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There are few studies explicitly linking cognitive biases to real-world incidents with highly negative outcomes. Examples: One study [11] explicitly focused on cognitive bias as a potential contributor to a disaster-level event; this study examined the causes of the loss of several members of two expedition teams on Mount Everest on two consecutive days in 1996.
While large bodies of research have been devoted to examining intergroup contact, social scientific reviews of the literature frequently voice skepticism about the likelihood of contact's optimal conditions occurring in concert, and by extension, about the generalizability of correlational research and lab studies on contact.
Systemic bias: This page outlines real, useful information about systemic bias on Wikipedia. We are aware that we have biases, and we do what we can to combat them. One against many: This page gives advice for dealing with situations where one editor wants to make a change but multiple editors oppose the change.
The publication or nonpublication of research findings, depend on the nature and direction of the results. Although medical writers have acknowledged the problem of reporting biases for over a century, [12] it was not until the second half of the 20th century that researchers began to investigate the sources and size of the problem of reporting biases.
According to a meta-analysis of 17 implicit bias interventions, counterstereotype training is the most effective way to reduce implicit bias. [14] In the area of gender bias, techniques such as imagining powerful women, hearing their stories, and writing essays about them have been shown to reduce levels of implicit gender bias on the IAT. [15]
The bias can be mitigated by having managers find common ground with the employee, thus priming the manager to see the employee as part of their in-group. [10] Firms can also counter the bias through implicit bias training and by having hiring and promotions be a data and metrics driven process.
Cognitive bias mitigation and cognitive bias modification are forms of debiasing specifically applicable to cognitive biases and their effects. Reference class forecasting is a method for systematically debiasing estimates and decisions, based on what Daniel Kahneman has dubbed the outside view .
Recent research on attribution biases has focused on identifying specific types of these biases and their effect on people's behavior. [7] [21] Additionally, some psychologists have taken an applied approach and demonstrated how these biases can be understood in real-world contexts (e.g., the workplace or school).