Bias and Heuristics

2020 ◽  
pp. 119-126
Author(s):  
Thomas Boraud
Keyword(s):  
Cognitive Bias ◽  
Automatic System ◽  
Cognitive Biases ◽  
Dilution Effect ◽  
Herbert Simon ◽  
Anchoring Effect ◽  
First Impression ◽  
Human Decision ◽  
System 2 ◽  
System 1

This chapter addresses the cognitive bias and heuristics of judgement. It also considers possible underlying neural mechanisms. Economist Herbert Simon introduced the notion of heuristics in judgement to define the approximate rational rules upon which individuals rely to make decisions. Experimental psychologists Daniel Kahneman and Amos Tversky transformed this notion of heuristics by highlighting the cognitive biases that influence judgements. From his work with Tversky, Kahneman elaborated the two-systems theory. According to him, human decision-making is the result of a competition between a fast, automatic system (System 1) that is prone to make mistakes and a slower, more demanding but also more reliable one (System 2). Both systems use heuristics, but the second compensates with anticipation. This chapter then looks at initial bias and beliefs. It also explains the anchoring effect, as well as the dilution effect. Anchoring is the excessive influence of a first impression on judgements.

Cognitive Biases in Decision Making in Post-Bureaucratic Organizations

2017 ◽  
pp. 358-382
Author(s):  
Marie-Therese Claes ◽  
Thibault Jacquemin
Keyword(s):  
Decision Making ◽  
Behavioral Economics ◽  
Cognitive Biases ◽  
Rational Choice Theory ◽  
Choice Theory ◽  
Decision Making Process ◽  
Rational Decision ◽  
Bureaucratic Organization ◽  
System 2 ◽  
System 1

In today's post-bureaucratic organization, where decision-making is decentralized, most managers are confronted with highly complex situations where time-constraint and availability of information makes the decision-making process essential. Studies show that a great amount of decisions are not taken after a rational decision-making process but rather rely on instinct, emotion or quickly processed information. After briefly describing the journey of thoughts from Rational Choice Theory to the emergence of Behavioral Economics, this chapter will elaborate on the mechanisms that are at play in decision-making in an attempt to understand the root causes of cognitive biases, using the theory of Kahneman's (2011) System 1 and System 2. It will discuss the linkage between the complexity of decision-making and post-bureaucratic organization.

Rational Versus Intuitive Processing

2019 ◽  
Vol 31 (1) ◽  
pp. 2-11 ◽  
Author(s):  
Marina Krcmar ◽  
Allison Eden
Keyword(s):  
Experimental Design ◽  
Cognitive Load ◽  
Automatic System ◽  
Cognitive Systems ◽  
Moral Foundations ◽  
Moral Foundations Theory ◽  
Moral Foundation ◽  
Rational System ◽  
System 2 ◽  
System 1

Abstract. This study explored two main theoretical propositions. First, we tested Hartmann’s (2011 , 2012 ) notion that video games are processed via two separate cognitive systems: System 1, the automatic system, and System 2, the rational system. Specifically, we used a cognitive load manipulation to test if intuitive moral responses such as guilt and anthropomorphism are processed in System 1. Second, we utilized moral foundations theory to test the effect of care salience on guilt and in-game aggression. Using an experimental design ( n = 94), the results indicate that under conditions of cognitive load, players had somewhat lower in-game aggression. Effects on guilt and anthropomorphism were in the same direction, albeit with small effects. In terms of moral foundations, we found that care salience was not negatively related to in-game aggression but was directly related to guilt, indicating that greater emphasis on the moral foundation of care resulted in greater guilt. Also, anthropomorphism was positively related to experienced guilt and negatively related to in-game aggression.

