This book, Nervous States – Democracy and the Decline of Reason, 2019, written by William Davies tries to explain the state we are in. The end of truth or the domination of feelings or the end of expertise all come to mind. People perceive that change is so fast that the slow knowledge developed by reason and learning is devalued, while instant knowledge that will be worthless tomorrow like that used by commodity, bond or stock trading networks is highly valued. Davies builds on Hayek and says many things that ring true. In three posts, I will present the main points of Davies’ book, argue with some of the points, and present what Davies says we can do about it. Devaluing reason is a big deal for decision making.
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.”
In Confidence, Part II, the authors conclude that confidence is computed continuously, online, throughout the decision making process, thus lending support to models of the mind as a device that computes with probabilistic estimates and probability distributions.
The Embodied Mind
One such explanation is that of predictive processing/embodied mind. Andy Clark, Jacob Hohwy, and Karl Friston have all helped to weave together this concept. Our minds are blends of top down and bottom up processing where error messages and the effort to fix those errors makes it possible for us to engage the world. According to the embodied mind model, our minds do not just reside in our heads. Our bodies determine how we interact with the world and how we shape our world so that we can predict better. Our evolutionary limitations have much to do with how our minds work. One example provided by Andy Clark and Barbara is a robot without any brain imitating human walking nearly perfectly (video go to 2:40). Now how does this tie into confidence? Confidence at a conscious level is the extent of our belief that our decisions are correct. But the same thing is going on as a fundamental part of perception and action. Estimating the certainty of our own prediction error signals of our own mental states and processes is as Clark notes: “clearly a delicate and tricky business. For it is the prediction error signal that…gets to ‘carry the news’.”
Now the confidence heuristic is not the only thing Trump takes advantage of, but we will leave those for another time. I will also avoid the question of whether or not Trump is actually confident. So what is the relationship of confidence and decision making? Daniel Kahneman in Thinking, Fast and Slow on page 13 describes:
a puzzling limitation of our mind: our excessive confidence in what we believe we know, and our apparent inability to acknowledge the full extent of our ignorance and the uncertainty of the world we live in. We are prone to overestimate how much we understand about the world and to underestimate the role of chance in events. Overconfidence is fed by the illusory certainty of hindsight.
I discovered that I was a celiac a few months ago and accordingly I am on a gluten free diet. Compared to most conditions discovered in one’s late sixties, celiac disease seems almost inconsequential. However, it fits into the idea of prediction error minimization. In effect, the environment has changed and I need to change my predictions. Bread and beer are now bad. My automatic, intuitive prediction machine has not been getting it right. It is disorienting. I can no longer “See food, eat food.” I can change the environment at home, but in the wider world I need to be aware. My brain needs to dedicate perpetual, and at least for now, conscious effort to this cause. It is almost as if I became instantly even dumber. It makes me more self absorbed in social settings that involve food. Not known for my social skills, I have been a good listener, but now not so much. On my Dad’s 94th birthday, I ate a big piece of German chocolate cake, enjoyed it thoroughly, and then remembered that it was not allowed. In my particular case, I do not get sick or nauseated when I make such a mistake so my commitment is always under threat. This demands an even larger share of my brain to be compliant. My main incentive to comply is those photos of my scalloped small intestine. I note that I was diagnosed after years of trying to figure out my low ferritin levels. (It will be extremely disappointing if I find that my ferritin is still low.) Continue reading
This post is derived from a review article: “The Role of Intuition in the Generation and Evaluation Stages of Creativity,” authored by Judit Pétervári, Magda Osman and Joydeep Bhattacharya that appeared in Frontiers of Psychology, September 2016 doi: 10.3389/fpsyg.2016.01420. It struck me that in all this blog’s posts, creativity had almost never come up. Then I threw it together with Edward O Wilson’s 2017 book: The Origins of Creativity, Liveright Publishing, New York. (See posts Evolution for Everyone and Cultural Evolution for more from Edward O. Wilson. He is the ant guy. He is interesting, understandable, and forthright.)
