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2020 | OriginalPaper | Buchkapitel

7. A Manager’s Introduction to AI Ethics

verfasst von : Mark Esposito, Joshua Entsminger, Lisa Xiong

Erschienen in: New Leadership in Strategy and Communication

Verlag: Springer International Publishing

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Abstract

Researchers and managers need to better understand how different ideas of ethics shape how artificial intelligence can be effectively applied and leveraged as a source of competitive advantage. More fundamentally, managers need to understand how the competitive use of artificial intelligence cannot be differentiated from the specific ethical claims reflected in the design, operation, management, and maintenance of the technology. We pose how AI can be given dimensions to provide better insight into ethical requirements. We pose, however, that there is no ethical panacea, rather that the effective global management of ethical and unethical AI requires a larger common meta-ethical approach.

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Grossman (2018).

Esposito et al. (Forthcoming).

See Dewey et al. (2012).

See for inspiration, as the specific concept of relevant in relation to moral propositions derives from Matheis’s work (2016).

However, within the field, there is a divide between those who believe the current set of solution and problems genuinely constitute AI or whether such neural networks, or any other similar solution (machine learning, deep learning, etc.) is simply imitation.

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Managers should learn to discriminate between systems that learn how to perform a specific task, and system that can learn “how to learn” how to perform that or other tasks.

Garcia (2018).

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For inspiration, see Scott (2008). The issue is identified in relation to government organization of forestation in strict rows by virtue of state defined reasons.

Esposito et al. (Forthcoming).

Ibid.

Esposito et al. (Forthcoming)

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Titel: A Manager’s Introduction to AI Ethics
verfasst von: Mark Esposito
Joshua Entsminger
Lisa Xiong
Verlag: Springer International Publishing
Buch: New Leadership in Strategy and Communication
Print ISBN: 978-3-030-19680-6

Electronic ISBN: 978-3-030-19681-3

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-19681-3_7