Cognitive Perspectives on Judgment and Decision Making
The Nature of Decision Making
Introduction to Decision Making: Decision making involves determining how to behave or act based on feelings, associations, and cognitive evaluations. It is distinguishably different from judgment, although the two are closely linked.
Implicit and Explicit Factors:
Implicit Bias: We may not always be aware of why we decide things due to positive or negative associations between concepts that are not consciously recognized.
Attribution of Values: Decisions require assigning values to different options. This can be explicit (e.g., creating a pro and con list) or implicit (e.g., gut feelings about social interactions).
Social Interaction Example: A common decision-making scenario involves social reach-out (e.g., "Should I call or text someone I am interested in?"). Individuals weigh prospective outcomes:
Pro: Reaching out might lead to a connection.
Con: Reaching out might make the person look "desperate."
Alternative Con: Not calling might result in appearing as if they are ignoring the other person.
Prescriptive vs. Descriptive Theories
Prescriptive Theories: These theories establish how humans should decide to achieve the most rational or optimal outcome.
Based on economical or mathematical models.
Focused on achieving the "best" possible result.
Example: An objective friend suggesting you wait several days to call someone back to ensure the decision is conservative and calculated rather than impulsive.
Descriptive Theories: These theories outline how humans actually behave and decide.
Often shows how human behavior departs from prescriptive, rational choices.
Decisions are frequently influenced by internal states (e.g., excitement) or external stimuli (e.g., watching a movie like Sleepless in Seattle and impulsively making a phone call).
It highlights the competition between endogenous (internal goals) and exogenous (external triggers) factors.
Decision Trees and Value Assignment
Decision Trees: This is the most straightforward depiction of the decision-making process, often involving "what-if" scenarios and cost-benefit analyses.
Example: Roger Federer and Tennis: A decision tree for whether to play tennis based on external factors:
Weather Outlook: Options include Sunny, Overcast, or Rainy.
Rainy: One might immediately decide "No," although some models check if it is windy before deciding "No."
Overcast: Usually leads to a "Yes."
Sunny: Leads to a secondary check for Humidity. High humidity might lead to a "No," while lower humidity leads to a "Yes."
Subjectivity in Values: Value assignment is relatively arbitrary and based on individual priorities.
Social Value: One person may value eating out highly due to being social; another may assign it low value because they dislike public settings.
Universal Values: High agreement generally exists on the value of basic needs like food, water, and shelter.
Contested Values: Significant disagreement exists regarding the value of complex societal issues like taxes, healthcare, or recycling.
Rationality Principles and Framing Effects
Principles of Rational Decision Making: There are two key principles that humans consistently ignore:
Transitivity: If the same relation holds between option and , and between option and , it must also hold between option and . Written as: If A > B and B > C, then A > C.
Framing Invariance: Two ways of asking the same question should result in the same answer.
The Tversky & Kahneman Study (1981): This study demonstrated how framing changes decisions even when mathematical outcomes are identical.
Scenario A (Positive Framing):
Option 1: people will be saved.
Option 2: A probability that will be saved and a probability that no one will be saved.
Result: Most people choose Option 1 because they prefer the certainty of seeing lives saved.
Scenario B (Negative Framing):
Option 1: people will die.
Option 2: A probability that no one will die and a probability that will die.
Result: Most people choose Option 2. Even though the math is the same as Scenario A ( dead means live), the image of "400 dead" is unpalatable, leading to risk-seeking behavior.
Prospect Theory and Bounded Rationality
Prospect Theory: Actions are determined by mental representations of situations rather than the situations themselves. The way a situation is "framed" dictates the choice.
Example: Convincing parents to pay for a concert.
Positive Representation: "This will be a lifelong memory/flashbulb memory."
Negative Representation: "I want to blow ."
Bounded Rationality: Proposed by Herbert Simon (Nobel Prize winner), this theory suggests people are as rational as their cognitive limitations allow.
The Working Memory Platter: Humans can only process a finite amount of information at once. Decisions are limited by the capacity of this "processing platter."
Example: Environmental Consciousness: A person may care about trash in the ocean (high value) but failed to recycle everything today or chose to buy a bag of SmartPop popcorn (creating non-biodegradable trash) instead of kernels. This happens because the logistical details of perfect recycling may not fit on the working memory platter at that moment.
Judgment and Heuristics
Nature of Judgment: Judgment is the process of thinking, "I believe this will be good/bad for me," based on information available.
Heuristics: These are mental "rules of thumb"—efficient strategies that usually lead to good outcomes.
Example: Using a side entrance of a parking lot to find a spot faster because fewer people use it.
Key Terms in Judgment:
Frequency Estimate: An informal assessment of how often something happens (e.g., saying something "usually" happens).
Base Rate: The actual, objective frequency at which something occurs (e.g., planes flying overhead exactly once every ).
Attribute Substitution: Relying on easily assessed information already in one's head rather than seeking out actual data (e.g., estimating flight frequency based on what you see out the window rather than checking a flight database).
Representativeness Heuristic: Assuming all instances of a category will resemble the prototype (e.g., dog, swimming pool). This relies on characteristic features as defining principles (as seen in the "Justice/Judge" association with Ruth Bader Ginsburg).
The Good Judgment Project (NPR Case Study)
Overview: An experiment funded by the intelligence community involving average citizens making probability estimates on geopolitical events.
The Experimenters: Psychologists Philip Tetlock, Barbara Mellors, and Don Moore.
Super Forecasters: Individuals in the top of accuracy. They are often teammates who outperform intelligence officers with access to classified information by approximately .
The Participant - Elaine Rich: A pharmacist from suburban Maryland with no professional background in international affairs.
Forecasting Process: She uses basic Google searches and Wikipedia rather than classified docs.
Questions Asked:
Will North Korea launch a new multistage missile before ?
Will the government of Syria and the Syrian Supreme Military Command announce a ceasefire?
Will Russian armed forces enter Kharkiv in Ukraine by May 10?
Anonymity: Rich notes that her anonymity gives her the freedom to make true, unbiased forecasts without a professional reputation at stake.
The Wisdom of Crowds (Scientific Basis)
Origins: Concept first discovered by British statistician Francis Galton in .
The Ox Experiment: At a fair, people guessed the weight of a dead ox.
Individual Guesses: Most were very poor (too high or too low).
Crowd Average: The average guess was . The actual weight was .
Mechanism: Prediction involves a "true signal" surrounded by "noise" (statistical random variation). When many predictions are pooled, the random variations on either side of the signal cancel each other out, leaving the true signal.
Application: Jason Matheny from the intelligence community notes that this project has significantly improved the accuracy of geopolitical forecasts. While it may not replace traditional intelligence, it serves as a powerful complement to existing methods.