Effects of incorrect computer-aided detection (CAD) output on human decision-making in mammography

To investigate the effects of incorrect computer output on the reliability of the decisions of human users. This work followed an independent UK clinical trial that evaluated the impact of computer-aided detection(CAD) in breast screening. The aim was to use data from this trial to feed into probabilistic models (similar to those used in "reliability engineering") which would detect and assess possible ways of improving the human-CAD interaction. Some analyses required extra data; therefore, two supplementary studies were conducted. Study 1 was designed to elucidate the effects of computer failure on human performance. Study 2 was conducted to clarify unexpected findings from Study 1

Automation: Decision Aid or Decision Maker?

This study clarified that automation bias is something unique to automated decision making contexts, and is not the result of a general tendency toward complacency. By comparing performance on exactly the same events on the same tasks with and without an automated decision aid, we were able to determine that at least the omission error part of automation bias is due to the unique context created by having an automated decision aid, and is not a phenomena that would occur even if people were not in an automated context. However, this study also revealed that having an automated decision aid did lead to modestly improved performance across all non-error events. Participants in the non- automated condition responded with 83.68% accuracy, whereas participants in the automated condition responded with 88.67% accuracy, across all events. Automated decision aids clearly led to better overall performance when they were accurate. People performed almost exactly at the level of reliability as the automation (which across events was 88% reliable). However, also clear, is that the presence of less than 100% accurate automated decision aids creates a context in which new kinds of errors in decision making can occur. Participants in the non-automated condition responded with 97% accuracy on the six "error" events, whereas participants in the automated condition had only a 65% accuracy rate when confronted with those same six events. In short, the presence of an AMA can lead to vigilance decrements that can lead to errors in decision making

Moralization and the 2012 U.S. presidential election campaign

People vary in the extent to which they imbue an attitude with moral conviction; however, little is known about what makes an issue transform from a relatively non-moral preference to a moral conviction. In the context of the 2012 U.S. presidential election, we test if affect and beliefs (thoughts about harms and benefits) are antecedents or consequences of participants’ moral conviction about their candidate preferences, or are some combination of both. Using a longitudinal design in the run-up to the election, we find that, overall, affect is both an antecedent and consequence, and beliefs about harms and benefits are only consequences, of changes in moral conviction related to candidate preferences. The affect results were consistent across liberals, conservatives, and moderates; however, the role of beliefs showed some differences between ideologues (liberals and conservatives) and moderates. Keywords: moral conviction; affect; hostility; enthusiasm; political psycholog

Moral punishment in everyday life

The present research investigated event-related, contextual, demographic, and dispositional predictors of the desire to punish perpetrators of immoral deeds in daily life, as well as connections among the desire to punish, moral emotions, and momentary well-being. The desire to punish was reliably predicted by linear gradients of social closeness to both the perpetrator (negative relationship) and the victim (positive relationship). Older rather than younger adults, conservatives rather than people with other political orientations, and individuals high rather than low in moral identity desired to punish perpetrators more harshly. The desire to punish was related to state anger, disgust, and embarrassment, and these were linked to lower momentary well-being. However, the negative effect of these emotions on well-being was partially compensated by a positive indirect pathway via heightened feelings of moral self-worth. Implications of the present field data for moral punishment research and the connection between morality and well-being are discussed. Keywords: Morality, Moral Punishment, Experience Sampling, Social Closenes

Why Are People's Decisions Sometimes Worse with Computer Support?

In many applications of computerised decision support, a recognised source of undesired outcomes is operators' apparent over-reliance on automation. For instance, an operator may fail to react to a potentially dangerous situation because a computer fails to generate an alarm. However, the very use of terms like "over-reliance" betrays possible misunderstandings of these phenomena and their causes, which may lead to ineffective corrective action (e.g. training or procedures that do not counteract all the causes of the apparently "over-reliant" behaviour). We review relevant literature in the area of "automation bias" and describe the diverse mechanisms that may be involved in human errors when using computer support. We discuss these mechanisms, with reference to errors of omission when using "alerting systems", with the help of examples of novel counterintuitive findings we obtained from a case study in a health care application, as well as other examples from the literature