Beleicia B. Bullock
ABSTRACT
The prevention of criminal activity has changed dramatically over the past two decades, largely due to the increased reliance on systems that provide crime data analysis. Created specifically for police, judicial sentencing, and prison applications, these systems conduct both predictive and retrospective analysis to aid decision making within the criminal justice system. Furthermore, these software platforms typically combine spatial informatics packages and advanced statistical features behind user-friendly interfaces. Recent studies have demonstrated problems with both the flawed logic within these systems' algorithms and the inherent biases in the underlying data. In this paper, we present a novel repository of computing ethics teaching modules across a variety of narrative areas. These modules and curated narratives help faculty to establish 'ethical laboratories' that can guide computer science students in improving their ethical reasoning skills as it relates to the creation of current and future technologies. First, we provide an overview of the Computing Ethics Narratives (CEN) project, its narrative repository and the module framework through a sample module on predictive policing algorithms. Furthermore, we share preliminary findings from a pilot of this module, which was implemented in an intermediate algorithms course. The preliminary student and faculty feedback suggest the predictive policing module was able to help students contextualize the ethical issues around the topic, however, students recommended devoting more class time to evaluating the technical complexities of these critical systems.
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Index Terms
- Computing Ethics Narratives: Teaching Computing Ethics and the Impact of Predictive Algorithms
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