Heuristics and Biases at the Bargaining Table Russell Korobkin
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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). -
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, -
The Art of Thinking Clearly (577H) Sources.Indd
THE ART OF THINKING CLEARLY A NOTE ON SOURCES Hundreds of studies have been conducted on the vast majority of cognitive and behav- ioural errors. In a scholarly work, the complete reference section would easily double the pages of this book. I have focused on the most important quotes, technical refer- ences, recommendations for further reading and comments. The knowledge encompassed in this book is based on the research carried out in the fields of cognitive and social psychology over the past three decades. SURVIVORSHIP BIAS Survivorship bias in funds and stock market indices, see: Edwin J. Elton, Martin J. Gruber & Christopher R. Blake, ‘Survivorship Bias and Mutual Fund Performance’, The Review of Financial Studies, volume 9, number 4, 1996, 1097–1120. Statistically relevant results by coincidence (self-selection), see: John P. A. Ioan- nidis, ‘Why Most Published Research Findings Are False’, PLoS Med 2(8), 2005, e124. SWIMMER’S BODY ILLUSION Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007), 109–110. ‘Ideally, the comparison should be made between people who went to Harvard and people who were admitted to Harvard but chose instead to go to Podunk State. Unfortunately, this is likely to produce samples too small for statistical analysis.’ Thomas Sowell, Economic Facts and Fallacies (New York: Basic Books, 2008), 106. David Lykken & Auke Tellegen, ‘Happiness Is a Stochastic Phenomenon’, Psycho- logical Science, Vol.7, No. 3, May 1996, 189. In his book Good to Great, Jim Collins cites the CEO of Pitney Bowes, Dave Nassef: ‘I used to be in the Marines, and the Marines get a lot of credit for building people’s values. -
Heuristics and Biases the Psychology of Intuitive Judgment. In
P1: FYX/FYX P2: FYX/UKS QC: FCH/UKS T1: FCH CB419-Gilovich CB419-Gilovich-FM May 30, 2002 12:3 HEURISTICS AND BIASES The Psychology of Intuitive Judgment Edited by THOMAS GILOVICH Cornell University DALE GRIFFIN Stanford University DANIEL KAHNEMAN Princeton University iii P1: FYX/FYX P2: FYX/UKS QC: FCH/UKS T1: FCH CB419-Gilovich CB419-Gilovich-FM May 30, 2002 12:3 published by the press syndicate of the university of cambridge The Pitt Building, Trumpington Street, Cambridge, United Kingdom cambridge university press The Edinburgh Building, Cambridge CB2 2RU, UK 40 West 20th Street, New York, NY 10011-4211, USA 477 Williamstown, Port Melbourne, VIC 3207, Australia Ruiz de Alarcon´ 13, 28014, Madrid, Spain Dock House, The Waterfront, Cape Town 8001, South Africa http://www.cambridge.org C Cambridge University Press 2002 This book is in copyright. Subject to statutory exception and to the provisions of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published 2002 Printed in the United States of America Typeface Palatino 9.75/12.5 pt. System LATEX2ε [TB] A catalog record for this book is available from the British Library. Library of Congress Cataloging in Publication data Heuristics and biases : the psychology of intuitive judgment / edited by Thomas Gilovich, Dale Griffin, Daniel Kahneman. p. cm. Includes bibliographical references and index. ISBN 0-521-79260-6 – ISBN 0-521-79679-2 (pbk.) 1. Judgment. 2. Reasoning (Psychology) 3. Critical thinking. I. Gilovich, Thomas. II. Griffin, Dale III. Kahneman, Daniel, 1934– BF447 .H48 2002 153.4 – dc21 2001037860 ISBN 0 521 79260 6 hardback ISBN 0 521 79679 2 paperback iv P1: FYX/FYX P2: FYX/UKS QC: FCH/UKS T1: FCH CB419-Gilovich CB419-Gilovich-FM May 30, 2002 12:3 Contents List of Contributors page xi Preface xv Introduction – Heuristics and Biases: Then and Now 1 Thomas Gilovich and Dale Griffin PART ONE. -
Bounded Rationality Till Grüne-Yanoff* Royal Institute of Technology, Stockholm, Sweden
Philosophy Compass 2/3 (2007): 534–563, 10.1111/j.1747-9991.2007.00074.x Bounded Rationality Till Grüne-Yanoff* Royal Institute of Technology, Stockholm, Sweden Abstract The notion of bounded rationality has recently gained considerable popularity in the behavioural and social sciences. This article surveys the different usages of the term, in particular the way ‘anomalous’ behavioural phenomena are elicited, how these phenomena are incorporated in model building, and what sort of new theories of behaviour have been developed to account for bounded rationality in choice and in deliberation. It also discusses the normative relevance of bounded rationality, in particular as a justifier of non-standard reasoning and deliberation heuristics. For each of these usages, the overview discusses the central methodological problems. Introduction The behavioural sciences, in particular economics, have for a long time relied on principles of rationality to model human behaviour. Rationality, however, is traditionally construed as a normative concept: it recommends certain actions, or even decrees how one ought to act. It may therefore not surprise that these principles of rationality are not universally obeyed in everyday choices. Observing such rationality-violating choices, increasing numbers of behavioural scientists have concluded that their models and theories stand to gain from tinkering with the underlying rationality principles themselves. This line of research is today commonly known under the name ‘bounded rationality’. In all likelihood, the term ‘bounded rationality’ first appeared in print in Models of Man (Simon 198). It had various terminological precursors, notably Edgeworth’s ‘limited intelligence’ (467) and ‘limited rationality’ (Almond; Simon, ‘Behavioral Model of Rational Choice’).1 Conceptually, Simon (‘Bounded Rationality in Social Science’) even traces the idea of bounded rationality back to Adam Smith. -
How Should We Think About Americans' Beliefs About Economic Mobility?