Creativity is notoriously difficult to capture by a single definition. Petervari et al suggest that creativity is a process that is broadly similar to problem solving, in which, for both, information is coordinated toward reaching a specific goal, and the information is organized in a novel, unexpected way. Problems which require creative solutions are ill-defined, primarily because there are multiple hypothetical solutions that would satisfy the goals. Wilson sees creativity beyond typical problem solving.
This post is based on selections from: “Kenneth R. Hammond’s contributions to the study of judgment and decision making,” written by Mandeep K. Dhami and Jeryl L. Mumpower that appeared in Judgment and Decision Making, Vol. 13, No. 1, January 2018, pp. 1–22. I am going to become more familiar with the work of the authors since they clearly share my admiration for Hammond and were his colleagues. They also understand better than I how he fit into the discipline of judgment and decision making (The links take you to past Posts.). I merely cherry pick my opinion of his most significant contributions.
As a student of Egon Brunswik, Hammond advanced Brunswik’s theory of probabilistic functionalism and the idea of representative design. Hammond pioneered the use of Brunswik’s lens model as a framework for studying how individuals use information from the task environment to make judgments. Hammond introduced the lens model equation to the study of judgment processes, and used this to measure the utility of different forms of feedback in multiple-cue probability learning.
Hammond proposed cognitive continuum theory which states that quasirationality is an important middle-ground between intuition and analysis and that cognitive performance is dictated by the match between task properties and mode of cognition. Intuition (often also referred to as System 1, experiential, heuristic, and associative thinking) is generally considered to be an unconscious, implicit, automatic, holistic, fast process, with great capacity, requiring little cognitive effort. By contrast, analysis (often also referred to as System 2, rational, and rule-based thinking) is generally characterized as a conscious, explicit, controlled, deliberative, slow process that has limited capacity and is cognitively demanding. For Hammond, quasirationality is distinct from rationality. It comprises different combinations of intuition and analysis, and so may sometimes lie closer to the intuitive end of the cognitive continuum and at other times closer to the analytic end. Brunswik pointed to the adaptive nature of perception (and cognition). Dhami and Mumpower suggest that for Hammond, modes of cognition are determined by properties of the task (and/or expertise with the task). Task properties include, for example, the amount of information, its degree of redundancy, format, and order of presentation, as well as the decision maker’s familiarity with the task, opportunity for feedback, and extent of time pressure. The cognitive mode induced will depend on the number, nature and degree of task properties present.
Movement along the cognitive continuum is characterized as oscillatory or alternating, thus allowing different forms of compromise between intuition and analysis. Success on a task inhibits movement along the cognitive continuum (or change in cognitive mode) while failure stimulates it. In my opinion, Glöckner and his colleagues have built upon Hammond’s work. Parallel constraint satisfaction theory suggests that intuition and analysis operate in an integrative fashion and in concert with Hammond’s idea of oscillation between the two. Glockner suggests that intuition makes the decisions through an iterative lens model type process, but sends analysis out for more information when there is no clear winner.
Hammond returned to the themes of analysis and intuition and the cognitive continuum in his last book entitled Beyond Rationality: The Search for Wisdom in a Troubled Time, published at age 92 in 2007. This is a frank look at the world that pulls few punches. At the heart of his argument is the proposition that the key to wisdom lies in being able to match modes of cognition to properties of the task.
In 1996, Hammond published a book entitled Human Judgment and Social Policy: Irreducible Uncertainty, Inevitable Error, Unavoidable Injustice which attempted to understand the policy formation process. The book emphasized two key themes. The first theme was whether our decision making should be judged on coherence competence or on correspondence competence. The issue, according to Hammond, was whether in a policy context, it was more important to be rational (internally and logically consistent) or to be empirically accurate. Analysis is best judged with coherence, while intuition is best judged by accuracy. To achieve balance–quasirationality and eventually wisdom, the key lies in how we think about error, which was the second theme. Hammond emphasized the duality of error. Brunswik demonstrated that the error distributions for intuitive and analytical processes were quite different. Intuitive processes led to distributions in which there were few precisely correct responses but also few large errors, whereas with analysis there were often many precisely correct responses but occasional large errors. According to Hammond, duality of error inevitably occurs whenever decisions must be made in the face of irreducible uncertainty, or uncertainty that cannot be reduced at the moment action is required. Thus, there are two potential mistakes that may arise — false positives (Type I errors) and false negatives (Type II errors)—whenever policy decisions involve dichotomous choices, such as whether to admit or reject college applications, claims for welfare benefits, and so on. Hammond argued that any policy problem involving irreducible uncertainty has the potential for dual error, and consequently unavoidable injustice in which mistakes are made that favor one group over another. He identified two tools of particular value for analyzing policy making in the face of irreducible environmental uncertainty and duality of error. These were Signal Detection Theory and the Taylor-Russell paradigm. These concepts also applicable to best designing airplane instruments (See post Technology and the Ecological Hybrid.).
