but read it for yourself.
His basis was a blog by Scott H. Young in early 2013, who as far as I can tell made much less outlandish representations about learning or domains of growth. Young explains that anything that you try to improve will have a growth curve, and that it is a mistake to assume that it will be linear. Young says that athletic performance, productivity, and mastery of a complex skill tend to be logarithmic. Early progress on logarithmic growth activities can make you overconfident if you do not realize that the curve will soon flatten. He notes that exponential functions tend to be limited to ranges and apply to technological improvement, business growth, wealth, and rewards to talent.
Continuing on the delay theme, this post is based on the paper: “Delay, Doubt, and Decision: How Delaying a Choice Reduces the Appeal of (Descriptively) Normative Options” written by Niels Van de Ven, Thomas Gilovich, and Marcel Zeelenberg, that appeared in Psychological Science in 2010.
The authors examined whether choosing to delay making a choice between a focal option and an alternative tends to make people subsequently less likely to choose what they would otherwise have chosen. They based their efforts on a regularity in elections in the United States that is known as the incumbent rule. It refers to the fact that undecided voters who end up casting ballots tend to vote against the incumbent. One analysis found that in 127 of 155 national, state,
and municipal elections, the majority of undecided voters went for the challenger. This may seem a little odd since decision researchers have documented a status quo bias in people’s
choices—a bias to stick with the status quo option rather than try something new. So why do undecided voters not favor the incumbent? Van de Ven et al contend that undecided voters
interpret the fact that they have yet to decide as information that calls into question the wisdom of picking the incumbent. Given that the incumbent is typically the more psychologically prominent candidate, and that people know they often follow an “if it ain’t broke, don’t fix it” rule, they may wonder why they have not already resolved to vote for the incumbent. In other words, they propose that the experience of doubt is experienced as doubt about the incumbent.
As you get older even those of us not labeled as procrastinators realize that some decisions never have to be made. You can wait a little bit and it becomes irrelevant or the decision becomes obvious. Using my adaptation of the parallel constraint satisfaction model, your intuitive processing often does not come up with a clear cut answer and sends the analytic system out for more information. This is a common point for us to insert delay if we can. Other times we make a decision and then get an opportunity to change it without any real penalty. Frank Partnoy’s book Wait- The Art and Science of Delay examines the overall issue mostly with a series of anecdotes. The book provides some insights.
This post is based on, “A spiral model of musical decision-making,” written by Daniel Bangert, Emery Schubert and Dorottya Fabian that appeared in Frontiers of Psychology on April 22, 2014. Although based on thin research, my intuition likes it, and it would seem to have applicability beyond music. It splices together ideas of Ken Hammond (post Cognitive Continuum), Jonathan Evans (post Dual Process Theories of Cognition), and Amy Baylor (post U-Shaped Intuition).
Research has shed light on how both intuition and deliberation are used by musicians. Bangert et. al. refer to Hallam who interviewed twenty-two performers about their practice habits and found differences between those who were “intuitive/serialists” who allowed their interpretation to evolve unconsciously versus “analytic/holists.” who relied on deliberate, conscious analysis of the piece. Other research has shown that while performing, musicians pay deliberate attention to certain specific musical aspects (performance cues) and also have spontaneous performance thoughts.
This post is based on a paper by Amy L Baylor, “A U-Shaped Model for the Development of Intuition by Expertise.” that appeared in New Ideas in Psychology, in 2001. I am bringing her ideas up now, because they are important for my next post. Although today intuition seems to have become unconscious thinking, Baylor saw it as closer to insight–far more special– in this paper. I notice this more because, I just finished reading Seeing What Others Don’t by Gary Klein which is about insight. Baylor’s questions are: Does a more naive view of a field lead to greater new insights? Or does expertise facilitate one’s capability for intuition in a given field? How can both of these positions be reconciled? It is interesting also that Baylor’s references do not duplicate authors that I have seen before.