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Cognitive Psychology
Table of Contents
Unit 11 Overview: Reasoning and Decision Making
11.1 Deductive and Inductive Reasoning
11.2 Decision-Making Models
11.3 Judgment Under Uncertainty
11.4 Cognitive Biases in Decision Making

Judgment under uncertainty is a crucial aspect of decision-making in our daily lives. We often rely on mental shortcuts, or heuristics, to make quick choices when faced with incomplete information, which can lead to both efficient and biased outcomes.

Our judgments are influenced by subjective probabilities and various cognitive biases. Understanding these factors can help us make more informed decisions and recognize potential errors in our thinking, ultimately improving our ability to navigate uncertain situations.

Understanding Judgment Under Uncertainty

Judgment under uncertainty

  • Process of making decisions with incomplete or ambiguous information involves estimating probabilities and outcomes in uncertain situations
  • Affects everyday choices and critical decisions influences fields (economics, politics, healthcare)
  • Real-world applications shape financial investments guide medical diagnoses inform weather predictions

Role of heuristics

  • Mental shortcuts or rules of thumb used to make quick judgments and decisions
  • Types include:
    1. Availability heuristic: judging probability based on ease of recall (plane crashes)
    2. Representativeness heuristic: assessing likelihood based on similarity to stereotypes (profiling)
    3. Anchoring and adjustment heuristic: relying on initial information to make estimates (negotiation starting points)
  • Reduce cognitive load enable faster decision-making but can lead to systematic errors or biases

Subjective probability in judgment

  • Personal belief about event likelihood based on individual knowledge, experience, and intuition
  • Contrasts with objective probability:
    • Subjective varies between individuals
    • Objective based on statistical data or formal calculations
  • Shapes risk perception affects decision-making processes
  • Bayesian reasoning involves updating beliefs based on new information: $P(A|B) = \frac{P(B|A) \times P(A)}{P(B)}$

Biases in uncertain decisions

  • Confirmation bias: seeking information confirming existing beliefs ignoring contradictory evidence (selective news consumption)
  • Overconfidence bias: overestimating abilities or knowledge underestimating risks (entrepreneurial ventures)
  • Framing effect: presentation of information influences decisions same information framed as gains or losses affects choices (marketing strategies)
  • Conjunction fallacy: believing specific conditions more probable than general ones violates basic probability laws (lottery ticket selection)
  • Base rate neglect: ignoring general probabilities when judging specific cases (medical diagnoses)
  • Hindsight bias: believing past events more predictable than they were (stock market predictions)
  • Availability cascade: self-reinforcing process where collective belief gains plausibility through repetition (social media trends)

Key Terms to Review (12)

Representativeness heuristic: The representativeness heuristic is a mental shortcut that relies on how closely something resembles a typical case or category, leading people to judge the probability of an event based on how similar it is to a prototype. This can often result in overlooking important statistical information or base rates, causing biased judgments and decisions in uncertain situations.
Anchoring and adjustment heuristic: The anchoring and adjustment heuristic is a cognitive shortcut used in decision-making, where an individual relies on an initial piece of information (the anchor) and makes adjustments based on that anchor to arrive at a final decision. This heuristic illustrates how people often start with a specific reference point and then modify their judgments, but these adjustments tend to be insufficient, leading to biased outcomes. This method is essential for understanding how we solve problems, make judgments under uncertainty, and the role of heuristics in everyday decision-making.
Availability heuristic: The availability heuristic is a mental shortcut that relies on immediate examples that come to mind when evaluating a specific topic, concept, method, or decision. This cognitive process often leads individuals to overestimate the importance or frequency of an event based on how easily they can recall similar instances, influencing problem-solving and decision-making in various contexts.
Confirmation bias: Confirmation bias is the tendency to search for, interpret, favor, and recall information in a way that confirms one's preexisting beliefs or hypotheses. This bias can significantly affect various cognitive processes, leading individuals to overlook contradictory evidence and reinforcing their current perspectives.
Availability Cascade: An availability cascade is a self-reinforcing process where an idea or belief gains increasing attention and acceptance due to its repeated expression in public discourse. This phenomenon often leads to a widespread perception of importance, regardless of the actual reality of the situation, as the more frequently something is mentioned, the more likely it is to be believed by others. This can significantly impact decision-making and judgment under uncertainty, as people tend to rely on what is most readily available in their minds rather than seeking out comprehensive information.
Hindsight bias: Hindsight bias is a cognitive phenomenon where people perceive events as having been more predictable after they have occurred. This bias leads individuals to believe that they knew the outcome of an event all along, contributing to an illusion of foresight. It often causes overconfidence in one's ability to predict future events based on past outcomes, affecting decision-making processes and evaluations of past judgments.
Framing effect: The framing effect is a cognitive bias where people's decisions are influenced by the way information is presented rather than just the information itself. This effect can significantly impact judgment and choice, leading individuals to respond differently based on how options are framed, such as in terms of potential gains or losses. Understanding this bias is crucial for recognizing how context and presentation shape perceptions and decision-making processes.
Conjunction fallacy: The conjunction fallacy is a cognitive error where people mistakenly believe that specific conditions are more probable than a single general one. This fallacy highlights how individuals often overlook the rules of probability when making judgments about the likelihood of events, leading to incorrect assessments in uncertain situations.
Base rate neglect: Base rate neglect is a cognitive bias where individuals ignore the general prevalence or frequency of an event (the base rate) when evaluating probabilities or making decisions. This bias leads people to focus on specific information rather than considering how it fits within the larger context of what is statistically likely, often resulting in poor judgment under uncertainty.
Overconfidence Bias: Overconfidence bias is a cognitive bias that leads individuals to overestimate their own abilities, knowledge, or control over outcomes. This bias can significantly impact decision-making processes, particularly in situations involving uncertainty where people may disregard evidence that contradicts their inflated self-assessment. It often results in poor judgments and decisions because individuals may ignore risks and underestimate challenges.
Bayesian reasoning: Bayesian reasoning is a statistical method that involves updating the probability estimate for a hypothesis as additional evidence or information becomes available. It is grounded in Bayes' theorem, which provides a mathematical framework for combining prior knowledge with new data to make informed decisions or predictions under uncertainty.
Subjective Probability: Subjective probability is an individual's personal assessment of the likelihood of an event occurring, based on their own experiences, beliefs, and intuition rather than objective data or statistical analysis. This form of probability emphasizes the role of personal judgment in decision-making, especially under uncertain conditions where concrete data may not be available. Understanding subjective probability helps to grasp how people evaluate risks and make choices when faced with uncertainty.