DOCSLIB.ORG

4. Cognitive Heuristics: an Approach

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
4. Cognitive Heuristics: an Approach View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by OTHES DIPLOMARBEIT Titel der Diplomarbeit Cognitive Heuristics and Biases and Their Impact on Negotiations Verfasserin Martina Györik Angestrebter akademischer Grad Magistra der Sozial- und Wirtschaftswissenschaften (Mag. rer. soc. oec.) Wien, im November 2010 Studienkennzahl lt. Studienblatt: A 157 Studienrichtung lt. Studienblatt: Internationale Betriebswirtschaft Betreuer: O. Univ.-Prof. Mag. Dr. Rudolf Vetschera Dedicated to my parents Table of Contents Table of Contents 1. Introduction .................................................................................................. 1 2. The Nature of Human Decision Behavior .............................................. 3 2.1 The Architecture of Cognition .................................................................................................. 3 2.2 Problem Solving, Choice and Judgment .................................................................................. 4 2.3 An Outlook on Decision Analysis ............................................................................................ 6 3. Models of Rationality................................................................................... 9 3.1 Homo œconomicus ..................................................................................................................... 9 3.2 The Concept of Bounded Rationality ..................................................................................... 11 4. Cognitive Heuristics: An Approach ........................................................ 13 4.1 An Introductory Example ........................................................................................................ 13 4.2 Context-sensitive Reasoning .................................................................................................... 14 4.3 Heuristics and History .............................................................................................................. 15 5. The Heuristics and Biases Program ........................................................ 17 5.1 Representativeness ..................................................................................................................... 18 5.1.1. The Conjunction Fallacy ...................................................................................................................................... 19 5.1.2 Base-rate Neglect .................................................................................................................................................... 21 5.1.3 Attribute Substitution ........................................................................................................................................... 22 5.2 Availability .................................................................................................................................. 23 5.3 Anchoring and Adjustment ...................................................................................................... 24 5.4. The Affect Heuristic.................................................................................................................. 25 5.5 Critique on the ‘Heuristics and Biases’ Program .................................................................. 27 5.5.1 The Conjunction Fallacy Revisited ..................................................................................................................... 27 5.5.2 Bayesian Reasoning Revisited .............................................................................................................................. 28 5.6 The Difference between Judgmental and Choice Heuristics .............................................. 29 6. ABC’s Heuristics: The Adaptive Toolbox ............................................. 30 6.1. Visions of Rationality ................................................................................................................ 30 6.2 Characteristics of Fast and Frugal Heuristics ........................................................................ 32 6.3 Classes of Heuristics .................................................................................................................. 34 6.3.1 Ignorance-Based Decision Making: The Recognition Heuristic ........................................................ 35 6.3.2 One-Reason Decision Making ............................................................................................................................ 38 6.3.2.1 The Minimalist .............................................................................................................................................. 39 Table of Contents 6.3.2.2 Take the Last ................................................................................................................................................. 40 6.3.2.3 Take the Best ................................................................................................................................................ 40 6.3.3 Elimination Heuristics .......................................................................................................................................... 42 6.3.3.1 Quick Estimation ......................................................................................................................................... 42 6.3.3.2 Categorization by Elimination ................................................................................................................... 43 6.4 When do People Use (Simple) Heuristics? ............................................................................ 45 6.5 The Influence of Emotions and Social Context ................................................................... 46 6.6 Critique on ABC’s Heuristics ................................................................................................... 47 6.7 Challenges Ahead: What remains to be answered ................................................................ 51 7. Negotiations ................................................................................................ 52 7.1 Characteristics of Negotiations ................................................................................................ 52 7.2 An Outlook on Negotiation Analysis ..................................................................................... 55 8. Judgmental Heuristics in Negotiations ................................................... 57 8.1 Framing ...................................................................................................................................................................... 57 8.2 Anchoring and Adjustment ................................................................................................................................... 58 8.3 Availability ................................................................................................................................................................ 58 8.4 The Mythical Fixed-Pie ........................................................................................................................................... 59 8.5 The Irrational Escalation of Commitment ......................................................................................................... 60 9. Discussion: A Critical Review of ABC’s Heuristics in Comparison to the Heuristics and Biases Program and Their Suitability for Negotiations.63 10. Literature ..................................................................................................... 70 10.1 Books ......................................................................................................................................... 70 10.2 Scientific Papers ......................................................................................................................... 71 11. Appendix ....................................................................................................... I Abstract (English) ..................................................................................................................................... I Abstract (German) .................................................................................................................................... I Resume ..................................................................................................................................................... II Lebenslauf .............................................................................................................................................. III Table of Figures Table of Figures Fig 1: Two Cognitive Systems. ................................................................................................................... 4 Fig 2: A Conceptual Model of Judgment .................................................................................................. 6 Fig 3: A Simplified Flowchart of the Decision Analysis Process .......................................................... 8 Fig 4: The Gaze Heuristic ......................................................................................................................... 13 Fig 5: The M A Paradigm ....................................................................................................................... 20 Fig 6: Stages of the Anchoring Mechanism .........................................................................................
Load more

Recommended publications
  • David G. Rand
    DAVID G. RAND Sloan School (E-62) Room 539 100 Main Street, Cambridge MA 02138 [email protected] EDUCATION 2006-2009 Ph.D., Harvard University, Systems Biology 2000-2004 B.A., Cornell University summa cum laude, Computational Biology PROFESSIONAL Massachusetts Institute of Technology 2019- Erwin H. Schell Professorship 2018- Associate Professor (tenured) of Management Science, Sloan School 2018- Secondary appointment, Department of Brain and Cognitive Sciences 2018- Affiliated faculty, Institute for Data, Systems, and Society Yale University 2017-2018 Associate Professor (tenured) – Psychology Department 2016-2017 Associate Professor (untenured) – Psychology Department 2013-2016 Assistant Professor – Psychology Department 2013-2018 Appointment by courtesy, Economics Department 2013-2018 Appointment by courtesy, School of Management 2013-2018 Cognitive Science Program 2013-2018 Institution for Social and Policy Studies 2013-2018 Yale Institute for Network Science Applied Cooperation Team (ACT) 2013- Director Harvard University 2012-2013 Postdoctoral Fellow – Psychology Department 2011 Lecturer – Human Evolutionary Biology Department 2010-2012 FQEB Prize Fellow – Psychology Department 2009-2013 Research Scientist – Program for Evolutionary Dynamics 2009-2011 Fellow – Berkman Center for Internet & Society 2006-2009 Ph.D. Student – Systems Biology 2004-2006 Mathematical Modeler – Gene Network Sciences, Ithaca NY 2003-2004 Undergraduate Research Assistant – Psychology, Cornell University 2002-2004 Undergraduate Research Assistant – Plant Biology, Cornell University SELECTED PUBLICATIONS [*Equal contribution] Mosleh M, Arechar AA, Pennycook G, Rand DG (In press) Cognitive reflection correlates with behavior on Twitter. Nature Communications. Bago B, Rand DG, Pennycook G (2020) Fake news, fast and slow: Deliberation reduces belief in false (but not true) news headlines. Journal of Experimental Psychology:General. doi:10.1037/xge0000729 Dias N, Pennycook G, Rand DG (2020) Emphasizing publishers does not effectively reduce susceptibility to misinformation on social media.
    [Show full text]
  • Concepts of Rationality in Management Research
    No. 57 - March 2011 Concepts of Rationality in Management Research From Unbounded Rationality to Eco- logical Rationality by Jörn Basel and Rolf Brühl Concepts of Rationality in Man- agement Research From Unbounded Rationality to Eco- logical Rationality ISSN: 1869-5426 AUTHORS Dipl.-Psych. Jörn Basel Chair of Management Control ESCP Europe Business School Berlin Heubnerweg 6, 14059 Berlin Germany T: +49 (0) 30 / 3 20 07-139 F: +49 (0) 30 / 3 20 07-107 [email protected] Prof. Dr. Rolf Brühl Chair of Management Control ESCP Europe Business School Berlin EDITOR Heubnerweg 6, 14059 Berlin © ESCP Europe Wirtschaftshochschule Berlin Germany Heubnerweg 6, 14059 Berlin, Germany T: +49 (0) 30 / 3 20 07-136 T: +49 (0) 30 / 3 20 07-0 F: +49 (0) 30 / 3 20 07-107 F: +49 (0) 30 / 3 20 07-111 [email protected] [email protected] www.escpeurope.eu ABSTRACT: This paper sketches important concepts of rationality. It concentrates on bounded ration- ality and provides descriptions of the heuristics and bias program and of the fast and fru- gal heuristics program by Gerd Gigerenzer and colleagues (Gigerenzer, 2002; Gigerenzer, Todd, & the ABC Research Group, 1999; Todd & Gigerenzer, 2000). One objective is to link the underlying concept of ecological rationality in judgment and decision making with the field of management research. This area has been mostly dominated with ideas of the heuristics and biases program coined by Daniel Kahneman and Amos Tversky (2000), with an emphasis of irrationality and lapses of peoples judgments and decisions. After an over- view of the historic development in this debate on rationality, this paper presents a sketch of the fast and frugal heuristic program as well as short impressions from two manage- ment disciplines in order to illustrate the fruitfulness.
    [Show full text]
  • Cooperation in Public Good Games. Calculated Or Confused?
    A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Goeschl, Timo; Lohse, Johannes Working Paper Cooperation in Public Good Games. Calculated or Confused? Discussion Paper Series, No. 626 Provided in Cooperation with: Alfred Weber Institute, Department of Economics, University of Heidelberg Suggested Citation: Goeschl, Timo; Lohse, Johannes (2016) : Cooperation in Public Good Games. Calculated or Confused?, Discussion Paper Series, No. 626, University of Heidelberg, Department of Economics, Heidelberg, http://dx.doi.org/10.11588/heidok.00022247 This Version is available at: http://hdl.handle.net/10419/162969 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die in der dort Content Licence (especially Creative Commons Licences), you genannten Lizenz gewährten Nutzungsrechte. may exercise further usage rights as specified in the indicated licence. www.econstor.eu University of Heidelberg Department of Economics Discussion Paper Series No. 626 Cooperation in Public Good Games.
    [Show full text]
  • Humans Make Best Use of Social Heuristics When Confronting Hard Problems in Large Groups
    Humans make best use of social heuristics when confronting hard problems in large groups Federica Stefanelli1, Enrico Imbimbo1, Daniele Vilone2,3, Franco Bagnoli4, Zoran Levnaji´c5, Andrea Guazzini1 1Department of Education and Psychology, University of Florence, Florence, Italy 2Laboratory of Agent Based Social Simulation, Institute of Cognitive Science and Technology, National Research Council (CNR), Rome, Italy; 3Grupo Interdisciplinar de Sistemas Complejos (GISC), Departamento de Matem´aticas, Universidad Carlos III de Madrid, Spain 4Department of Physics and Astronomy & Center for Study of Complex Dynamics, University of Florence and INFN, Florence, Italy 5Faculty of Information Studies in Novo mesto, Novo Mesto, Slovenia Abstract We report the results of a game-theoretic experiment with human players who solve the problems of increasing complexity by cooperating in groups of increas- ing size. Our experimental environment is set up to make it complicated for players to use rational calculation for making the cooperative decisions. This environment is directly translated into a computer simulation, from which we extract the collaboration strategy that leads to the maximal attainable score. Based on this, we measure the error that players make when estimating the benefits of collaboration, and find that humans massively underestimate these benefits when facing easy problems or working alone or in small groups. In con- trast, when confronting hard problems or collaborating in large groups, humans accurately judge the best level of collaboration and easily achieve the maxi- mal score. Our findings are independent on groups’ composition and players’ personal traits. We interpret them as varying degrees of usefulness of social heuristics, which seems to depend on the size of the involved group and the arXiv:1808.07670v2 [physics.soc-ph] 8 Mar 2019 complexity of the situation.
    [Show full text]
  • Conducting Interactive Experiments Online
    DISCUSSION PAPER SERIES IZA DP No. 10517 Conducting Interactive Experiments Online Antonio A. Arechar Simon Gächter Lucas Molleman JANUARY 2017 DISCUSSION PAPER SERIES IZA DP No. 10517 Conducting Interactive Experiments Online Antonio A. Arechar Lucas Molleman Yale University CeDEx, University of Nottingham and MPI for Human Development Simon Gächter CeDEx, University of Nottingham, CESifo and IZA JANUARY 2017 Any opinions expressed in this paper are those of the author(s) and not those of IZA. Research published in this series may include views on policy, but IZA takes no institutional policy positions. The IZA research network is committed to the IZA Guiding Principles of Research Integrity. The IZA Institute of Labor Economics is an independent economic research institute that conducts research in labor economics and offers evidence-based policy advice on labor market issues. Supported by the Deutsche Post Foundation, IZA runs the world’s largest network of economists, whose research aims to provide answers to the global labor market challenges of our time. Our key objective is to build bridges between academic research, policymakers and society. IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. IZA – Institute of Labor Economics Schaumburg-Lippe-Straße 5–9 Phone: +49-228-3894-0 53113 Bonn, Germany Email: [email protected] www.iza.org IZA DP No. 10517 JANUARY 2017 ABSTRACT Conducting Interactive Experiments Online* Online labor markets provide new opportunities for behavioral research, but conducting economic experiments online raises important methodological challenges.
    [Show full text]
  • Towards a Balanced Social Psychology: Causes, Consequences, and Cures for the Problem-Seeking Approach to Social Behavior and Cognition
    BEHAVIORAL AND BRAIN SCIENCES (2004) 27, 000–000 Printed in the United States of America Towards a balanced social psychology: Causes, consequences, and cures for the problem-seeking approach to social behavior and cognition Joachim I. Krueger Department of Psychology, Brown University, Providence, RI 02912. [email protected] http://www.brown.edu/departments/psychology/faculty/krueger.html David C. Funder Department of Psychology, University of California, Riverside, CA 92506 [email protected] http://www.psych.ucr.edu/faculty/funder/rap/rap.htm Abstract: Mainstream social psychology focuses on how people characteristically violate norms of action through social misbehaviors such as conformity with false majority judgments, destructive obedience, and failures to help those in need. Likewise, they are seen to violate norms of reasoning through cognitive errors such as misuse of social information, self-enhancement, and an over-readiness to at- tribute dispositional characteristics. The causes of this negative research emphasis include the apparent informativeness of norm viola- tion, the status of good behavior and judgment as unconfirmable null hypotheses, and the allure of counter-intuitive findings. The short- comings of this orientation include frequently erroneous imputations of error, findings of mutually contradictory errors, incoherent interpretations of error, an inability to explain the sources of behavioral or cognitive achievement, and the inhibition of generalized the- ory. Possible remedies include increased attention to the complete range of behavior and judgmental accomplishment, analytic reforms emphasizing effect sizes and Bayesian inference, and a theoretical paradigm able to account for both the sources of accomplishment and of error. A more balanced social psychology would yield not only a more positive view of human nature, but also an improved under- standing of the bases of good behavior and accurate judgment, coherent explanations of occasional lapses, and theoretically grounded suggestions for improvement.
    [Show full text]
  • The Dual-Process Approach to Human Sociality 1
    Running head: THE DUAL-PROCESS APPROACH TO HUMAN SOCIALITY 1 The dual-process approach to human sociality: A review Valerio Capraro1 Middlesex University London Correspondence: [email protected] THE DUAL-PROCESS APPROACH TO HUMAN SOCIALITY 2 Abstract Which social decisions are intuitive? Which are deliberative? The dual-process approach to human sociality has emerged in the last decades as a vibrant and exciting area of research. Here, I review the existing literature on the cognitive basis of cooperation, altruism, honesty, positive and negative reciprocity, and (act) utilitarianism. I conclude by introducing a game-theoretical framework that organizes the majority of the empirical regularities. This framework extends Rand and colleagues’ Social Heuristics Hypothesis to any one-shot game G. The core assumption of this “General Social Heuristics Hypothesis” is that, under intuition, people play a Nash equilibrium of the “real analogue of G”, Greal, while under deliberation people play a Nash equilibrium of G. Greal differs from G along two dimensions: G is one-shot, while Greal might be iterated; the payoffs of Greal might be different from the payoffs of G, although they are ordered in (almost) the same way. Keywords: dual-process, pro-sociality, cooperation, altruism, honesty, reciprocity, moral judgments. THE DUAL-PROCESS APPROACH TO HUMAN SOCIALITY 3 The dual-process approach to human sociality: A review We, humans, are unique in the animal kingdom for our capacity to live in large societies made of thousands, if not millions, of unrelated individuals. Bees, ants, and the mole naked rat, for example, live in large societies, but individuals in the same society tend to share a substantial degree of biological relatedness.