The Electronic Hive Mind and Cybersecurity

2019 ◽  
pp. 206-262 ◽  
Author(s):  
Shalin Hai-Jew
Keyword(s):  
Decision Making ◽  
Cognitive Biases ◽  
Mass Scale ◽  
Data Sources ◽  
Micro Scale ◽  
Weakest Link ◽  
System 2 ◽  
Research Questions ◽  
System 1 ◽  
Scale Data

If people are the “weakest link” in cybersecurity because of their psychological make-up and hardwiring—their socialized desire to trust and cooperate with others, their cognitive biases and misperceptions, their preferences for convenience, their general going with System 1 inattention instead of System 2 attention and thinking—this begs the question of whether the same micro-scale cognitive limits found in individual users are also present on a mass scale. After all, there have been discovered problematic unthinking leanings in group decision making: obedience to authority, bystander effects, groupthink, and the Abilene paradox, among others. Using a range of often mass-scale data sources and data analytics tools, research questions were asked around three areas: (1) the level of sophistication of the cybersecurity electronic hive mind towards cybersecurity issues, (2) the gap between the non-expert members and the expert members in the hive mind, and (3) whether the extant hive mind was more reflective of mob unthinkingness or deliberation and wisdom.

Giving reasons as a means to enhance compliance with legal norms

2021 ◽  
Author(s):  
Daphna Lewinsohn-Zamir ◽  
Eyal Zamir ◽  
Ori Katz
Keyword(s):  
Automatic System ◽  
Theoretical Discussion ◽  
Policy Makers ◽  
Legal Norms ◽  
Theoretical Part ◽  
Deliberative System ◽  
System 2 ◽  
Enforcement Mechanisms ◽  
System 1

The threat of sanctions is often insufficient to ensure compliance with legal norms. Recently, much attention has been given to nudges – choice-preserving measures that take advantage of people’s automatic System 1 thinking – as a means of influencing behaviour without sanctions, but nudges are often ineffective and controversial. This article explores the provision of information about the reasons underlying legal norms, as a means to enhance compliance, primarily through deliberative System 2 thinking. While the idea that legal norms should be accompanied by explanatory preambles – to complement the law’s threat of sanctions with persuasion – goes back to Plato, this technique is not commonly used nowadays, and scholars have failed to systematically consider this possibility. The article argues that reason giving can enhance compliance and reduce the need for costly enforcement mechanisms. The theoretical part of the article comprises three parts. It first describes the mechanisms through which reasons may influence people’s behaviour. It then distinguishes between reason giving as a means to enhance compliance and as a means to attain other goals and between reason giving and related means to enhance compliance. Finally, it discusses various policy and pragmatic considerations that bear on the use of reason giving. Following the theoretical discussion, the empirical part of the article uses vignette studies to demonstrate the feasibility and efficacy of the reason-giving technique. The results of these new studies show that providing good reasons for legal norms enhances people’s inclination to comply with them, in comparison to not providing the reasons underlying the norms. However, whereas persuasive reasons may promote compliance, questionable reasons might reduce it. We call on scholars and policy makers to pay more attention to this readily available measure of enhancing compliance with norms.

scholarly journals Cognitive bias: how understanding its impact on antibiotic prescribing decisions can help advance antimicrobial stewardship

2020 ◽  
Vol 2 (4) ◽  
Author(s):  
Bradley J Langford ◽  
Nick Daneman ◽  
Valerie Leung ◽  
Dale J Langford
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Healthcare Setting ◽  
Hyperbolic Discounting ◽  
Antibiotic Prescribing ◽  
Support Tools ◽  
Human Decision