Although I have had much respect for Dan Kahan’s work, I have had a little trouble with the Identity protective Cognition Thesis (ICT). The portion in bold in the quote below from “Motivated Numeracy and Enlightened Self-Government” has never rung true.
On matters like climate change, nuclear waste disposal, the financing of economic stimulus programs, and the like, an ordinary citizen pays no price for forming a perception of fact that is contrary to the best available empirical evidence: That individual’s personal beliefs and related actions—as consumer, voter, or public discussant—are too inconsequential to affect the level of risk he or anyone else faces or the outcome of any public policy debate. However, if he gets the ‘wrong answer” in relation to the one that is expected of members of his affinity group, the impact could be devastating: the loss of trust among peers, stigmatization within his community, and even the loss of economic opportunities.
Why should Thanksgiving be so painful if it were true? I do not even know what my friends think of these things. Now at some point issues like climate change become so politically tainted that you may avoid talking about them to not antagonize your friends, but that does not change my view. But now Kahan has a better explanation.
This post is based on a paper: “Learning from experience in nonlinear environments: Evidence from a competition scenario,” authored by Emre Soyer and Robin M. Hogarth, Cognitive Psychology 81 (2015) 48-73. It is not a new topic, but adds to the evidence of our nonlinear shortcomings.
In 1980, Brehmer questioned whether people can learn from experience – more specifically, whether they can learn to make appropriate inferential judgments in probabilistic environments outside the psychological laboratory. His assessment was quite pessimistic. Other scholars have also highlighted difficulties in learning from experience. Klayman, for example, pointed out that in naturally occurring environments, feedback can be scarce, subject to distortion, and biased by lack of appropriate comparative data. Hogarth asked when experience-based judgments are accurate and introduced the concepts of kind and wicked learning environments (see post Learning, Feedback, and Intuition). In kind learning environments, people receive plentiful, accurate feedback on their judgments; but in wicked learning environments they don’t. Thus, Hogarth argued, a kind learning environment is a necessary condition for learning from experience whereas wicked learning environments lead to error. This paper explores the boundary conditions of learning to make inferential judgments from experience in kind environments. Such learning depends on both identifying relevant information and aggregating information appropriately. Moreover, for many tasks in the naturally occurring environment, people have prior beliefs about cues and how they should be aggregated.
This post is based on a paper: “Intuition and analytic processes in probabilistic reasoning: The role of time pressure,” authored by Sarah Furlan, Franca Agnoli, and Valerie F. Reyna. Valerie Reyna is, of course, the primary creator of fuzzy-trace theory. Reyna’s papers tend to do a good job of summing up the state of the decision making art and fitting in her ideas.
The authors note that although there are many points of disagreement, theorists generally agree that there are heuristic processes (Type 1) that are fast, automatic, unconscious, and require low effort. Many adult judgment biases are considered a consequence of these fast heuristic responses, also called default responses, because they are the first responses that come to mind. Type 1 processes are a central feature of intuitive thinking, requiring little cognitive effort or control. In contrast, analytic (Type 2) processes are considered slow, conscious, deliberate, and effortful, and they place demands on central working memory resources. Furlan, Agnoli, and Reyna assert that Type 2 processes are thought to be related to individual differences in cognitive capacity and Type 1 processes are thought to be independent of cognitive ability, a position challenged by the research presented in their paper. I was surprised by the given that intuitive abilities were unrelated to overall intelligence and cognitive abilities as set up by typical dual process theories.