Emotions impact decision making. Normative decision making models struggle to internalize this impact. Resentment, grievance, and bitterness are similar to each other, but different enough for me to include them all. They are low grade long term emotions that seem dysfunctional for those who carry them, but maybe functional at some level to encourage us to treat others better.
According to Wikipedia resentment is a complex, multilayered emotion that has been described as a mixture of disappointment, disgust, anger, and fear. You can feel resentment directly toward a person or group for how they mistreated you or you can feel resentment toward a person or group because they have been treated better by others or seem better in some way than you. Grievance somehow seems more specific, while bitterness seems more general and resigned. Resentment is anger’s passive aggressive brother.
In 2022, resentment seems to be driving all sorts of decision making all over the world. Vladimir Putin declares war on Ukraine. Millions of people suddenly do not want to get vaccinated and millions of others believe an election was stolen without evidence.
This is the third and final post looking at William Davies book Nervous States–Democracy and the Decline of Reason. Davies provides some ideas for getting out of this mess at the end of the book. I believe that they are well thought out. First, Davies notes that there is one problem confronting humanity that may never go away, and which computers do nothing to alleviate: how to make promises. A promise made to a child or a public audience has a binding power. It can be broken, but the breaking of it is a breach that can leave deep emotional and cultural wounds. Davies states:
“Whether we like it or not, the starting point for this venture will be the same as it was for Hobbes: the modern state, issuing laws backed by sovereign power. It is difficult to conceive how promises can be made at scale, in a complex modern society, without the use of contracts, rights and statutes underpinned by sovereign law. Only law really has the ability to push back against the rapidly rising tide of digital algorithmic power. It remains possible to make legal demands on the owners and controllers of machines, regardless of how sophisticated those machines are.”
This is the second of three posts discussing William Davies’ book Nervous States–Democracy and the Decline of Reason. I pick a couple of areas to argue with some of the scenarios Davies presents.
Markets and Evolution
Davies discusses Hayek as the guy who believes in free markets above all else, and who has helped us reach this point of not agreeing on reality. When I read Hayek (The Road to Serfdom), he said to me that free markets with the right stable rules in place are the best system for everyone. Unfortunately, determining the right stable rules is difficult and the job of government. Hayek seems to have taken Adam Smith’s invisible hand and run with it. David Sloan Wilson in This View of Life- Completing the Darwinian Revolution makes clear that the invisible hand only works at one scale of a market (see posts Evolution for Everyone and Multilevel Selection Theory).
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 based on a paper written by Andy Clark, author of Surfing Uncertainty (See Paper Predictive Processing for a fuller treatment.), “A nice surprise? Predictive processing and the active pursuit of novelty,” that appeared in Phenomenology and the Cognitive Sciences, pp. 1-14. DOI: 10.1007/s11097-017-9525-z. For me this is a chance to learn how Andy Clark has polished up his arguments since his book. It also strikes me as connected to my recent posts on Curiosity and Creativity.
Clark and Friston (See post The Prediction Machine) depict human brains as devices that minimize prediction error signals: signals that encode the difference between actual and expected sensory simulations. But we know that we are attracted to the unexpected. We humans often seem to actively seek out surprising events, deliberately seeking novel and exciting streams of sensory stimulation. So how does that square with the idea of minimizing prediction error.
This post is based on the paper: “The role of interoceptive inference in theory of mind,” by
Sasha Ondobaka, James Kilner, and Karl Friston, Brain Cognition, 2017 Mar; 112: 64–68.
Understanding or inferring the intentions, feelings and beliefs of others is a hallmark of human social cognition often referred to as having a Theory of Mind. ToM has been described as a cognitive ability to infer the intentions and beliefs of others, through processing of their physical appearance, clothes, bodily and facial expressions. Of course, the repertoire of hypotheses of our ToM is borrowed from the hypotheses that cause our own behavior.
But how can processing of internal visceral/autonomic information (interoception) contribute to the understanding of others’ intentions? The authors consider interoceptive inference as a special case of active inference. Friston (see post Prediction Error Minimization) has theorized that the goal of the brain is to minimize prediction error and that this can be achieved both by changing predictions to match the observed data and, via action, changing the sensory input to match predictions. When you drop the knife and then catch it with the other hand, you are using active inference.
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 the paper: “Cultural differences are not always reducible to individual differences,” written by Jinkyung Na, Igor Grossmann, Michael E. W. Varnum, Shinobu Kitayama, Richard Gonzalez, and Richard E. Nisbett p 6192-6197 | PNAS | April 6, 2010 | vol.107.
As people, I think that we want to believe that cultural differences can be reduced to individual differences. But is it actually true? The authors studied whether or not cultural constructs can be conceptualized as psychological traits at the individual level.
According to the authors, cultural psychology has placed a heavy emphasis on two constructs: social orientation and cognitive style. These two constructs seem applicable to decision making and make me want to apply them when there are international negotiations going on. Some cultures, such as the United States, are characterized by a social orientation valuing independence: emphasizing uniqueness, having relatively low sensitivity to social cues, and encouraging behaviors that affirm autonomy. In contrast, other cultures including China, Japan, and Korea tend to value interdependence: emphasizing harmonious relations with others, promoting sensitivity to social cues, and encouraging behaviors that affirm relatedness to others. Similarly, cultures have been shown to vary along the analytic holistic dimension in cognitive style. Some cultures are analytic: detaching a focal object from the perceptual field, categorizing objects taxonomically, and ascribing causality to focal actors or objects. Other cultures are holistic: paying attention to the entire perceptual field, especially relations among objects and events, categorizing objects on the basis of their thematic relations, and attributing causality to context.
This post is based on a paper, “Cross Cultural Differences in Decisions from Experience: Evidence from Denmark, Israel, and Taiwan,” authored by Sibilla Di Guida, Ido Erev, and David Marchiori. It is a 2015 working paper of ECARES. It immediately reminded me Richard Nisbett’s Geography of Thought.
Richard Nisbett in Geography of Thought provides interesting insights into such differences. He divides the world into Easterners and Westerners. Easterners have difficulty in recognizing changes in objects, while Westerners cannot recognize changes in backgrounds. Easterners believe that the world is complicated and inscrutable. Westerners believe that they can understand the world. Westerners create simple and useful models that can be tested, but tend to focus on the object and slight the possible role of context. Westerners are particularly susceptible to the fundamental attribution error–thinking other people’s actions are explained by what they are, while my actions are explained by circumstances. The table below sets out some more distinctions.
object oriented, interventionist-surgery
more engineers/less lawyers
more lawyers/less engineers
avoid conflict–meetings ratify consensus
attempt persuasion, faith in free market of ideas
Japan 2 Nobel prizes in 90s
US 44 Nobel prizes in 90s
Tentative agreed upon guides for future-changeable
Fixed-deal is a deal
ambiguity of causality so that they insist on apology even if seems to be their fault
This is the final of three posts on this subject. It reflects the work of Jakob Hohwy as referenced in the post Explaining Away and an interview in connection with his book: The Predictive Mind.
An interesting example of the hierarchical predictive coding model is binocular rivalry. Binocular rivalry is a form of visual experience that occurs when, using a special experimental set-up, each eye is presented (simultaneously) with a different visual stimulus. Thus, the right eye might be presented with an image of a house, while the left receives an image of a face. Under these albeit artificial conditions, subjective experience unfolds in a surprising, “bi-stable” manner. Instead of visually experiencing a confusing all-points merger of house and face information, subjects report a kind of perceptual alternation between seeing the house and seeing the face.