Influence of Cognitive Biases in Distorting Decision Making and Leading to Critical Unfavorable Incidents
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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). -
The Status Quo Bias and Decisions to Withdraw Life-Sustaining Treatment
HUMANITIES | MEDICINE AND SOCIETY The status quo bias and decisions to withdraw life-sustaining treatment n Cite as: CMAJ 2018 March 5;190:E265-7. doi: 10.1503/cmaj.171005 t’s not uncommon for physicians and impasse. One factor that hasn’t been host of psychological phenomena that surrogate decision-makers to disagree studied yet is the role that cognitive cause people to make irrational deci- about life-sustaining treatment for biases might play in surrogate decision- sions, referred to as “cognitive biases.” Iincapacitated patients. Several studies making regarding withdrawal of life- One cognitive bias that is particularly show physicians perceive that nonbenefi- sustaining treatment. Understanding the worth exploring in the context of surrogate cial treatment is provided quite frequently role that these biases might play may decisions regarding life-sustaining treat- in their intensive care units. Palda and col- help improve communication between ment is the status quo bias. This bias, a leagues,1 for example, found that 87% of clinicians and surrogates when these con- decision-maker’s preference for the cur- physicians believed that futile treatment flicts arise. rent state of affairs,3 has been shown to had been provided in their ICU within the influence decision-making in a wide array previous year. (The authors in this study Status quo bias of contexts. For example, it has been cited equated “futile” with “nonbeneficial,” The classic model of human decision- as a mechanism to explain patient inertia defined as a treatment “that offers no rea- making is the rational choice or “rational (why patients have difficulty changing sonable hope of recovery or improvement, actor” model, the view that human beings their behaviour to improve their health), or because the patient is permanently will choose the option that has the best low organ-donation rates, low retirement- unable to experience any benefit.”) chance of satisfying their preferences. -
Ambiguity Seeking As a Result of the Status Quo Bias
Ambiguity Seeking as a Result of the Status Quo Bias Mercè Roca 1, Robin M. Hogarth 2, A. John Maule 3 1ESRC Postgraduate Researcher, Centre for Decision Research, Leeds University Business School, The University of Leeds, Leeds, LS2 9JT, United Kingdom 2ICREA Research Professor, Departament d’Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 08005, Barcelona, Spain 3Professor, Centre for Decision Research, Leeds University Business School, The University of Leeds, Leeds, LS2 9JT, United Kingdom Contact details: Mercè Roca, [email protected] , Telephone: (0044)07709557423. Leeds University Business School, Maurice Keyworth Building. The University of Leeds, Leeds, LS2 9JT, United Kingdom * Funds for the experiments were provided by the Centre for Decision Research of Leeds University Business School. The authors are grateful for the comments received from Gaëlle Villejoubert, Albert Satorra and Peter Wakker. This paper was presented at SPUDM20 in Stockholm. 1 Abstract Several factors affect attitudes toward ambiguity. What happens, however, when people are asked to exchange an ambiguous alternative in their possession for an unambiguous one? We present three experiments in which individuals preferred to retain the former. This status quo bias emerged both within- and between-subjects, with and without incentives, with different outcome distributions, and with endowments determined by both the experimenter and the participants themselves. Findings emphasize the need to account for the frames of reference under which evaluations of probabilistic information take place as well as modifications that should be incorporated into descriptive models of decision making. Keywords Ambiguity, risk, status quo bias, decision making, uncertainty. JEL code: C91, D81. 2 The phenomenon of ambiguity aversion – or the preference for gambles with known as opposed to unknown probabilities – has been well documented in the literature on decision making in both psychology and economics (see, e.g., Ellsberg, 1961; Camerer & Weber, 1992; Keren & Gerritsen, 1999). -