Abstract The way clinicians think about decision-making is evolving. Human decision-making shifts between two modes of thinking, either fast/intuitive (Type 1) or slow/deliberate (Type 2). In the healthcare setting where thousands of decisions are made daily, Type 1 thinking can reduce cognitive load and help ensure decision making is efficient and timely, but it can come at the expense of accuracy, leading to systematic errors, also called cognitive biases. This review provides an introduction to cognitive bias and provides explanation through patient vignettes of how cognitive biases contribute to suboptimal antibiotic prescribing. We describe common cognitive biases in antibiotic prescribing both from the clinician and the patient perspective, including hyperbolic discounting (the tendency to favour small immediate benefits over larger more distant benefits) and commission bias (the tendency towards action over inaction). Management of cognitive bias includes encouraging more mindful decision making (e.g., time-outs, checklists), improving awareness of one’s own biases (i.e., meta-cognition), and designing an environment that facilitates safe and accurate decision making (e.g., decision support tools, nudges). A basic understanding of cognitive biases can help explain why certain stewardship interventions are more effective than others and may inspire more creative strategies to ensure antibiotics are used more safely and more effectively in our patients.

scholarly journals Anchoring Effect as A Cognitive Bias: An Example of a Classroom Experiment

2020 ◽  
Vol 7 (3) ◽  
pp. 608-629
Author(s):  
Mehmet SEVGIN
Keyword(s):  
Economic Theory ◽  
Behavioral Economics ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Primary Sources ◽  
Anchoring Effect ◽  
Classroom Experiment ◽  
The Mean ◽  
Biases And Heuristics

Over the last decades, standard economic assumptions are questioned due to some empirical violation examples of the rationality principle in economic theory. Behavioral economists suggest that it is more realistic to call individuals and firms "bounded rational" than rational to solve this inconsistency. Hence, one of the primary sources of these rationalities comes from cognitive biases and heuristics, according to many psychologies and behavioral economics studies. It is assumed that anchoring effect is one of the most robust cognitive biases since it might occur without the individual's awareness. In this study, anchoring effect as a cognitive bias is analyzed with its theoretical and psychological background. In the last section of the study, the findings of a class experiment are presented and discussed. According to the results, when the anchoring effect increases, the anchors' impact on the mean estimations of the subjects also increases. Moreover, when the subjects are explicitly directed to the anchor value, anchoring effect is more influential than a regular incidental anchoring effect. Hence, increases in anchoring effect result in a larger influence on the estimations of the subjects.

The Role of Cognitive Bias in Breast Radiology Diagnostic and Judgment Errors

2020 ◽  
Vol 2 (4) ◽  
pp. 382-389
Author(s):  
Vilert A Loving ◽  
Elizabeth M Valencia ◽  
Bhavika Patel ◽  
Brian S Johnston
Keyword(s):  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Organizational Level ◽  
Individual Level ◽  
Gambler’S Fallacy ◽  
Satisfaction Of Search ◽  
Human Decision ◽  
The Individual

Abstract Cognitive bias is an unavoidable aspect of human decision-making. In breast radiology, these biases contribute to missed or erroneous diagnoses and mistaken judgments. This article introduces breast radiologists to eight cognitive biases commonly encountered in breast radiology: anchoring, availability, commission, confirmation, gambler’s fallacy, omission, satisfaction of search, and outcome. In addition to illustrative cases, this article offers suggestions for radiologists to better recognize and counteract these biases at the individual level and at the organizational level.

scholarly journals A neural network framework for cognitive bias

2017 ◽  
Author(s):  
J. E. Korteling ◽  
Anne-Marie Brouwer ◽  
Alexander Toet
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Decision Making ◽  
Cognitive Bias ◽  
Cognitive Biases ◽  
Relevant Information ◽  
Theoretical Perspectives ◽  
Human Decision ◽  
Underlying Mechanisms

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. In order to substantiate our viewpoint, we discern and explain four basic neural network principles: (1) Association, (2) Compatibility (3) Retainment, and (4) Focus. These principles are inherent to (all) neural networks which were originally optimized to perform concrete biological, perceptual, and motor functions. They form the basis for our inclinations to associate and combine (unrelated) information, to prioritize information that is compatible with our present state (such as knowledge, opinions and expectations), to retain given information that sometimes could better be ignored, and to focus on dominant information while ignoring relevant information that is not directly activated. The supposed mechanisms are complementary and not mutually exclusive. For different cognitive biases they may all contribute in varying degrees to distortion of information. The present viewpoint not only complements the earlier three viewpoints, but also provides a unifying and binding framework for many cognitive bias phenomena.

