Category Archives: Evaluation/Accuracy/Achievement

People Say/ Everyone Knows/ They Say

This post is sooo… derivative, but I cannot help myself. Good judgment is dependent on good information. It has never been so obvious how much we rely on good referees to determine what is good information. Most persuasion is based on filtering the information to the persuader’s advantage, but it has been rare in my lifetime to use the strategy of just hammering the lie.

It is easy to imagine that our paleo brains were rewarded by believing the chief. We both had skin in the game. So our still tribal brains believe things that are repeated over and over, even lies. Unfortunately, our information sources have gotten further and further from us so that our futures are not intertwined, except in an existential way. Our information networks have expanded and more critically selectively expanded.

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The Myth of Experience

Emre Soyer and Robin Hogarth have written a new book, The Myth of Experience.  Why We Learn the Wrong Lessons, and Ways to Correct Them. This book is aimed at a general audience although it has copious and detailed notes and an index that will allow for deeper looks. I have much respect for their past work both individually and together.

The key idea that they have developed elsewhere is that some learning environments are kind so that what you learn by experience is helpful–say riding a bike– while other environments are wicked and experience cannot be relied upon to make good decisions. Robin Hogarth’s Educating Intuition develops this (See posts: What has Brunswik’s Lens Model Taught? ‘  , Kind and Wicked Learning Environments)

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Coronavirus Math

Early 2020 is a truly Interesting time for decision making. We have learned what an inexact science risk communication is and had Robin Hogarth’s statement reemphasized:

“Human achievement is lower when there are nonlinearities in the ecology.” (What has Brunswik’s Lens Model Taught?).

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The Mind is Flat

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.

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Elastic

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.

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AI–Building a Mind is Hard

This post is inspired by the book:  Rebooting AI – Building Artificial Intelligence We Can Trust, written by Gary Marcus and Ernest Davis, New York, 2019. Gary Marcus (see post Kluge) is a well known author and artificial intelligence entrepreneur and Ernest Davis is a professor of computer science at Carnegie Mellon. To oversimplify, the authors emphasize that the successes of AI are narrow and tend to be greedy, opaque, and brittle. They provide history of AI seemingly about being ready for prime time decade after decade after decade. Self driving cars are almost there, but they are not. Human frailties in driving result in a death about every 100,000,000 miles driven, but Marcus and Davis indicate that self driving cars require human intervention every 10,000 miles which is 10,000 times in 100,000,000 miles. It may be a very long time before we are ready to sign off on self-driving cars, because the progress thus far has been the easy part.

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Taming Uncertainty

Taming Uncertainty  by Ralph Hertwig (See posts Dialectical Bootstrapping and Harnessing the Inner Crowd.), Timothy J Pleskac (See post Risk Reward Heuristic.), Thorsten Pachur (See post Emotion and Risky Choice.) and the Center for Adaptive Rationality, MIT Press, 2019, is a new compendium that I found accidentally in a public library. There is plenty of interesting reading in the book. It takes the adaptive toolbox approach as opposed to the Swiss Army Knife . The book gets back cover raves from Cass Sunstein (See posts Going to Extremes, Confidence, Part 1.), Nick Chater, and Gerd Gigerenzer (See post Gigerenzer–Risk Saavy, and others.). I like the pieces, but not the whole.

 

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Nervous States- Democracy and the Decline of Reason

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.

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Confidence, Part III

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 Webb 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’.”

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Confidence, Part I

Confidence is defined as our degree of belief that a certain thought or action is correct. There is confidence in your own individual decisions or perceptions and then the between person confidence where you defer your own decision making to someone else.

Why am I thinking of confidence? An article by Cass Sunstein explains it well. The article appeared in Bloomberg, Politics & Policy, October 18, 2018, Bloomberg Opinion, “Donald Trump is Amazing. Here’s the Science to Prove It.”

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