Writing an honest and informative biosketch.
Posted Oct 02, 2020
A few months ago, I was invited to participate on a panel to describe the Artificial Intelligence Quotient (AIQ) toolkit. The overall theme of the meeting centered on Artificial Intelligence and computer science, and most of the audience members were specialists in these areas. Some also had backgrounds in neuroscience.
In preparing materials to promote this meeting, I was asked to submit a biosketch and I came up with the following.
Gary Klein, Ph.D., is a cognitive psychologist who helped to initiate the Naturalistic Decision-Making movement in 1989. His Recognition-Primed Decision (RPD) model has been tested and replicated several times. He also developed a Data/Frame model of sensemaking and a Triple-Path model of insight. His work relies on Cognitive Task Analysis methods, primarily the Critical Decision method that he and his colleagues developed in 1985. In addition, he has formulated the Pre-Mortem method for identifying risks, and the ShadowBox method for training cognitive skills. The 5 books he has authored and the 3 he has co-edited have sold over 100,000 copies. He founded Klein Associates, Inc. in 1977 and when it grew to 37 employees he sold it to Applied Research Associates in 2005. He started his new company, ShadowBox LLC, in 2014.
However, as I was editing this biosketch, I realized that it was deceptive. It described what I had done in the past, but it failed to mention my limitations—and these limitations mattered here because the audience was likely to make erroneous assumptions about me simply because of the nature of the meeting—computer science and artificial intelligence—and the fact that I was an invited panelist.
So I wrote a parallel biosketch that was much more honest and, I think, would have been much more useful:
Gary Klein, Ph.D., is a cognitive psychologist with minimal technical background in computer science or Artificial Intelligence or mathematical psychology. He cannot program. He is unfamiliar with the analytical methods and algorithmic techniques essential for most Machine Learning or Deep Neural Net systems such as Convolutional Neural Nets or Recurrent Neural Nets. He has a minimal grasp of Bayesian statistics. When he encounters concepts such as back-propagation his immediate response is to consult Wikipedia. His knowledge of statistical methods pretty much ended with the granting of his Ph.D. in 1969. Although he received a M.S. in physiological psychology in 1968, he has failed to keep up with the field of neuroscience.
Needless to say, I did not send in this alternative version. However, this anti-biosketch does illustrate the value of explaining what we don’t know and what we can’t do. It illustrates how to counter incorrect assumptions that others might make. We don't have to expose every fault that we have, but we have some obligation to prevent misunderstandings. For common ground, and for coordination, it is important to give a clear picture of our limitations as well as our strengths. Perhaps we can start with more candid biosketches.
Even if we don't publicize these anti-biosketches, they are kind of fun to write.