Heuristics Made Easy: an Effort-Reduction Framework
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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, -
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. -
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. -
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 -
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: -
Mitigating Cognitive Bias and Design Distortion
RSD2 Relating Systems Thinking and Design 2013 Working Paper. www.systemic-design.net Interliminal Design: Mitigating Cognitive Bias and Design Distortion 1 2 3 Andrew McCollough, PhD , DeAunne Denmark, MD, PhD , and Don Harker, MS “Design is an inquiry for action” - Harold Nelson, PhD Liminal: from the Latin word līmen, a threshold “Our values and biases are expressions of who we are. It isn’t so much that our prior commitments disable our ability to reason; it is that we need to appreciate that reasoning takes place, for the most part, in settings in which we are not neutral bystanders.” - Alva Noe In this globally interconnected and information-rich society, complexity and uncertainty are escalating at an unprecedented pace. Our most pressing problems are now considered wicked, or even super wicked, in that they commonly have incomplete, continuously changing, intricately interdependent yet contradictory requirements, urgent or emergency status, no central authority, and are often caused by the same entities charged with solving them (Rittel & Webber, 1973). Perhaps similar to philosopher Karl Jaspers’ Axial Age where ‘man asked radical questions’ and the ‘unquestioned grasp on life was loosened,’ communities of all kinds now face crises of “in-between”; necessary and large-scale dismantling of previous structures, institutions, and world-views has begun, but has yet to be replaced. Such intense periods of destruction and reconstruction, or liminality, eliminate boundary lines, reverse or dissolve social hierarchies, disrupt cultural continuity, and cast penetrating onto future outcomes. Originating in human ritual, liminal stages occur mid-transition, where initiates literally "stand at the threshold" between outmoded constructs of identity or community, and entirely new ways of being. -
The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm1
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Purdue E-Pubs The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm1 Stellan Ohlssoni Abstract The research paradigm invented by Allen Newell and Herbert A. Simon in the late 1950s dominated the study of problem solving for more than three decades. But in the early 1990s, problem solving ceased to drive research on complex cognition. As part of this decline, Newell and Simon’s most innovative research practices – especially their method for inducing subjects’ strategies from verbal protocols - were abandoned. In this essay, I summarize Newell and Simon’s theoretical and methodological innovations and explain why their strategy identification method did not become a standard research tool. I argue that the method lacked a systematic way to aggregate data, and that Newell and Simon’s search for general problem solving strategies failed. Paradoxically, the theoretical vision that led them to search elsewhere for general principles led researchers away from stud- ’ ies of complex problem solving. Newell and Simon’s main enduring contribution is the theory that people solve problems via heuristic search through a problem space. This theory remains the centerpiece of our understanding of how people solve unfamiliar problems, but it is seriously incomplete. In the early 1970s, Newell and Simon suggested that the field should focus on the question where problem spaces and search strategies come from. I propose a breakdown of this overarching question into five specific research questions. Principled answers to those questions would expand the theory of heuristic search into a more complete theory of human problem solving. -
Heuristics & Biases Simplified
University of Pennsylvania ScholarlyCommons Master of Behavioral and Decision Sciences Capstones Behavioral and Decision Sciences Program 8-9-2019 Heuristics & Biases Simplified: Easy ot Understand One-Pagers that Use Plain Language & Examples to Simplify Human Judgement and Decision-Making Concepts Brittany Gullone University of Pennsylvania Follow this and additional works at: https://repository.upenn.edu/mbds Part of the Social and Behavioral Sciences Commons Gullone, Brittany, "Heuristics & Biases Simplified: Easy to Understand One-Pagers that Use Plain Language & Examples to Simplify Human Judgement and Decision-Making Concepts" (2019). Master of Behavioral and Decision Sciences Capstones. 7. https://repository.upenn.edu/mbds/7 The final capstone research project for the Master of Behavioral and Decision Sciences is an independent study experience. The paper is expected to: • Present a position that is unique, original and directly applies to the student's experience; • Use primary sources or apply to a primary organization/agency; • Conform to the style and format of excellent academic writing; • Analyze empirical research data that is collected by the student or that has already been collected; and • Allow the student to demonstrate the competencies gained in the master’s program. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/mbds/7 For more information, please contact [email protected]. Heuristics & Biases Simplified: Easy ot Understand One-Pagers that Use Plain Language & Examples to Simplify Human Judgement and Decision-Making Concepts Abstract Behavioral Science is a new and quickly growing field of study that has found ways of capturing readers’ attention across a variety of industries. The popularity of this field has led to a wealth of terms, concepts, and materials that describe human behavior and decision making. -
