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Characterizing Uncertainty through Expert Elicitation
Published in Charles Yoe, Principles of Risk Analysis, 2019
Confirmation bias is a tendency to search for or interpret information in a way that confirms one's preconceptions. The problem is people, including experts, have been shown to actively seek out and assign more weight to evidence that confirms their hypothesis, and ignore or underweigh evidence that could disconfirm their hypothesis. Confirmation bias not only affects how people gather information, but also how they interpret and recall information. We need look no further than politics for a plethora of examples. If you like the incumbent president of your country, you likely get your news from sources that share your view and you see alternative sources as biased. If you dislike the incumbent you likely do the opposite. Furthermore, every action the incumbent takes is filtered through your like/dislike lens. We tend to seek information that supports our existing beliefs. This type of bias can prevent us from looking at a situation objectively. It can also influence the decisions we make and can lead to poor or faulty choices made when we fail to see the world as it truly is.
Decision Making
Published in Christopher D. Wickens, Justin G. Hollands, Simon. Banbury, Raja. Parasuraman, Engineering Psychology and Human Performance, 2015
Christopher D. Wickens, Justin G. Hollands, Simon. Banbury, Raja. Parasuraman
Evidence bearing on a hypothesis or belief may be either passively received or actively sought. The confirmation bias describes a tendency for people to seek information and cues that confirm the tentatively held hypothesis or belief, and not seek (or discount) those that support an opposite conclusion or belief. Ambiguous cues, that information which is totally undiagnostic within the framework presented in Section 5.1, will be interpreted in a manner that supports the favored belief (Cook & Smallman, 2008; Einhorn & Hogarth, 1978; Herbert, 2010; Hope, Memon, & George, 2004; Mynatt, Doherty, & Tweney, 1977; Nickerson, 1998; Schustack & Sternberg, 1981). This bias produces a sort of “cognitive tunnel vision” in which operators fail to encode or process information that is contradictory to or inconsistent with the initially formulated hypothesis, hence conferring even greater rigidity to the anchor.
Cognitive Factors in Emergency Medical Services
Published in Joseph R. Keebler, Elizabeth H. Lazzara, Paul Misasi, Human Factors and Ergonomics of Prehospital Emergency Care, 2017
Confirmation bias is the tendency to consider only information that is consistent with a hypothesis or one᾿s point of view rather than also considering information that might disprove it (Baron, 2000). In a famous example by Shafir (1993), two groups of participants evaluated a hypothetical scenario in which two parents were suing for the sole custody of their child. Both groups read the same descriptions of the parents: parent A had average income, health, and working hours; an average relationship with the child; and a relatively stable social life, while parent B had an above-average income, minor health problems, long working hours, an extremely close relationship with the child, and an extremely active social life. When one group of participants was asked, “To which parent would you award sole custody?” they picked parent B 64% of the time. Interestingly, however, when the other group was asked, “To which parent would you deny sole custody?” they also tended to pick parent B 55% of the time. In other words, Parent B was both awarded and denied custody of the child, depending on how the question was framed. Why would this preference reversal happen? When the participants considered reasons to award custody, they tended to concentrate on the positive aspects of parent B to confirm their decision, but when they considered reasons to deny custody, they concentrated on the negative aspects of parent B in the same vein. In other words, the participants tended to concentrate on information that was consistent with the decision they needed to make, rather than considering all of the information as a whole.
Why Majorities Are Silent but Minorities Are Loud: An Empirical Approach to Opinion Interactions in Online Communities
Published in International Journal of Human–Computer Interaction, 2023
Several psychological concepts provide more detailed explanations of user perceptions and behaviors observed only in online environments. For instance, confirmation bias is a useful theoretical lens. Knobloch-Westerwick and Kleinman (2012) investigated confirmation bias in pre-election issues and found that people exhibited confirmational bias and anticipated that their supporting party would win when they infrequently received online news. This result indicates that the strength of belief in an opinion can induce selective exposure and construct confirmation bias. Similarly, Pearson and Knobloch-Westerwick (2019) examined how political stances (conservative and liberal) and media types (online and print) affect confirmation bias in pre-election issues. In this study, people with strong beliefs (ie, whose party was likely to win) revealed confirmation bias, whereas people with weak beliefs (ie, whose party was predicted to lose) did not. Interestingly, confirmation bias easily appeared in the online context. These studies imply that a homogeneous opinion space can lead people to build strong beliefs, and accordingly, confirmation biases.
Explainable AI: The Effect of Contradictory Decisions and Explanations on Users’ Acceptance of AI Systems
Published in International Journal of Human–Computer Interaction, 2023
Carolin Ebermann, Matthias Selisky, Stephan Weibelzahl
The CDT states that individuals apply different strategies to reduce this cognitive dissonance (Festinger, 1957), e.g., modifying their cognitions or ignoring contradictory information. However, previous studies also found resistance to changing attitudes, opinions or decisions for many situations – especially in the case of increased negative affect (Devine et al., 1999; Festinger & Carlsmith, 1959; Pyszczynski et al., 1993). For example, the confirmation bias (Wason, 1960, 1968) postulated that users tend to ignore contradictory information and do not change their opinion, attitude or decision. These findings are in line with the study of Giboney et al. (2015) where the system had less influence on user’s decision in the case of cognitive misfit. Based on these assumptions, it can be suggested that, in case of cognitive misfit, users disregard AI’s different decision and corresponding explanation, do not change their decision and are less willing to use the AI again. Therefore, the following hypothesis is formulated:
Can hedonic technology use drive sexism in youth? Reconsidering the cultivation and objectification perspectives
Published in Behaviour & Information Technology, 2022
Because men and women can respond differently to technology-mediated gender-role messages (Rollero 2013), it is reasonable to expect gender-based difference in the possible effects of exposure to media, the content of which tends to portray women as inferior to men (Harris, 2018). The differences may stem from confirmation bias (Nickerson 1998) which together with cognitive dissonance theory (Festinger 1957) suggests that people will more easily adopt cognitions that are consistent with their worldview and are favourable to them, such that self-worth is enhanced and unpleasant dissonance is reduced. As such, differences between how men and women respond to women-demeaning content can be influenced by the fact that such views are more congruent with male worldviews and less so with female worldviews (Barnes, Beaulieu, and Saxton 2020). Indeed, responses to content and messages depend on congruity with typical gender-roles (Read, Lynch, and Matthews 2018). Hence, it is reasonable to expect that the use of hedonic technologies (again, assuming they includes some if not much sexist content) will be more strongly associated with sexism in males than in females. Hence: H2a-c: The association between the use of hedonic technologies ([a] videogames, [b] social media, and [c] video streaming) and sexist attitudes will be more pronounced in males.