    [Show full text]
  • 1 Group Identity As a Social Heuristics: an Experiment With
    Group Identity as a Social Heuristics: An Experiment with Reaction Times Antonio Filippin a & Francesco Guala b Università degli Studi di Milano CLASSIFICATION Major category: Social Sciences Minor category: Economic Sciences. a University of Milan, Department of Economics, Management and Quantitative Methods (DEMM), via Conservatorio 7, 20122 Milan, Italy, and Institute for the Study of Labor (IZA), Schaumburg-Lippe-Str. 5-9, 53113 Bonn, Germany. Email: [email protected]. b University of Milan, Department of Economics, Management and Quantitative Methods (DEMM), via Conservatorio 7, 20122 Milan, Italy. Email: [email protected]. 1 Abstract A large amount of evidence indicates that group identity influences social interactions and, in particular, economic decisions. In this paper we test the hypothesis that group identity triggers social norms or heuristics, using reaction times collected in a series of simple distributive tasks (mini-dictator games). We control for individual preferences using the degree of selfishness expressed in the allocation decisions, and we account for variations in the difficulty of decisions by conditioning on subject’s pro-social inclination. Our results support the heuristic hypothesis: generosity seems to be an effect of ‘fast and frugal’ behavioral rules that simplify decisions, especially when it conflicts with an underlying tendency to behave in a self-interested manner. In the language of ‘dual-process’ theories, group identity triggers ‘System 1’ processes that facilitate choice and override slow, calculative decision-making. Significance Groups play an important role in human sociality and human evolution. As a consequence, the capacity to identify group membership is a crucial cognitive skill that we constantly use to modulate our social interactions.
    [Show full text]
  • Social Environment Shapes the Speed of Cooperation Nishi, Akihiro; Christakis, Nicholas; Evans, A.M.; O'malley, James; Rand, David
    Tilburg University Social environment shapes the speed of cooperation Nishi, Akihiro; Christakis, Nicholas; Evans, A.M.; O'Malley, James; Rand, David Published in: Scientific Reports DOI: 10.1038/srep29622 Publication date: 2016 Link to publication in Tilburg University Research Portal Citation for published version (APA): Nishi, A., Christakis, N., Evans, A. M., O'Malley, J., & Rand, D. (2016). Social environment shapes the speed of cooperation. Scientific Reports, 6, [29622]. https://doi.org/10.1038/srep29622 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Download date: 30. sep. 2021 www.nature.com/scientificreports OPEN Social Environment Shapes the Speed of Cooperation Akihiro Nishi1,2,3, Nicholas A. Christakis2,3,4,5, Anthony M. Evans6, A. James O’Malley7,8 & David G. Rand2,9,10 Received: 17 May 2016 Are cooperative decisions typically made more quickly or slowly than non-cooperative decisions? Accepted: 16 June 2016 While this question has attracted considerable attention in recent years, most research has focused Published: 20 July 2016 on one-shot interactions.
    [Show full text]
  • 1 Dual Process Utility Theory
    DUAL PROCESS UTILITY THEORY: A MODEL OF DECISIONS UNDER RISK AND OVER TIME* BY MARK SCHNEIDER This Version: January 25, 2018 ABSTRACT. The Discounted Expected Utility model has been a major workhorse for analyzing individual behavior for over half a century. However, it cannot account for evidence that risk interacts with time preference, that time interacts with risk preference, that many people are averse to timing risk and do not discount the future exponentially, that discounting depends on the magnitude of outcomes, that risk preferences are not time preferences, and that risk and time preferences are correlated with cognitive reflection. Here we address these issues in a decision model based on the interaction of an affective and a reflective valuation process. The resulting Dual Process Utility theory provides a unified approach to modeling risk preference, time preference, and interactions between risk and time preferences. It also provides a unification of models based on a rational economic agent, models based on prospect theory or rank-dependent utility, and dual system models of decision making. We conclude by demonstrating that a simple extension of the model provides a unified approach to explaining empirical violations of ‘dimensional independence’ across the domains of risk, time, and social preferences. Such violations of dimensional independence challenge the leading normative and behavioral models of decision making. Keywords: Risk preferences; Time preferences; Social preferences; System 1; System 2 JEL Codes: D01, D03, D81, D90. * Economic Science Institute, Chapman University. One University Drive, Orange, CA 92866. (Phone: (714) 744-7083; Fax: (714) 628-2881; e-mail: [email protected]).
