Nick Chater is the author of The Mind is Flat–the Remarkable Shallowness of the Improvising Brain, Yale University Press, New Haven, 2019. He is a professor of behavioral science at the Warwick Business School. The book is two parts and overall it is as ambitious as it is simple. The first part is the most convincing. He shows how misguided we are on our perceptions, emotions, and decision making. Our vision seems to provide us with a full fledged model of our environment, when we really only can focus on a very small area with our furtive eye movements providing the impression of a complete detailed picture. Our emotions do not well up from deep inside, but are the results of in-the-moment interpretations based on the situation we are in, and highly ambiguous evidence from our own bodily state. Chater sees our beliefs, desires, and hopes as just as much inventions as our favorite fictional characters. Introspection does not work, because there is nothing to look at. We are imaginative creatures with minds that pretty much do everything on the fly. We improvise so our decision making is inconsistent as are our preferences.
This post is based on the book, Elastic–Flexible Thinking in a Time of Change by Leonard Mlodinow, Pantheon Books, New York, 2018. Mlodinow is a physicist and worked with Stephen Hawking. His previous book Subliminal evidently gave him considerable access to interesting people like Seth MacFarlane. He mentions that Stephen Hawking’s pace of communicating was at best six words a minute with public presentations being done ahead of time. Mlodinow notes that this slowing of the pace of a conversation is actually quite helpful in forcing you to consider the words as opposed to thinking of what you are going to say while the other person is talking so that you can have an instant response.
This post is inspired by The Attention Merchants, Tim Wu, Vintage Books, 2017, New York. Decision making is not a front line issue in the book, but it is also clear that we cannot control our decision making if we cannot control our attention. The book begins as a history of what has grabbed our attention from newspapers and posters to radio to television to computers and video games, to the internet and its vehicles including our present attention grabber, the cell phone. Of course, each attention platform has ultimately had to make money and advertising has been the dominant path chosen. Advertising is the villain only to the extent that it puts able resources into effectively capturing our attention. But we do not check our email so often or play video games so long due to advertising. There is definitely some behavioral conditioning going on. Wu mentions that video games can even: “induce a ‘flow state’, that form of contentment, of optimal experience, described by the cognitive scientist Mihaly Csikszentimihalyi, in which people feel ‘strong, alert, if effortless control, unselfconscious, and at the peak of their abilities.”
Why do almost all people tell the truth in ordinary everyday
life? […] The reason is, firstly because it is easier; for
lying demands invention, dissimulation, and a good memory
(Friedrich Nietzsche, page 54, Human, All Too Human: A Book for Free Spirits, 1878)
This post is based on the paper: ” ‘ I can see it in your eyes’: Biased Processing and Increased Arousal in Dishonest Responses,” authored by Guy Hochman, Andreas Glockner, Susan Fiedler, and Shahar Ayal, that appeared in the Journal of Behavioral Decision Making, December 2015.
This post is based on a paper by Andy Clark: “Embodied Prediction,” in T. Metzinger & J. M. Windt (Eds). Open MIND: 7(T). Frankfurt am Main: MIND Group (2015). Andy Clark is a philosopher at the University of Edinburgh whose tastes trend toward the wild shirt. He is a very well educated philosopher in the brain sciences and a good teacher. The paper seems to put forward some major ideas for decision making even though that is not its focus. Hammond’s idea of the Cognitive Continuum is well accommodated. It also seems quite compatible with Parallel Constraint Satisfaction, but leaves room for Fast and Frugal Heuristics. It seems to provide a way to merge Parallel Constraint Satisfaction and Cognitive Niches. I do not really understand PCS well enough, but it seems potentially to add hierarchy to PCS and make it into a generative model that can introduce fresh constraint satisfaction variables and constraints as new components. If you have not read the post Prediction Machine, you should because the current post skips much background. It is also difficult to distinguish Embodied Prediction and Grounded Cognition. There are likely to be posts that follow on the same general topic.
This post is derived from “Chapter 5, Multiple Measure Strategy Classification-Outcomes, Decision Times, and Confidence Ratings” authored by Andreas Glockner from Foundations for Tracing Intuition– Challenges and Methods, edited by Andreas Glockner and Cilia Witteman 2010 Psychology Press NY. It shines a little light on how intuition experiments seeking to answer if a person is using a Take the Best strategy or a Parallel Constraint Satisfaction strategy, etc are actually done. It is written more understandably than a typical paper for a journal. It will hopefully give more meaning to the letters MM-ML.
I occasionally like to go far afield from judgment and decision making, and here I go again. This post takes a look at Michio Kaku’s 2014 book, The Future of the Mind–The Scientific Quest To Understand, Enhance, And Empower The Mind, Doubleday, New York.
Decision models can sometimes seem very explanatory, but they seem so simple minded when I read in Kaku’s book that we have two separate centers of consciousness and that we may all have photographic memories.
Recognition as a memory-based process
While acknowledging that recognition should generally be treated as a continuous variable, Goldstein and Gigerenzer focused on the outcome of this recognition process, which is either “recognized” or “not recognized” with only a small and negligible gray zone of uncertainty in between. Accordingly, the quality of these subjective recognition judgments, that is, whether
they were true or not or with what confidence, was originally not considered. Meanwhile, some researchers have asked whether and how the recognition process itself possibly affects subsequent inferences.
This post and the next post are based on Rudiger Pohl’s article, “On the Use of Recognition in Inferential Decision Making” that appeared in the Journal of Judgment and Decision Making in 2011. The Journal had three issues devoted to recognition. Pohl provides the best summary and is also the last. I found that some of the articles with two or three authors trying to come up with a summary failed apparently because there was so much disagreement among the authors.
“Intuition is nothing more or less than recognition.” Daniel Kahneman delivers this and credits Simon in Thinking Fast and Thinking Slow. Pohl’s article does not address this statement, but it helps me address it. Maybe the statement is not making intuition simpler, but making recognition much more complicated.
This post is based on the paper presented at the 2013 Annual Conference of the of the Cognitive Science Society, “Justified True Belief Triggers False Recall of “Knowing”” by Derek Powell, Zachary Horne, Angel Pinillos, and Keith J. Holyoak. People’s beliefs are the primary drivers of their actions, yet these beliefs are often uncertain—the products of limited information about the world and interconnections between other (often uncertain) beliefs.