NDLI: Employee Perceptions of the Effective Adoption of AI Principles.

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Employee Perceptions of the Effective Adoption of AI Principles.

Content Provider	Europe PMC
Author	Kelley, Stephanie
Abstract	This study examines employee perceptions on the effective adoption of artificial intelligence (AI) principles in their organizations. 49 interviews were conducted with employees of 24 organizations across 11 countries. Participants worked directly with AI across a range of positions, from junior data scientist to Chief Analytics Officer. The study found that there are eleven components that could impact the effective adoption of AI principles in organizations: communication, management support, training, an ethics office(r), a reporting mechanism, enforcement, measurement, accompanying technical processes, a sufficient technical infrastructure, organizational structure, and an interdisciplinary approach. The components are discussed in the context of business code adoption theory. The findings offer a first step in understanding potential methods for the effective adoption of AI principles in organizations.
Related Links	https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC9259894&blobtype=pdf
ISSN	01674544
Journal	Journal of Business Ethics [J Bus Ethics]
Volume Number	178
DOI	10.1007/s10551-022-05051-y
PubMed Central reference number	PMC9259894
Issue Number	4
PubMed reference number	35818389
e-ISSN	15730697
Language	English
Publisher	Springer Netherlands
Publisher Date	2022-02-10
Publisher Place	Dordrecht
Access Restriction	Open
Rights License	This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. © The Author(s), under exclusive licence to Springer Nature B.V. 2022
Subject Keyword	AI principles AI ethics Artificial intelligence Adoption
Content Type	Text
Resource Type	Article
Subject	Business and International Management Arts and Humanities Law Economics and Econometrics Business, Management and Accounting

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