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Bias and Bias Management in Ethics Education

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Abstract Ethical conduct is commonly held to depend on ethical decision-making (Greenberg & Baron, 2010). Ethical decision-making, however, is a complex process. Such decisions are influenced by knowledge (National Institute of Medicine, 2002), the strategies people apply in working with this knowledge set, and the context in which the decision is made (Detert, Trevino, & Sweitzer, 2008). Further, both psychological factors and contextual variables may give rise to errors or biases in any decision (Hogarth, 1980; Mumford, Blair, Dailey, Leritz, & Osburn, 2006). The specific goals of the proposed research are to: 1) identify the contextual and psychological variables that might bias ethical decision-making, 2) identify the strategies that might be used to prevent or compensate for most biases, 3) empirically test the relationships of biases and compensatory variables to ethical decision-making, and 4) assess the gains in ethical decision-making resulting from training in bias management. To address these goals a four-phase effort is envisioned. In the first phase, we will conduct a series of qualitative studies, studies based on interviews and think-aloud protocols, to identify the variables that bias ethical decision-making and the strategies that might be used to compensate for these biases. In the second phase, we will develop objective measures of these biases and compensatory strategies. In the third phase, we will assess the incremental value of these biases and compensatory strategies in accounting for ethical decision-making among doctoral students in the health, biological, and social sciences. In the fourth and final phase, findings emerging in phase three will guide modifications to a university-wide ethics education program. The incremental value of including bias management content in ethics education will be tested in a field experiment. The effort outlined above is noteworthy because it will allow identification of critical biases shaping ethical decision-making, and enable the generation of a validated model curriculum for bias management.
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