Confirmation bias, as the term is typically used in the psychological literature, connotes the seeking or interpreting of evidence in ways that are partial to existing beliefs, expectations, or a h...

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Confirmation Bias: A Ubiquitous Phenomenon in Many Guises:

In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

Theoretical models of financial markets built on the assumption that some investors are overconfident yield one central prediction: overconfident investors will trade too much. We test this prediction by partitioning investors on the basis of a variable that provides a natural proxy for overconfidence--gender. Psychological research has established that men are more prone to overconfidence than women. Thus, models of investor overconfidence predict that men will trade more and perform worse than women. Using account data for over 35,000 households from a large discount brokerage firm, we analyze the common stock investments of men and women from February 1991 through January 1997. Consistent with the predictions of the overconfidence models, we document that men trade 45 percent more than women and earn annual risk-adjusted net returns that are 1.4 percent less than those earned by women. These differences are more pronounced between single men and single women; single men trade 67 percent more than single women and earn annual risk-adjusted net returns that are 2.3 percent less than those earned by single women.

https://papers.ssrn.com/sol3/Delivery.cfm/98110615.pdf?abstractid=139415&rulid=175370&mirid=3

Boys Will Be Boys: Gender, Overconfidence, and Common Stock Investment

Theoretical models predict that overconedent investors trade excessively We test this prediction by partitioning investors on gender Psychological research demonstrates that, in areas such as enance, men are more overconedent than women Thus, theory predicts that men will trade more excessively than women Using account data for over 35,000 households from a large discount brokerage, we analyze the common stock investments of men and women from February 1991 through January 1997 We document that men trade 45 percent more than women Trading reduces men’s net returns by 265 percentage points a year as opposed to 172 percentage points for women It’s not what a man don’t know that makes him a fool, but what he does know that ain’t so Josh Billings, nineteenth century American humorist It is difecult to reconcile the volume of trading observed in equity markets with the trading needs of rational investors Rational investors make periodic contributions and withdrawals from their investment portfolios, rebalance their portfolios, and trade to minimize their taxes Those possessed of superior information may trade speculatively, although rational speculative traders will generally not choose to trade with each other It is unlikely that rational trading needs account for a turnover rate of

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Boys will be Boys: Gender, Overconfidence, and Common Stock Investment

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Research Design: Qualitative, Quantitative, and Mixed Methods Approaches

Contents: Preface, Erik Hollnagel Resilience and restlessness, Ron Westrum Resilience engineering: the birth of a notion, Christopher P. Nemeth The need for 'translators' and for new models of safety, Jean-Christophe Le Coze and Michele Dupre Measures of resilient performance, David Mendonca Unexampled events, resilience, and PRA, Steve Epstein Safety management - looking back or looking forward, Erik Hollnagel When resilience does not work, Akinori Komatsubara Rules management as source for loose coupling in high-risk systems, Gudela Grote Work practices and prescriptions: a key issue for organizational resilience, Dimitris Nathanael and Nicholas Marmaras Crew resilience and simulator training in aviation, Sidney Dekker, Nicholas DahlstrA m, Roel van Winsen and James M. Nyce Underlying concepts in robustness and resilience and their use in designing socio-technical systems, Bernard Pavard, Julie Dugdale, Narges Bellamine-Ben Saoud, Sandrine Darcy and Pascal Salembier Stress-strain plots as a basis for assessing system resilience, David D. Woods and John Wreathall Designing resilient critical infrastructure systems using risk and vulnerability analysis, Kurt E. Petersen and Henrik Johanssen Towards a resilient approach of safety assessment: experiences based on the design of the future air traffic management system, Oliver StrAter Resilience in the emergency department, Robert L. Wears, Shawna J. Perry, Shilo Anders and David D. Woods The Beatson event - a resilience engineering perspective, John Wreathall What went wrong at the Beatson Oncology Centre?, Richard I. Cook, Christopher P. Nemeth and Sidney Dekker Resilience, safety and testing, Steve Epstein Detecting an erroneous plan: does a system allow for effective cross-checking?, Matthieu Branlat, Shilo Anders, David D. Woods and Emily S. Patterson Investigations as an impediment to learning, Eric Hollnagel Analysis of the Beatson event, Pierre Le Bot Appendix Bibliography Indexes