scholarly journals Milk Production, Body Weight, Body Condition Score, Activity, and Rumination of Organic Dairy Cattle Grazing Two Different Pasture Systems Incorporating Cool- and Warm-Season Forages

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 264
Author(s):  
Kathryn E. Ritz ◽  
Bradley J. Heins ◽  
Roger D. Moon ◽  
Craig C. Sheaffer ◽  
Sharon L. Weyers
Keyword(s):  
Body Weight ◽  
Milk Production ◽  
Body Condition Score ◽  
Warm Season ◽  
Cool Season ◽  
Organic Dairy ◽  
Condition Score ◽  
Annual Grasses ◽  
System 2 ◽  
System 1

Organic dairy cows were used to evaluate the effect of two organic pasture production systems (temperate grass species and warm-season annual grasses and cool-season annuals compared with temperate grasses only) across two grazing seasons (May to October of 2014 and 2015) on milk production, milk components (fat, protein, milk urea nitrogen (MUN), somatic cell score (SCS)), body weight, body condition score (BCS), and activity and rumination (min/day). Cows were assigned to two pasture systems across the grazing season at an organic research dairy in Morris, Minnesota. Pasture System 1 was cool-season perennials (CSP) and Pasture System 2 was a combination of System 1 and warm-season grasses and cool-season annuals. System 1 and System 2 cows had similar milk production (14.7 and 14.8 kg d−1), fat percentage (3.92% vs. 3.80%), protein percentage (3.21% vs. 3.17%), MUN (12.5 and 11.5 mg dL−1), and SCS (4.05 and 4.07), respectively. Cows in System 1 had greater daily rumination (530 min/day) compared to cows in System 2 (470 min/day). In summary, warm-season annual grasses may be incorporated into grazing systems for pastured dairy cattle.

scholarly journals Comparison of Three Fungicide Spray Advisories for Lettuce Downy Mildew

Plant Disease ◽  
2001 ◽  
Vol 85 (8) ◽  
pp. 895-900 ◽  
Author(s):  
B. M. Wu ◽  
K. V. Subbarao ◽  
A. H. C. van Bruggen ◽  
S. T. Koike
Keyword(s):  
Downy Mildew ◽  
Drip Irrigation ◽  
Leaf Wetness ◽  
Lettuce Downy Mildew ◽  
Advisory System ◽  
System 2 ◽  
Forecasting System ◽  
Low Incidence ◽  
System 1 ◽  
First Time

Lettuce growers in coastal California have relied mainly on protective fungicide sprays to control downy mildew. Thus, timing of sprays before infection is critical for optimal results. A leaf-wetness-driven, infection-based advisory system, previously developed, did not always perform satisfactorily. In this study, the advisory system was modified by incorporating a pathogen survival component (system 1) or both survival and sporulation components (system 2). These systems were then evaluated in commercial lettuce fields in coastal California during 1996-1998. Three or four treatments were carried out in each field: (i) no spray; (ii) sprays as scheduled by the growers; (iii) sprays following modified system 1; and (iv) sprays following the original advisory system (1996) or modified system 2 (1998). Downy mildew incidence was evaluated every 2 to 9 days. In fields with drip irrigation, the number of fungicide applications was reduced by one or two regardless of the advisory system used compared to the grower's calendar-based schedule, although one unnecessary spray was recommended in 1996 at Soledad and 1997 at Salinas. Under all three systems, disease levels were low (incidence <25% and about 1 lesion per plant) for fields with drip irrigation, but not for fields with sprinklers (incidence up to 100% and 5 to 10 lesions per plant). For the first time, we established that survival and sporulation components are not needed for a lettuce downy mildew forecasting system. Instead, a threshold with a shorter period of morning leaf wetness and high temperatures were found to have potential for improving forecasting efficiency.

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