How to Better Reduce Confirmation Bias? The Fit Between Types of Counter-Argument and Tasks

Confirmation bias is a driver of problematic decision making. People search information supporting current beliefs and ignore real critical evidence. Counter-argument i.e. providing evidences opposite to preferred beliefs was shown to have an effect on reducing confirmation bias. This study advances past studies by separating counter-arguments into two types and examining their effects in different stock investment contexts. We attempt to show that different types of counter-arguments are needed under different decisional contexts

The Impact of media coverage of criminal trials on the impartiality of the courts

Submitted in partial fulfillment of the requirements of the Bachelor of Laws Degree, Strathmore University Law SchoolCourt impartiality is a fundamental right that is accorded to accused persons. This right is in pursuit of a broader right of fair hearing which is recognized both internationally and nationally. Various factors contribute to the court bias. They include the normal human cognitive processes that limit a man to his observations. Prior exposure to facts of a criminal case may limit one's mind openness to the facts of a case that do not conform to the ones exposed to before. Therefore, the overall purpose of this paper is to illustrate the relationship between media coverage of criminal trials and court bias in making judicial decisions in criminal cases. This is through objectives such as investigate why criminal proceedings attract media attention; investigating how media portrays criminal proceedings; and investigating how the bias arises in courts as an effect of media coverage. There is a direct and indirect relationship that exists between media and judicial decisions. These exist between the media, the public and the judiciary. There is broad literature that has been covered to illustrate the same and judicial opinions in decided cases have also mentioned this relationship that leads to court bias. It is hoped that this study will inform judicial authorities of the need to balance the freedom of expression of the media and the right of an accused person to a fair trial that will not lead to either of the rights being trumped on

Overcoming Anchoring Bias: The Potential of AI and XAI-based Decision Support

Information systems (IS) are frequently designed to leverage the negative effect of anchoring bias to influence individuals’ decision-making (e.g., by manipulating purchase decisions). Recent advances in Artificial Intelligence (AI) and the explanations of its decisions through explainable AI (XAI) have opened new opportunities for mitigating biased decisions. So far, the potential of these technological advances to overcome anchoring bias remains widely unclear. To this end, we conducted two online experiments with a total of N=390 participants in the context of purchase decisions to examine the impact of AI and XAI-based decision support on anchoring bias. Our results show that AI alone and its combination with XAI help to mitigate the negative effect of anchoring bias. Ultimately, our findings have implications for the design of AI and XAI-based decision support and IS to overcome cognitive biases

Come On Down: Investigating an Informational Strategy to Debias the Anchoring Heuristic

When individuals estimate the price of goods or services, irrelevant factors may affect the estimates. For example, irrelevant numbers in individuals’ environments can cause participants to “anchor” to them as starting point price estimates, such that estimates tend toward the anchor (Tversky & Kahneman, 1974; Chapman & Johnson, 1994). In fact, anchored individuals may pay up to three times as much for a product and buy 32% more products (Ariely, Loewenstein, & Prelec, 2003; Wansink, Kent, & Hoch, 1998). Because anchoring affects purchases large and small, this study investigates how to debias, or reduce the negative effects of, the anchoring heuristic. Debiasing strategies are not easily implemented outside the lab where anchoring has the largest real world effects (Strack & Mussweiler, 1997; Chapman & Johnson, 1994; George, Duffy, & Ahuja, 2000). We therefore investigated an easily implemented informational debiasing strategy offering little disruption to an individual’s daily routine. The debiasing had no effect on anchoring, but further investigation with a larger sample size and higher external validity is necessary before discounting the strategy completely

Come On Down: Investigating an Informational Strategy to Debias the Anchoring Heuristic

When individuals estimate the price of goods or services, irrelevant factors may affect the estimates. For example, irrelevant numbers in individuals’ environments can cause participants to “anchor” to them as a starting point price estimates, such that estimates tend toward the anchor (Tversky & Kahneman, 1974; Chapman & Johnson, 1994). In fact, anchored individuals may pay up to three times as much for a product and buy 32% more products (Ariely, Loewenstein, & Prelec, 2003; Wansink, Kent, & Hoch, 1998). Because anchoring affects purchases large and small, this study investigates how to debias, or reduce the negative effects of, the anchoring heuristic. Debiasing strategies are not easily implemented outside the lab where anchoring has the largest real world effects (Strack & Mussweiler, 1997; Chapman & Johnson, 1994; George, Duffy, & Ahuja, 2000).We investigated an easily implemented informational debiasing strategy that would offer little disruption to an individual’s daily routine and investigated whether it could reduce the negative effects of the anchoring heuristic. The strategy had no effect on anchoring, but further investigation with a larger sample size and higher external validity is necessary before discounting the strategy completely

“They’re All the Same!” Stereotypical Thinking and Systematic Errors in Users’ Privacy-Related Judgments About Online Services

Given the ever-increasing volume of online services, it has become impractical for Internet users to study every company’s handling of information privacy separately and in detail. This challenges a central assumption held by most information privacy research to date—that users engage in deliberate information processing when forming their privacy-related beliefs about online services. In this research, we complement previous studies that emphasize the role of mental shortcuts when individuals assess how a service will handle their personal information. We investigate how a particular mental shortcut—users’ stereotypical thinking about providers’ handling of user information—can cause systematic judgment errors when individuals form their beliefs about an online service. In addition, we explore the effectiveness of counter-stereotypic privacy statements in preventing such judgment errors. Drawing on data collected at two points in time from a representative sample of smartphone users, we studied systematic errors caused by stereotypical thinking in the context of a mobile news app. We found evidence for stereotype-induced errors in users’ judgments regarding this provider, despite the presence of counter-stereotypic privacy statements. Our results further suggest that the tone of these statements makes a significant difference in mitigating the judgment errors caused by stereotypical thinking. Our findings contribute to emerging knowledge about the role of cognitive biases and systematic errors in the context of information privacy