Remaining Sensitive to the Possibility of Failure

Tool builders have focused, not improperly, on tool building--how to build better performing machine problem-solvers, where the implicit model is a human expert solving a problem in isolation. A critical task then for the designer working in this paradigm is to collect human knowledge for computerization in the stand alone machine problem-solver. But tool use involves more. Building systems that are "good" problem-solvers in isolation does not guarantee high performance in actual work contexts where the performance of the joint person-machine system is the relevant criterion. The key to the effective application of computational technology is to conceive, model, design, and evaluate the joint human-machine cognitive system (Hollnagel & Woods, 1983). Like Gestalt principles in perception, a decision system is not merely the sum of its parts, human and machine. The configuration or organization of the human and machine components is a critical determinant of the performance of the system as a whole (e.g. Sorkin & Woods, 1985). The joint cognitive system paradigm (Woods, 1986; Woods, Roth & Bennett, in press) demands a problemdriven, rather than technology-driven, approach where the requirements and bottlenecks in cognitive task performance drive the development of tools to support the human problem-solver. In this paper we describe an approach to understand the cognitive activities performed by joint human-machine cognitive systems. The real impediment to effective knowledge acquisition is the lack of an adequate language to describe cognitive activities in particular domains--what are the cognitive implications of some application's task demands and of the aids and interfaces available to the people in the system; how do people behave/perform in the cognitive situations defined by these demands and tools. Because this independent cognitive description has been missing, an uneasy mixture of other types of description of a complex situation has been substituted---descriptions in terms of the application itself, of the implementation technology of the interfaces/aids, of the user's physical activities or user psychohaetrics. We describe one approach to provide an independent cognitive description of complex situations that can be used to understand the sources of both good and poor performance, i.e. the cognitive problems to be solved or challenges to be met.

Mapping cognitive demands in complex problem-solving worlds

Is safety a subject for science

The recent foundering of the Costa Concordia in January 2012 demonstrated that accidents can occur even with ships that are considered masterpieces of modern technology and despite more than 100 years of regulatory and technological progress in maritime safety. The purpose of this paper is, however, not to speculate about the concrete causes of the Costa Concordia accident, but rather to consider some human and organizational factors that were present in the Costa Concordia accident as well as in the foundering of the Titanic a century ago, and which can be found in many other maritime accidents over the years. The paper argues that these factors do not work in isolation but in combination and often together with other underlying factors. The paper critically reviews the focus of maritime accident investigations and points out that these factors do not receive sufficient attention. It is argued that the widespread confidence in the efficacy of new or improved technical regulations, that characterizes the recommendations from most maritime accident investigations, has led to a lack of awareness of complex interactions of factors and components in socio-technical systems. If maritime safety is to be sustainably improved, a systemic focus must be adopted in future accident investigations.

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From Titanic to Costa Concordia—a century of lessons not learned

When an accident happens, it is obviously important to understand what caused it in order to take effective preventive measures. Accident analysis always implies an accident model, i.e., a set of assumptions of what the underlying "mechanisms" are. Over the last 50-75 years there have been significant changes in accident models, leading to changes in the methods and goals of accident analysis. In parallel to this development the understanding of the role of humans in accidents, and of the nature of "human error", has also changed. This paper provides an overview of the developments, and outlines the consequences for contemporary accident analysis and prevention.

Erik Hollnagel

Papers

Remaining Sensitive to the Possibility of Failure

Mapping cognitive demands in complex problem-solving worlds

Is safety a subject for science

From Titanic to Costa Concordia—a century of lessons not learned

Understanding accidents-from root causes to performance variability