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, -
Perceptions of Teacher Expectations Among First and Second
Digital Commons @ George Fox University Doctor of Education (EdD) Theses and Dissertations 12-1-2016 Student Voice: Perceptions of Teacher Expectations Among First and Second Generation Vietnamese and Mexican Students Sara Gandarilla George Fox University, [email protected] This research is a product of the Doctor of Education (EdD) program at George Fox University. Find out more about the program. Recommended Citation Gandarilla, Sara, "Student Voice: Perceptions of Teacher Expectations Among First and Second Generation Vietnamese and Mexican Students" (2016). Doctor of Education (EdD). 90. http://digitalcommons.georgefox.edu/edd/90 This Dissertation is brought to you for free and open access by the Theses and Dissertations at Digital Commons @ George Fox University. It has been accepted for inclusion in Doctor of Education (EdD) by an authorized administrator of Digital Commons @ George Fox University. For more information, please contact [email protected]. STUDENT VOICE: PERCEPTIONS OF TEACHER EXPECTATIONS AMONG FIRST AND SECOND GENERATION VIETNAMESE AND MEXICAN STUDENTS By SARA GANDARILLA FACULTY RESEARCH COMMITTEE: Chair: Terry Huffman, Ph.D. Members: Ginny Birky, Ph.D. and Tatiana Cevallos, Ed.D. Presented to the College of Education, George Fox University In partial fulfillment of the requirements for the degree of Doctor of Education December 7, 2016 ii ABSTRACT This qualitative research study explored the perceptions first and second generation Vietnamese and Mexican high school students hold on teacher expectations based on their racial identity. Specifically, this study explores the critical concepts of stereotype threat, halo effect, and self-fulfilling prophecy. The primary purpose of this investigation was to enhance the understanding of how the perception students have impacts success or lack of success for two different student groups. -
A Neural Network Framework for Cognitive Bias
fpsyg-09-01561 August 31, 2018 Time: 17:34 # 1 HYPOTHESIS AND THEORY published: 03 September 2018 doi: 10.3389/fpsyg.2018.01561 A Neural Network Framework for Cognitive Bias Johan E. Korteling*, Anne-Marie Brouwer and Alexander Toet* TNO Human Factors, Soesterberg, Netherlands Human decision-making shows systematic simplifications and deviations from the tenets of rationality (‘heuristics’) that may lead to suboptimal decisional outcomes (‘cognitive biases’). There are currently three prevailing theoretical perspectives on the origin of heuristics and cognitive biases: a cognitive-psychological, an ecological and an evolutionary perspective. However, these perspectives are mainly descriptive and none of them provides an overall explanatory framework for the underlying mechanisms of cognitive biases. To enhance our understanding of cognitive heuristics and biases we propose a neural network framework for cognitive biases, which explains why our brain systematically tends to default to heuristic (‘Type 1’) decision making. We argue that many cognitive biases arise from intrinsic brain mechanisms that are fundamental for the working of biological neural networks. To substantiate our viewpoint, Edited by: we discern and explain four basic neural network principles: (1) Association, (2) Eldad Yechiam, Technion – Israel Institute Compatibility, (3) Retainment, and (4) Focus. These principles are inherent to (all) neural of Technology, Israel networks which were originally optimized to perform concrete biological, perceptual, Reviewed by: and motor functions. They form the basis for our inclinations to associate and combine Amos Schurr, (unrelated) information, to prioritize information that is compatible with our present Ben-Gurion University of the Negev, Israel state (such as knowledge, opinions, and expectations), to retain given information Edward J. -
Cognitive Bias in Emissions Trading
