Common Biases & Heuristics
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Mirrored Externalities Lisa Grow Sun BYU Law School
Notre Dame Law Review Volume 90 | Issue 1 Article 4 11-2014 Mirrored Externalities Lisa Grow Sun BYU Law School Brigham Daniels BYU Law School Follow this and additional works at: http://scholarship.law.nd.edu/ndlr Part of the Property Law and Real Estate Commons Recommended Citation 90 Notre Dame L. Rev. 135 (2014) This Article is brought to you for free and open access by the Notre Dame Law Review at NDLScholarship. It has been accepted for inclusion in Notre Dame Law Review by an authorized administrator of NDLScholarship. For more information, please contact [email protected]. \\jciprod01\productn\N\NDL\90-1\NDL104.txt unknown Seq: 1 8-DEC-14 14:39 MIRRORED EXTERNALITIES Lisa Grow Sun* and Brigham Daniels** ABSTRACT A fundamental but underappreciated truth is that positive and negative externalities are actually mirror reflections of each other. What we call “mirrored externalities” exist because any action with externalities associated with it can be described as a choice to do or to refrain from doing that particular action. For example, if a person smokes and thereby creates a negative externality of more secondhand smoke, then her choice not to smoke creates a positive externality of less secondhand smoke. Conversely, if a person’s choice to get an immunization confers a positive externality of reducing vectors for disease transmission, then a choice not to get an immu- nization necessarily imposes negative externalities on third parties in the form of more vectors for disease. In each set, the negative externalities are the inverse—the mirror image—of the positive externalities. -
Critical Thinking and Debiasing: Experimentation in an Academic Writing Course
JAPAN ASSOCIATION FOR LANGUAGE TEACHING JALT2019 • TEACHER EFFICACY, LEARNER AGENCY NOVEMBER 1–4, 2019 • NAGOYA, JAPAN Critical Thinking and Debiasing: Experimentation in an Academic Writing Course esearch and interest in cognitive heuristics (shortcuts in thinking) and cognitive Guy Smith R biases (thinking predispositions or tendencies) has grown rapidly in the past 10 to 15 years. What is known about cognitive biases today owes much to work drawn from International Christian University behavioral economics, social psychology, decision making, and error studies. Recently, the cognitive bias discussion has found a much wider audience with the publication John Peloghitis of popular science books such as Nudge by Richard Thaler and Cass Sunstein (2008), International Christian University Predictably Irrational by Dan Ariely (2009), Daniel Kahneman’s Thinking, Fast and Slow (2011), and Robert Cialdini’s Pre-suasion (2016). These books provided the general public with a fascinating and, in some ways, unsettling look into how we think. The Reference Data: research demonstrated that judgments and decisions often emerge from taking thinking Smith, G., & Peloghitis, J. (2020). Critical thinking and debiasing: Experimentation in an academic shortcuts, relying on our intuitions and feelings, and attending to certain stimuli while writing course. In P. Clements, A. Krause, & R. Gentry (Eds.), Teacher efficacy, learner agency. ignoring others. Some of the biases that emerge from these cognitive processes include Tokyo: JALT. https://doi.org/10.37546/JALTPCP2019-51 confirmation bias (to look for or interpret information that confirms a previous belief), in- group bias (a tendency to favor members of your in-groups) and the aptly named ostrich In the last two decades, interest in cognitive biases has rapidly grown across various fields of effect (the tendency to ignore negative situations). -
Addressing Cognitive Biases in Augmented Business Decision Systems Human Performance Metrics for Generic AI-Assisted Decision Making
Addressing Cognitive Biases in Augmented Business Decision Systems Human performance metrics for generic AI-assisted decision making. THOMAS BAUDEL* IBM France Lab, Orsay, France MANON VERBOCKHAVEN IBM France Lab & ENSAE VICTOIRE COUSERGUE IBM France Lab, Université Paris-Dauphine & Mines ParisTech GUILLAUME ROY IBM France Lab & ENSAI RIDA LAARACH IBM France Lab, Telecom ParisTech & HEC How do algorithmic decision aids introduced in business decision processes affect task performance? In a first experiment, we study effective collaboration. Faced with a decision, subjects alone have a success rate of 72%; Aided by a recommender that has a 75% success rate, their success rate reaches 76%. The human-system collaboration had thus a greater success rate than each taken alone. However, we noted a complacency/authority bias that degraded the quality of decisions by 5% when the recommender was wrong. This suggests that any lingering algorithmic bias may be amplified by decision aids. In a second experiment, we evaluated the effectiveness of 5 presentation variants in reducing complacency bias. We found that optional presentation increases subjects’ resistance to wrong recommendations. We conclude by arguing that our metrics, in real usage scenarios, where decision aids are embedded as system-wide features in Business Process Management software, can lead to enhanced benefits. CCS CONCEPTS • Cross-computing tools and techniques: Empirical studies, Information Systems: Enterprise information systems, Decision support systems, Business Process Management, Human-centered computing, Human computer interaction (HCI), Visualization, Machine Learning, Automation Additional Keywords and Phrases: Business decision systems, Decision theory, Cognitive biases * [email protected]. 1 INTRODUCTION For the past 20 years, Business Process Management (BPM) [29] and related technologies such as Business Rules [10, 52] and Robotic Process Automation [36] have streamlined processes and operational decision- making in large enterprises, transforming work organization. -
Ambiguity Aversion in Qualitative Contexts: a Vignette Study
Ambiguity aversion in qualitative contexts: A vignette study Joshua P. White Melbourne School of Psychological Sciences University of Melbourne Andrew Perfors Melbourne School of Psychological Sciences University of Melbourne Abstract Most studies of ambiguity aversion rely on experimental paradigms involv- ing contrived monetary bets. Thus, the extent to which ambiguity aversion is evident outside of such contexts is largely unknown, particularly in those contexts which cannot easily be reduced to numerical terms. The present work seeks to understand whether ambiguity aversion occurs in a variety of different qualitative domains, such as work, family, love, friendship, exercise, study and health. We presented participants with 24 vignettes and measured the degree to which they preferred risk to ambiguity. In a separate study we asked participants for their prior probability estimates about the likely outcomes in the ambiguous events. Ambiguity aversion was observed in the vast majority of vignettes, but at different magnitudes. It was predicted by gain/loss direction but not by the prior probability estimates (with the inter- esting exception of the classic Ellsberg ‘urn’ scenario). Our results suggest that ambiguity aversion occurs in a wide variety of qualitative contexts, but to different degrees, and may not be generally driven by unfavourable prior probability estimates of ambiguous events. Corresponding Author: Joshua P. White ([email protected]) AMBIGUITY AVERSION IN QUALITATIVE CONTEXTS: A VIGNETTE STUDY 2 Introduction The world is replete with the unknown, yet people generally prefer some types of ‘unknown’ to others. Here, an important distinction exists between risk and uncertainty. As defined by Knight (1921), risk is a measurable lack of certainty that can be represented by numerical probabilities (e.g., “there is a 50% chance that it will rain tomorrow”), while ambiguity is an unmeasurable lack of certainty (e.g., “there is an unknown probability that it will rain tomorrow”). -
Contingent Reliance on the Affect Heuristic As a Function of Regulatory Focus
Contingent Reliance on the Affect Heuristic as a Function of Regulatory Focus Michel Tuan Pham Tamar Avnet Results from four studies show that the reliance on affect as a heuristic of judgment and decision-making is more pronounced under a promotion focus than under a prevent ion focus. Two different manifestations of this phenomenon were observed. Studies 1–3 show that different type s of affective inputs are weighted more heavily under promotion than under prevention in person-impression formation, product evaluations, and social recommendations. Study 4 additionally shows that valuations performed under promotion are more scope- insensitive—a characteristic of affect-based valuations—than valuations performed under prevention. The greater reliance on affect as a heuristic under promotion seems to arise because promotion-focused individuals tend to find affective inputs more diagnostic, not because promotion increases the reliance on peripheral information per se. Although decision research has historically focused affective responses to make judgments and decisions, on the cognitive processes underlying decision making, to begin with? a growing body of research from multiple disciplines The purpose of this research is to test the suggests that affective processes play an important role hypothesis that an important determinant of the as well. In particular, there is strong evidence that reliance on affect as a heuristic for evaluations and decisions are often based on subjective affective decisions is the self-regulatory orientation of the responses to the options, which appear to be seen as decision-maker. Building on recent findings by Pham indicative of the options’ values (Bechara, Damasio, and Avnet (2004), we propose that the reliance on Tranel, & Damasio, 1997; Loewenstein, Weber, Hsee, affect as an evaluation heuristic is more pronounced & Welch, 2001; Pham, 1998; Schwarz & Clore, 1983). -
A Task-Based Taxonomy of Cognitive Biases for Information Visualization
A Task-based Taxonomy of Cognitive Biases for Information Visualization Evanthia Dimara, Steven Franconeri, Catherine Plaisant, Anastasia Bezerianos, and Pierre Dragicevic Three kinds of limitations The Computer The Display 2 Three kinds of limitations The Computer The Display The Human 3 Three kinds of limitations: humans • Human vision ️ has limitations • Human reasoning 易 has limitations The Human 4 ️Perceptual bias Magnitude estimation 5 ️Perceptual bias Magnitude estimation Color perception 6 易 Cognitive bias Behaviors when humans consistently behave irrationally Pohl’s criteria distilled: • Are predictable and consistent • People are unaware they’re doing them • Are not misunderstandings 7 Ambiguity effect, Anchoring or focalism, Anthropocentric thinking, Anthropomorphism or personification, Attentional bias, Attribute substitution, Automation bias, Availability heuristic, Availability cascade, Backfire effect, Bandwagon effect, Base rate fallacy or Base rate neglect, Belief bias, Ben Franklin effect, Berkson's paradox, Bias blind spot, Choice-supportive bias, Clustering illusion, Compassion fade, Confirmation bias, Congruence bias, Conjunction fallacy, Conservatism (belief revision), Continued influence effect, Contrast effect, Courtesy bias, Curse of knowledge, Declinism, Decoy effect, Default effect, Denomination effect, Disposition effect, Distinction bias, Dread aversion, Dunning–Kruger effect, Duration neglect, Empathy gap, End-of-history illusion, Endowment effect, Exaggerated expectation, Experimenter's or expectation bias, -
Enhancing the Production Effect in Memory: Singing, Underlying Mechanisms, and Applications
ENHANCING THE PRODUCTION EFFECT IN MEMORY: SINGING, UNDERLYING MECHANISMS, AND APPLICATIONS by Chelsea Karmel Quinlan Submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy at Dalhousie University Halifax, Nova Scotia December 2017 © Copyright by Chelsea Karmel Quinlan, 2017 TABLE OF CONTENTS LIST OF TABLES .......................................................................... v LIST OF FIGURES ....................................................................... vi ABSTRACT ................................................................................ vii LIST OF ABBREVIATIONS USED .................................................. viii ACKNOWLEDGEMENTS ................................................................ ix CHAPTER 1: INTRODUCTION ......................................................... 1 1.1 INTRODUCTION .................................................................................................. 2 1.2 HISTORY OF THE PRODUCTION EFFECT ........................................................... 4 1.3 A REVIEW OF THEORETICAL PERSPECTIVES .................................................. 11 1.4 MUSIC AND MEMORY ....................................................................................... 17 1.5 CHAPTER SUMMARY, RATIONALE, AND CURRENT EXPERIMENTS ................ 19 CHAPTER 2: EXTENDING THE BOUNDARIES OF THE PRODUCTION EFFECT .................................................................................... 24 2.1 ABSTRACT ........................................................................................................ -
