Educating Computer Science Students about Algorithmic Fairness, Accountability, Transparency and Ethics

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Abstract

Professionals are increasingly relying on algorithmic systems for decision making however, algorithmic decisions occasionally perceived as biased or not just. Prior work has provided evidences that education can make a difference on the perception of young developers on algorithmic fairness. In this paper, we investigate computer science students' perception of FATE in algorithmic decision-making and whether their views on FATE can be changed by attending a seminar on FATE topics. Participants attended a seminar on FATE in algorithmic decision-making and they were asked to respond to two online questionnaires to measure their pre- and post-seminar perception on FATE. Results show that a short seminar can make a difference in understanding and perception as well as the attitude of the students towards FATE in algorithmic decision support. CS curricula need to be updated and include FATE topics if we want algorithmic decision support systems to be just for all.

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Kasinidou, M., Kleanthous, S., Orphanou, K., & Otterbacher, J. (2021). Educating Computer Science Students about Algorithmic Fairness, Accountability, Transparency and Ethics. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE (pp. 484–490). Association for Computing Machinery. https://doi.org/10.1145/3430665.3456311

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