    [Show full text]
  • Social Heuristics Shape Intuitive Cooperation
    ARTICLE Received 17 Oct 2013 | Accepted 17 Mar 2014 | Published 22 Apr 2014 DOI: 10.1038/ncomms4677 Social heuristics shape intuitive cooperation David G. Rand1,2,3,*, Alexander Peysakhovich1,4,*, Gordon T. Kraft-Todd1, George E. Newman3, Owen Wurzbacher1, Martin A. Nowak4,5,6 & Joshua D. Greene7 Cooperation is central to human societies. Yet relatively little is known about the cognitive underpinnings of cooperative decision making. Does cooperation require deliberate self-restraint? Or is spontaneous prosociality reined in by calculating self-interest? Here we present a theory of why (and for whom) intuition favors cooperation: cooperation is typically advantageous in everyday life, leading to the formation of generalized cooperative intuitions. Deliberation, by contrast, adjusts behaviour towards the optimum for a given situation. Thus, in one-shot anonymous interactions where selfishness is optimal, intuitive responses tend to be more cooperative than deliberative responses. We test this ‘social heuristics hypothesis’ by aggregating across every cooperation experiment using time pressure that we conducted over a 2-year period (15 studies and 6,910 decisions), as well as performing a novel time pressure experiment. Doing so demonstrates a positive average effect of time pressure on cooperation. We also find substantial variation in this effect, and show that this variation is partly explained by previous experience with one-shot lab experiments. 1 Department of Psychology, Yale University, New Haven, Connecticut 06511, USA. 2 Department of Economics, Yale University, New Haven, Connecticut 06511, USA. 3 Yale School of Management, Yale University, New Haven, Connecticut 06511, USA. 4 Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachusetts 02138, USA.
    [Show full text]
  • Adaptive Foundations of Heroism: Social Heuristics Push Advantageous Everyday Ethical Behavior to Heroic Extremes
    Adaptive foundations of heroism: Social heuristics push advantageous everyday ethical behavior to heroic extremes Gordon T. Kraft-Todd & David G. Rand Department of Psychology, Yale University Appears in Handbook of Heroism and Heroic Leadership (2016) Eds. Allison ST, Goethals G, Kramer R. London, UK: Routledge Publishing. ISBN 978113891565. We argue that heroism is typically adaptive everyday ethical behavior taken to the extreme by over-generalization. We discuss three types of ethical principles with the properties of being cooperative, adaptive in the context of everyday life, but not in one’s self-interest when taken to the extreme: justice—behaviors concerned with fairly distributing resources; solidarity—behaviors concerned with group-beneficial self-sacrifice; and pacifism—behaviors concerned with the avoidance of harming others. Because these behaviors are typically individually adaptive, they become automatized as social heuristics. These heuristics may then be (mis)applied in settings where cooperating is long-run costly to the individual, resulting in heroism. The potential to be a hero is in all of us. This is no mere platitude; it reflects a deep and simple truth: heroism is an extreme form of everyday ethical behavior. Heroes, by our definition, are people who make great personal sacrifices for the benefit of others. From an evolutionary perspective, heroes have a mysterious origin story: how did the “self-interested” process of natural selection give rise to self-sacrifice? Extreme self-sacrificing behavior seems particularly maladaptive: wouldn’t heroes have died out by now? We will argue that this puzzle can be resolved by considering the evolutionary logic supporting milder forms of self-sacrifice, the sort of ethics we see in our everyday lives.
    [Show full text]