Anchoring Bias in Eliciting Attribute Weights and Values in Multi-Attribute Decision-Making
Delft University of Technology Anchoring bias in eliciting attribute weights and values in multi-attribute decision-making Rezaei, Jafar DOI 10.1080/12460125.2020.1840705 Publication date 2020 Document Version Final published version Published in Journal of Decision Systems Citation (APA) Rezaei, J. (2020). Anchoring bias in eliciting attribute weights and values in multi-attribute decision-making. Journal of Decision Systems, 30(1), 72-96. https://doi.org/10.1080/12460125.2020.1840705 Important note To cite this publication, please use the final published version (if applicable). Please check the document version above. Copyright Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons. Takedown policy Please contact us and provide details if you believe this document breaches copyrights. We will remove access to the work immediately and investigate your claim. This work is downloaded from Delft University of Technology. For technical reasons the number of authors shown on this cover page is limited to a maximum of 10. Journal of Decision Systems ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/tjds20 Anchoring bias in eliciting attribute weights and values in multi-attribute decision-making Jafar Rezaei To cite this article: Jafar Rezaei (2020): Anchoring bias in eliciting attribute weights and values in multi-attribute decision-making, Journal of Decision Systems, DOI: 10.1080/12460125.2020.1840705 To link to this article: https://doi.org/10.1080/12460125.2020.1840705 © 2020 The Author(s). -
The Flushtration Count Illusion: Attribute Substitution Tricks Our Interpretation of a Simple Visual Event Sequence Cyril Thomas
The Flushtration Count Illusion: Attribute substitution tricks our interpretation of a simple visual event sequence Cyril Thomas1, André Didierjean2 and Gustav Kuhn1 1 Department of Psychology 2 Laboratoire de Psychologie & MSHE Goldsmiths University of London Université de Bourgogne-Franche-Comté, New Cross, London SE14 6NW 30 rue Mégevand, 25030 Besançon United Kingdom France Address for correspondence: Cyril Thomas, Department of Psychology, Goldsmiths University of London, New Cross, London SE14 6NW, United Kingdom E-mail: [email protected] Telephone number: +33 (0)3 81 66 51 92 Fax number: +33 (0)3 81 66 54 40 Abstract: When faced with a difficult question, people sometimes work out an answer to a related, easier question without realizing that a substitution has taken place (e.g., Kahneman; 2011). In two experiments, we investigated whether this attribute substitution effect can also affect the interpretation of a simple visual event sequence. We used a magic trick called the “Flushtration Count Illusion,” which involves a technique used by magicians to give the 1 illusion of having seen multiple cards with identical backs, when in fact only the back of one card (the bottom card) is repeatedly shown. In Experiment 1, we demonstrated that most participants are susceptible to the illusion, even if they have the visual and analytical reasoning capacity to correctly process the sequence. In Experiment 2, we demonstrated that participants construct a biased and simplified representation of the Flushtration Count by substituting some attributes of the event sequence. We discussed of the psychological processes underlying this attribute substitution effect. Keywords: Magic, Attribute Substitution Effect, Misdirection, Flushtration Count Illusion, Perception, reasoning, Dual process theory Word Count: 4992. -
Revisiting Herbert Simon's “Science of Design” DJ Huppatz
Revisiting Herbert Simon’s “Science of Design” DJ Huppatz Herbert A. Simon’s The Sciences of the Artificial has long been con- sidered a seminal text for design theorists and researchers anxious to establish both a scientific status for design and the most inclusive possible definition for a “designer,” embodied in Simon’s oft-cited “[e]veryone designs who devises courses of action aimed at chang- ing existing situations into preferred ones.”1 Similar to the earlier Design Methods movement, which defines design as a problem solving, process-oriented activity (rather than primarily concerned 1 Herbert A. Simon, The Sciences of the with the production of physical artifacts), Simon’s “science of Artificial, 3rd ed. (Cambridge, MA: MIT design” was part of his broader project of unifying the social Press, 1996): 111. Design research sciences with problem solving as the glue. This article revisits review articles typically start with Simon’s text as foundational. See, for Simon’s ideas about design both to place them in context and to example, Nigel Cross, “Editorial: Forty question their ongoing legacy for design researchers. Much contem- Years of Design Research,” Design porary design research, in its pursuit of academic respectability, Studies 28, no. 1 (January 2007): 1–4; remains aligned to Simon’s broader project, particularly in its and Nigan Bayazit, “Investigating definition of design as “scientific” problem solving. However, the Design: A Review of Forty Years of Design Research,” Design Issues 20, repression of judgment, intuition, experience, and social interaction no. 1 (Winter 2004): 16–29. in Simon’s “logic of design” has had, and continues to have, pro- 2 See Hunter Crowther-Heyck, Herbert A.