Judgment and Decision Making, Vol. 13, No. 3, May 2018, pp. 297–304 How should we think about Americans’ beliefs about economic mobility? Shai Davidai∗ Thomas Gilovich† Abstract Recent evidence suggests that Americans’ beliefs about upward mobility are overly optimistic. Davidai & Gilovich (2015a), Kraus & Tan (2015), and Kraus (2015) all found that people overestimate the likelihood that a person might rise up the economic ladder, and underestimate the likelihood that they might fail to do so. However, using a different methodology, Chambers, Swan and Heesacker (2015) reported that Americans’ beliefs about mobility are much more pessimistic. Swan, Chambers, Heesacker and Nero (2017) provide a much-needed summary of these conflicting findings and question the utility of measuring population-level biases in judgments of inequality and mobility. We value their summary but argue that their conclusion is premature. By focusing on measures that best tap how laypeople naturally think about the distribution of income, we believe that researchers can draw meaningful conclusions about the public’s perceptions of economic mobility. When more ecologically representative measures are used, the consistent finding is that Americans overestimate the extent of upward mobility in the United States. To explain the divergent findings in the literature, we provide evidence that the methods used by Chambers et al. (2015) inadvertently primed participants to think about immobility rather than mobility. Finally, using a novel method to examine beliefs about economic -
Cognitive Biases in Software Engineering: a Systematic Mapping Study
Cognitive Biases in Software Engineering: A Systematic Mapping Study Rahul Mohanani, Iflaah Salman, Burak Turhan, Member, IEEE, Pilar Rodriguez and Paul Ralph Abstract—One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently gained popularity in software engineering research. This paper therefore systematically maps, aggregates and synthesizes the literature on cognitive biases in software engineering to generate a comprehensive body of knowledge, understand state of the art research and provide guidelines for future research and practise. Focusing on bias antecedents, effects and mitigation techniques, we identified 65 articles (published between 1990 and 2016), which investigate 37 cognitive biases. Despite strong and increasing interest, the results reveal a scarcity of research on mitigation techniques and poor theoretical foundations in understanding and interpreting cognitive biases. Although bias-related research has generated many new insights in the software engineering community, specific bias mitigation techniques are still needed for software professionals to overcome the deleterious effects of cognitive biases on their work. Index Terms—Antecedents of cognitive bias. cognitive bias. debiasing, effects of cognitive bias. software engineering, systematic mapping. 1 INTRODUCTION OGNITIVE biases are systematic deviations from op- knowledge. No analogous review of SE research exists. The timal reasoning [1], [2]. In other words, they are re- purpose of this study is therefore as follows: curring errors in thinking, or patterns of bad judgment Purpose: to review, summarize and synthesize the current observable in different people and contexts. A well-known state of software engineering research involving cognitive example is confirmation bias—the tendency to pay more at- biases. -
Mechanisms in Risky Choice Framing
Mechanisms in Risky Choice Framing Affective Responses and Deliberative Processing Liva Jenny Martinussen Master of Philosophy in Psychology, Cognitive Neuroscience Department of Psychology University of Oslo April 2016 II Mechanisms in Risky Choice Framing: Affective Responses and Deliberative Processing By Liva Jenny Martinussen Department of Psychology UNIVERSITY OF OSLO III © Liva Jenny Martinussen 2016 Mechanisms in Risky Choice Framing: Affective responses and Deliberative Processing Author: Live Jenny Martinussen http://www.duo.uio.no/ IV Summary Author: Liva Jenny Martinussen Supervisors: Anine Riege (Supervisor) and Unni Sulutvedt (Co-Supervisor) Title: Mechanisms in Risky Choice Framing: Affective Responses and Deliberative Processing Background: The risky choice framing effect is a decision making bias, where people tend to be risk-averse when options are presented as gains and risk-seeking when options are presented as losses, although the outcomes are objectively equivalent. The mechanisms involved in risky choice framing effects are still not fully understood. Several individual differences are assumed to moderate the processing of framing tasks and the magnitude of framing effects. Objectives: The aim of the current study was to investigate the framing effect across six framing task in a within-subject design, and explore whether gain and loss frames were associated with different levels of affective responses and deliberative processing. An additional aim was to investigate how individual differences in emotion management ability and numeracy affected performance and processing of framing tasks. Method: The study was an independent research project and the author collected all the data. Eye-tracking technology was employed; number of fixations, duration of fixations, repeated inspections of options and pupil dilations were recorded from 80 predominantly young adults while performing on six framing tasks. -