The Availability Heuristic
CHAPTER 11 THE AVAILABILITY HEURISTIC According to Amos Tversky and Daniel Kahneman (1974, p. 1127), the availability heuristic is a rule of thumb in which decision makers "assess the frequency of a class or the probability of an event by the ease with which instances or occurrences can be brought to mind." Usually this heuristic works quite well; all things being equal, common events are easier to remember or imagine than are uncommon events. By rely ing on availability to estimate frequency and probability, decision mak ers are able to simplify what might otherwise be very difficult judg ments. As with any heuristic, however, there are cases in which the general rule of thumb breaks down and leads to systematic biases. Some events are more available than others not because they tend to occur frequently or with high probability, but because they are inherently easier to think about, because they have taken place recently, because they are highly emotional, and so forth. This chapter examines three general questions: (1) What are instances in which the availability heuristic leads to biased judgments? (2) Do decision makers perceive an event as more likely after they have imagined it happening? (3) How is vivid information dif ferent from other information? AVAILABILITY GOES AWRY Which is a more likely cause of death in the United States-being killed by falling airplane parts or by a shark? Most people rate shark attacks as more probable than death from falling airplane parts (see Item #7 of the Reader Survey for your answer). Shark attacks certainly receive more publicity than do deaths from falling airplane parts, and they are far easier to imagine (thanks in part to movies such as Jaws). -
1 Session 17
42nd Annual National Conference of Regulatory Attorneys Nashville, Tennessee May 5-8, 2019 Outline & Materials Session 17 - Bridge Over Troubled Water: The Arch of Ethics It is easy to fall into ethically-troubled waters. Here, a series of lively skits will show us some of the daily challenges facing attorneys who practice before the fictitious Nirvana Public Utility Commission. The situations portrayed leave us to question: Will these lawyers slip into the muddy waters or steady themselves by clinging to the Model Rules of Professional Conduct? Legal Instruction: Richard Collier, Esq. Skit Production: Eve Moran, Esq. _________________________________________________________________________ Skit I - Things Are Jumping At The Bluebird Bar & Grill Resources: Ex Parte Statutes - Tennessee (Tenn. Code Ann. § 4-5-304) Model Rule 3.5 A lawyer shall not: (a) seek to influence a judge, juror, prospective juror or other official by means prohibited by law; (b) communicate ex parte with such a person during the proceeding unless authorized to do so by law or court order; (c) communicate with a juror or prospective juror after discharge of the jury if: (1) the communication is prohibited by law or court order; (2) the juror has made known to the lawyer a desire not to communicate; or (3) the communication involves misrepresentation, coercion, duress or harassment; or (d) engage in conduct intended to disrupt a tribunal. Model Rule 8.4 It is professional misconduct for a lawyer to: (a) violate or attempt to violate the Rules of Professional Conduct, -
The Art of Thinking Clearly
For Sabine The Art of Thinking Clearly Rolf Dobelli www.sceptrebooks.co.uk First published in Great Britain in 2013 by Sceptre An imprint of Hodder & Stoughton An Hachette UK company 1 Copyright © Rolf Dobelli 2013 The right of Rolf Dobelli to be identified as the Author of the Work has been asserted by him in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means without the prior written permission of the publisher, nor be otherwise circulated in any form of binding or cover other than that in which it is published and without a similar condition being imposed on the subsequent purchaser. A CIP catalogue record for this title is available from the British Library. eBook ISBN 978 1 444 75955 6 Hardback ISBN 978 1 444 75954 9 Hodder & Stoughton Ltd 338 Euston Road London NW1 3BH www.sceptrebooks.co.uk CONTENTS Introduction 1 WHY YOU SHOULD VISIT CEMETERIES: Survivorship Bias 2 DOES HARVARD MAKE YOU SMARTER?: Swimmer’s Body Illusion 3 WHY YOU SEE SHAPES IN THE CLOUDS: Clustering Illusion 4 IF 50 MILLION PEOPLE SAY SOMETHING FOOLISH, IT IS STILL FOOLISH: Social Proof 5 WHY YOU SHOULD FORGET THE PAST: Sunk Cost Fallacy 6 DON’T ACCEPT FREE DRINKS: Reciprocity 7 BEWARE THE ‘SPECIAL CASE’: Confirmation Bias (Part 1) 8 MURDER YOUR DARLINGS: Confirmation Bias (Part 2) 9 DON’T BOW TO AUTHORITY: Authority Bias 10 LEAVE YOUR SUPERMODEL FRIENDS AT HOME: Contrast Effect 11 WHY WE PREFER A WRONG MAP TO NO -
MITIGATING COGNITIVE BIASES in RISK IDENTIFICATION: Practitioner Checklist for the AEROSPACE SECTOR
MITIGATING COGNITIVE BIASES IN RISK IDENTIFICATION: Practitioner Checklist for the AEROSPACE SECTOR Debra L. Emmons, Thomas A. Mazzuchi, Shahram Sarkani, and Curtis E. Larsen This research contributes an operational checklist for mitigating cogni- tive biases in the aerospace sector risk management process. The Risk Identification and Evaluation Bias Reduction Checklist includes steps for grounding the risk identification and evaluation activities in past project experiences through historical data, and emphasizes the importance of incorporating multiple methods and perspectives to guard against optimism and a singular project instantiation-focused view. The authors developed a survey to elicit subject matter expert judgment on the value of the check- list to support its use in government and industry as a risk management tool. The survey also provided insights on bias mitigation strategies and lessons learned. This checklist addresses the deficiency in the literature in providing operational steps for the practitioner to recognize and implement strategies for bias reduction in risk management in the aerospace sector. DOI: https://doi.org/10.22594/dau.16-770.25.01 Keywords: Risk Management, Optimism Bias, Planning Fallacy, Cognitive Bias Reduction Mitigating Cognitive Biases in Risk Identification http://www.dau.mil January 2018 This article and its accompanying research contribute an operational FIGURE 1. RESEARCH APPROACH Risk Identification and Evaluation Bias Reduction Checklist for cognitive bias mitigation in risk management for the aerospace sector. The checklist Cognitive Biases & Bias described herein offers a practical and implementable project management Enabling framework to help reduce biases in the aerospace sector and redress the Conditions cognitive limitations in the risk identification and analysis process. -
Nudge Theory
Nudge Theory http://www.businessballs.com/nudge-theory.htm Nudge theory is a flexible and modern concept for: • understanding of how people think, make decisions, and behave, • helping people improve their thinking and decisions, • managing change of all sorts, and • identifying and modifying existing unhelpful influences on people. Nudge theory was named and popularized by the 2008 book, 'Nudge: Improving Decisions About Health, Wealth, and Happiness', written by American academics Richard H Thaler and Cass R Sunstein. The book is based strongly on the Nobel prize- winning work of the Israeli-American psychologists Daniel Kahneman and Amos Tversky. This article: • reviews and explains Thaler and Sunstein's 'Nudge' concept, especially 'heuristics' (tendencies for humans to think and decide instinctively and often mistakenly) • relates 'Nudge' methods to other theories and models, and to Kahneman and Tversky's work • defines and describes additional methods of 'nudging' people and groups • extends the appreciation and application of 'Nudge' methodology to broader change- management, motivation, leadership, coaching, counselling, parenting, etc • offers 'Nudge' methods and related concepts as a 'Nudge' theory 'toolkit' so that the concept can be taught and applied in a wide range of situations involving relationships with people, and enabling people to improve their thinking and decision- making • and offers a glossary of Nudge theory and related terms 'Nudge' theory was proposed originally in US 'behavioral economics', but it can be adapted and applied much more widely for enabling and encouraging change in people, groups, or yourself. Nudge theory can also be used to explore, understand, and explain existing influences on how people behave, especially influences which are unhelpful, with a view to removing or altering them.