scholarly journals Expanding the Weighted Updating Model

2016 ◽  
Author(s):  
Jesse Aaron Zinn
Keyword(s):  
Cognitive Biases ◽  
Bayesian Updating ◽  
Irrelevant Information ◽  
Base Rate ◽  
Order Effects ◽  
Availability Heuristic ◽  
Base Rate Neglect ◽  
Attribution Bias

This work casts light upon a pair of restrictions inherent to the basic weighted updating model, which is a generalization of Bayesian updating that allows for biased learning. Relaxing the restrictions allows for the study of individuals who discriminate between observations or who treat information in a dynamically inconsistent manner. These generalizations augment the set of cognitive biases that can be studied using new versions of the weighted updating model to include the availability heuristic, order effects, self-attribution bias, and base-rate neglect in light of irrelevant information.

scholarly journals Experts use base rates in real-world sequential decisions

2021 ◽  
Author(s):  
Daniel Link ◽  
Markus Raab
Keyword(s):  
Real World ◽  
Cognitive Biases ◽  
Real Life ◽  
Base Rate ◽  
Decision Makers ◽  
Decision Strategies ◽  
The Real ◽  
Base Rates ◽  
Base Rate Neglect ◽  
Specific Category

AbstractHuman behavior is often assumed to be irrational, full of errors, and affected by cognitive biases. One of these biases is base-rate neglect, which happens when the base rates of a specific category are not considered when making decisions. We argue here that while naïve subjects demonstrate base-rate neglect in laboratory conditions, experts tested in the real world do use base rates. Our explanation is that lab studies use single questions, whereas, in the real world, most decisions are sequential in nature, leading to a more realistic test of base-rate use. One decision that lends itself to testing base-rate use in real life occurs in beach volleyball—specifically, deciding to whom to serve to win the game. Analyzing the sequential choices in expert athletes in more than 1,300 games revealed that they were sensitive to base rates and adapted their decision strategies to the performance of the opponent. Our data describes a threshold at which players change their strategy and use base rates. We conclude that the debate over whether decision makers use base rates should be shifted to real-world tests, and the focus should be on when and how base rates are used.

BASE RATE NEGLECT FOR THE WEALTH OF INTERACTING PEOPLE

2010 ◽  
Vol 13 (05) ◽  
pp. 607-619 ◽  
Author(s):  
DIEMO URBIG
Keyword(s):  
Information Processing ◽  
Social Learning ◽  
Learning Process ◽  
Base Rate ◽  
Human Information Processing ◽  
Base Rates ◽  
Base Rate Neglect ◽  
Positive Externalities ◽  
Rate Information

Previous research investigating base rate neglect as a bias in human information processing has focused on isolated individuals. This study complements this research by showing that in settings of interacting individuals, especially in settings of social learning, where individuals can learn from one another, base rate neglect can increase a population's welfare. This study further supports the research arguing that a population with members biased by neglecting base rates does not need to perform worse than a population with unbiased members. Adapting the model of social learning suggested by Bikhchandani, Hirshleifer and Welch (The Journal of Political Economy100 (1992) 992–1026) and including base rates that differ from generic cases such as 50–50, conditions are identified that make underweighting base rate information increasing the population's welfare. The base rate neglect can start a social learning process that otherwise had not been started and thus base rate neglect can generate positive externalities improving a population's welfare.

scholarly journals Model-based fMRI reveals dissimilarity processes underlying base rate neglect

eLife ◽  
2018 ◽  
Vol 7 ◽  
Author(s):  
Sean R O'Bryan ◽  
Darrell A Worthy ◽  
Evan J Livesey ◽  
Tyler Davis
Keyword(s):  
Computational Models ◽  
Human Subjects ◽  
Base Rate ◽  
Imaging Data ◽  
Multivoxel Pattern Analysis ◽  
Activation Patterns ◽  
Model Based ◽  
Base Rate Neglect ◽  
Rate Information ◽  
Rare Category

Extensive evidence suggests that people use base rate information inconsistently in decision making. A classic example is the inverse base rate effect (IBRE), whereby participants classify ambiguous stimuli sharing features of both common and rare categories as members of the rare category. Computational models of the IBRE have either posited that it arises from associative similarity-based mechanisms or dissimilarity-based processes that may depend upon higher-level inference. Here we develop a hybrid model, which posits that similarity- and dissimilarity-based evidence both contribute to the IBRE, and test it using functional magnetic resonance imaging data collected from human subjects completing an IBRE task. Consistent with our model, multivoxel pattern analysis reveals that activation patterns on ambiguous test trials contain information consistent with dissimilarity-based processing. Further, trial-by-trial activation in left rostrolateral prefrontal cortex tracks model-based predictions for dissimilarity-based processing, consistent with theories positing a role for higher-level symbolic processing in the IBRE.

American base‐rate neglect: It is not the math, but the context

2020 ◽  
Vol 34 (1) ◽  
pp. 116-130
Author(s):  
Shali Wu ◽  
Clifton Emery
Keyword(s):  
Base Rate ◽  
Base Rate Neglect

scholarly journals BASE-RATE NEGLECT AS A FUNCTION OF BASE RATES IN PROBABILISTIC CONTINGENCY LEARNING

2008 ◽  
Vol 90 (1) ◽  
pp. 23-32 ◽  
Author(s):  
Florian Kutzner ◽  
Peter Freytag ◽  
Tobias Vogel ◽  
Klaus Fiedler
Keyword(s):  
Base Rate ◽  
Contingency Learning ◽  
Base Rates ◽  
Base Rate Neglect
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