A Heuristic Study of the Process of Becoming an Integrative Psychotherapist
'This Time it's Personal': A Heuristic Study of the Process of Becoming an Integrative Psychotherapist. A thesis submitted to the University of Manchester for the degree of Professional Doctorate in Counselling Psychology in the Faculty of Humanities 2015 Cathal O’Connor 1 2 Contents Abstract 7 Declaration 8 Copyright Statement 9 Dedication and Acknowledgements 11 Chapter 1: Introduction 12 Introduction 12 The person of the researcher: What's past is 12 prologue There is an 'I' in thesis 13 Statement of the problem 15 The structure of my research 16 What is counselling psychology? 17 Integration 18 What is psychotherapy? 20 Conclusion 21 Chapter 2: Literature Review 22 Introduction 22 Researching psychotherapy and integration 22 Personal and professional development in 24 counselling psychology training What is personal development? 25 Therapist training 27 Stages of development 34 Supervision 35 Personal development and personal therapy 37 Training in integrative psychotherapy 41 Developing an integrative theory of practice 46 Journaling for personal and professional 48 development Conclusion 57 Chapter 3: Methodology 59 Introduction 59 3 Philosophical positioning 59 Psychology and counselling psychology 60 Epistemology and the philosophy of science 60 The philosophy of scientific psychology 62 Qualitative research 63 Phenomenology 64 Research design 65 Initial engagement 69 The research question 71 Immersion 73 Incubation 76 Illumination 78 Explication 79 Creative synthesis 80 Data generation: Journaling 80 Data analysis: Thematic analysis -
The Law of Implicit Bias
The Law of Implicit Bias Christine Jolls† Cass R. Sunstein†† Considerable attention has been given to the Implicit Association Test (IAT), which finds that most people have an implicit and unconscious bias against members of traditionally disadvantaged groups. Implicit bias poses a special challenge for antidiscrimination law because it suggests the pos- sibility that people are treating others differently even when they are un- aware that they are doing so. Some aspects of current law operate, whether intentionally or not, as controls on implicit bias; it is possible to imagine other efforts in that vein. An underlying suggestion is that implicit bias might be controlled through a general strategy of “debiasing through law.” Introduction Consider two pairs of problems: 1A. A regulatory agency is deciding whether to impose new restric- tions on cloning mammals for use as food. Most people within the agency believe that the issue is an exceedingly difficult one, but in the end they support the restrictions on the basis of a study suggesting that cloned mammals are likely to prove unhealthy for human consumption. The study turns out to be based on palpable errors. 1B. A regulatory agency is deciding whether to impose new restric- tions on cloning mammals for use as food. Most people within the agency believe that the issue is an exceedingly difficult one, but in the end they support the restrictions on the basis of a “gut feeling” that cloned mammals are likely to be unhealthy to eat. It turns out that the “gut feeling,” spurred Copyright © 2006 California Law Review, Inc. -
Behavioral Economics in Context Applications for Development, Inequality & Discrimination, Finance, and Environment
Behavioral Economics In Context Applications for Development, Inequality & Discrimination, Finance, and Environment By Anastasia C. Wilson An ECI Teaching Module on Social and Environmental Issues in Economics Global Development Policy Center Boston University 53 Bay State Road Boston, MA 02155 bu.edu/gdp Economics in Context Initiative, Global Development Policy Center, Boston University, 2020. Permission is hereby granted for instructors to copy this module for instructional purposes. Suggested citation: Wilson, Anastasia C. (2020) “Behavioral Economics In Context: Applications for Development, Inequality & Discrimination, Finance, and Environment.” An ECI Teaching Module on Social and Economic Issues, Economics in Context Initiative, Global Development Policy Center, Boston University, 2020. Students may also download the module directly from: http://www.bu.edu/eci/education-materials/teaching-modules/ Comments and feedback from course use are welcomed: Economics in Context Initiative Global Development Policy Center Boston University 53 Bay State Road Boston, MA 02215 http://www.bu.edu/eci/ Email: [email protected] NOTE – terms denoted in bold face are defined in the KEY TERMS AND CONCEPTS section at the end of the module. BEHAVIORAL ECONOMICS IN CONTEXT TABLE OF CONTENTS 1. INTRODUCTION ........................................................................................................ 4 1.1 The History and Development of Behavioral Economics .......................................................... 5 1.2 Behavioral Economics Toolkit: