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Implementing AI Ethics in Practice: An Empirical Evaluation of the RESOLVEDD Strategy

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 370))

Abstract

As Artificial Intelligence (AI) systems exert a growing influence on society, real-life incidents begin to underline the importance of AI Ethics. Though calls for more ethical AI systems have been voiced by scholars and the general public alike, few empirical studies on the topic exist. Similarly, few tools and methods designed for implementing AI ethics into practice currently exist. To provide empirical data into this on-going discussion, we empirically evaluate an existing method from the field of business ethics, the RESOLVEDD strategy, in the context of ethical system development. We evaluated RESOLVEDD by means of a multiple case study of five student projects where its use was given as one of the design requirements for the projects. One of our key findings is that, even though the use of the ethical method was forced upon the participants, its utilization nonetheless facilitated of ethical consideration in the projects. Specifically, it resulted in the developers displaying more responsibility, even though the use of the tool did not stem from intrinsic motivation.

An early version of this paper was presented in the Euromicro Conference on Software Engineering and Advanced Applications (SEAA 2019).

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Notes

  1. 1.

    https://www.bbc.com/news/technology-48276660.

  2. 2.

    https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G.

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Correspondence to Ville Vakkuri .

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Vakkuri, V., Kemell, KK. (2019). Implementing AI Ethics in Practice: An Empirical Evaluation of the RESOLVEDD Strategy. In: Hyrynsalmi, S., Suoranta, M., Nguyen-Duc, A., Tyrväinen, P., Abrahamsson, P. (eds) Software Business. ICSOB 2019. Lecture Notes in Business Information Processing, vol 370. Springer, Cham. https://doi.org/10.1007/978-3-030-33742-1_21

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  • DOI: https://doi.org/10.1007/978-3-030-33742-1_21

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