sustainability Article Cognitive Bias in Emissions Trading Jae-Do Song 1 and Young-Hwan Ahn 2,* 1 College of Business Administration, Chonnam National University, Gwangju 61186, Korea; [email protected] 2 Korea Energy Economics Institute, 405-11 Jongga-ro, Jung-gu, Ulsan 44543, Korea * Correspondence: [email protected]; Tel.: +82-52-714-2175; Fax: +82-52-714-2026 Received: 8 February 2019; Accepted: 27 February 2019; Published: 5 March 2019 Abstract: This study investigates whether cognitive biases such as the endowment effect and status quo bias occur in emissions trading. Such cognitive biases can serve as a barrier to trade. This study’s survey-based experiments, which include hypothetical emissions trading scenarios, show that the endowment effect does occur in emissions trading. The status quo bias occurs in only one of the three experiments. This study also investigates whether accumulation of experience can reduce cognitive bias as discovered preference hypothesis expects. The results indicate that practitioners who are supposed to have more experience show no evidence of having less cognitive bias. Contrary to the conventional expectation, the practitioners show significantly higher level of endowment effect than students and only the practitioners show a significant status quo bias. A consignment auction situation, which is used in California’s cap-and-trade program, is also tested; no significant difference between general permission trading and consignment auctions is found. Keywords: emissions trading; cognitive bias; consignment auction; climate policy 1. Introduction Emissions trading allows entities to achieve emission reduction targets in a cost-effective way through buying and selling emission allowances in emissions trading markets [1,2]. -
Positive Stereotypes, Negative Outcomes: Reminders of the Positive Components of Complementary Gender Stereotypes Impair Perform
1 British Journal of Social Psychology (2018) © 2018 The British Psychological Society www.wileyonlinelibrary.com Positive stereotypes, negative outcomes: Reminders of the positive components of complementary gender stereotypes impair performance in counter-stereotypical tasks Rotem Kahalon1* , Nurit Shnabel1 and Julia C. Becker2 1Tel-Aviv University, Israel 2Osnabruck University, Germany Gender stereotypes are complementary: Women are perceived to be communal but not agentic, whereas men are perceived to be agentic but not communal. The present research tested whether exposure to reminders of the positive components of these gender stereotypes can lead to stereotype threat and subsequent performance deficits on the complementary dimension. Study 1 (N = 116 female participants) revealed that compared to a control/no-stereotype condition, exposure to reminders of the stereotype about women’s communality (but not to reminders of the stereotype about women’s beauty) impaired women’s math performance. In Study 2 (N = 86 male participants), reminders of the stereotype about men’s agency (vs. a control/no- stereotype condition) impaired men’s performance in a test of socio-emotional abilities. Consistent with previous research on stereotype threat, in both studies the effect was evident among participants with high domain identification. These findings extend our understanding of the potentially adverse implications of seemingly positive gender stereotypes. While the message that negative stereotypes are anti-egalitarian and socially unacceptable is reinforced in contemporary Western society, positive stereotypes are prevalent and considered socially acceptable (Czopp, Kay, & Cheryan, 2015). The present research tested whether, despite their subjectively positive tone, positive gender stereotypes might lead to negative outcomes. In particular, we examined whether highlighting the positive stereotypes about women’s communality and men’s agency can lead to stereotype threat effects. -
Communication Science to the Public
David M. Berube North Carolina State University ▪ HOW WE COMMUNICATE. In The Age of American Unreason, Jacoby posited that it trickled down from the top, fueled by faux-populist politicians striving to make themselves sound approachable rather than smart. (Jacoby, 2008). EX: The average length of a sound bite by a presidential candidate in 1968 was 42.3 seconds. Two decades later, it was 9.8 seconds. Today, it’s just a touch over seven seconds and well on its way to being supplanted by 140/280- character Twitter bursts. ▪ DATA FRAMING. ▪ When asked if they truly believe what scientists tell them, NEW ANTI- only 36 percent of respondents said yes. Just 12 percent expressed strong confidence in the press to accurately INTELLECTUALISM: report scientific findings. ▪ ROLE OF THE PUBLIC. A study by two Princeton University researchers, Martin TRENDS Gilens and Benjamin Page, released Fall 2014, tracked 1,800 U.S. policy changes between 1981 and 2002, and compared the outcome with the expressed preferences of median- income Americans, the affluent, business interests and powerful lobbies. They concluded that average citizens “have little or no independent influence” on policy in the U.S., while the rich and their hired mouthpieces routinely get their way. “The majority does not rule,” they wrote. ▪ Anti-intellectualism and suspicion (trends). ▪ Trump world – outsiders/insiders. ▪ Erasing/re-writing history – damnatio memoriae. ▪ False news. ▪ Infoxication (CC) and infobesity. ▪ Aggregators and managed reality. ▪ Affirmation and confirmation bias. ▪ Negotiating reality. ▪ New tribalism is mostly ideational not political. ▪ Unspoken – guns, birth control, sexual harassment, race… “The amount of technical information is doubling every two years. -
Understanding Outcome Bias ∗
Understanding Outcome Bias ∗ Andy Brownbacky Michael A. Kuhnz University of Arkansas University of Oregon January 31, 2019 Abstract Disentangling effort and luck is critical when judging performance. In a principal-agent experiment, we demonstrate that principals' judgments of agent effort are biased by luck, despite perfectly observing the agent's effort. This bias can erode the power of incentives to stimulate effort when there is noise in the outcome process. As such, we explore two potential solutions to this \outcome bias" { control over irrelevant information about luck, and outsourcing judgment to independent third parties. We find that both are ineffective. When principals have control over information about luck, they do not avoid the information that biases their judgment. In contrast, when agents have control over the principal's information about luck, agents strategically manipulate principals' outcome bias to minimize their punishments. We also find that independent third parties are just as biased as principals. These findings indicate that outcome bias may be more widespread and pernicious than previously understood. They also suggest that outcome bias cannot be driven solely by disappointment nor by distributional preferences. Instead, we hypothesize that luck directly affects beliefs about agents even though effort is perfectly observed. We elicit the beliefs of third parties and principals and find that lucky agents are believed to exert more effort in general than identical, unlucky agents. JEL Classification: C92, D63, D83 Keywords: Experiment, Reciprocity, Outcome Bias, Attribution Bias, Blame ∗We wish to thank Gary Charness, Ryan Oprea, Peter Kuhn, Joshua Miller, Justin Rao, and James Andreoni for valuable feedback. -
Safe-To-Fail Probe Has…
Liz Keogh [email protected] If a project has no risks, don’t do it. @lunivore The Innovaon Cycle Spoilers Differentiators Commodities Build on Cynefin Complex Complicated sense, probe, analyze, sense, respond respond Obvious Chaotic sense, act, categorize, sense, respond respond With thanks to David Snowden and Cognitive Edge EsBmang Complexity 5. Nobody has ever done it before 4. Someone outside the org has done it before (probably a compeBtor) 3. Someone in the company has done it before 2. Someone in the team has done it before 1. We all know how to do it. Esmang Complexity 5 4 3 Analyze Probe (Break it down) (Try it out) 2 1 Fractal beauty Feature Scenario Goal Capability Story Feature Scenario Vision Story Goal Code Capability Feature Code Code Scenario Goal A Real ProjectWhoops, Don’t need forgot this… Can’t remember Feature what this Scenario was for… Goal Capability Story Feature Scenario Vision Story Goal Code Capability Feature Code Code Scenario Goal Oops, didn’t know about Look what I that… found! A Real ProjectWhoops, Don’t need forgot this… Can’t remember Um Feature what this Scenario was for… Goal Oh! Capability Hmm! Story FeatureOoh, look! Scenario Vision Story GoalThat’s Code funny! Capability Feature Code Er… Code Scenario Dammit! Oops! Oh F… InteresBng! Goal Sh..! Oops, didn’t know about Look what I that… found! We are uncovering be^er ways of developing so_ware by doing it Feature Scenario Goal Capability Story Feature Scenario Vision Story Goal Code Capability Feature Code Code Scenario Goal We’re discovering how to