The role of consumer perceptions of the ethics of machine learning in the appropriation of artificial intelligence-based systems

Christine Balagué () and Zeling Zhong ()
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Christine Balagué: LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], CONNECT - Consommateur Connecté dans la Société Numérique - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris]
Zeling Zhong: LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris]

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Abstract: Generally, we expect Machine Learning (ML) in marketing to provide efficient recommendation systems, improvement in advertising with real time bidding, more accurate customers' behaviors predictions, and better CRM. This research focuses on the role of ML ethics, which is a combination of four ethical concepts: data privacy and security, fairness, accountability, and transparency of ML algorithms. The results show that ML ethics play a key role on consumer's behavior by positively influencing AI services appropriation. We use a PLS model to quantitatively measure AI services appropriation, as well as its antecedents (ML ethics and trust) and consequences (perceived value and NPS). We also reveal that fulfillment of contract obligations has a mediating role between ML ethics and trust in AI services. This research shows that marketers need to be responsible by focusing on the ethics of ML to answer AI users' needs and to enter in the Artificial Intelligence era.

Keywords: Artificial intelligence; Ethics; Appropriation; Transparency; Accountability; Fairness (search for similar items in EconPapers)
Date: 2022-06-16
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Published in 2022 ISMS Marketing Science Conference, INFORMS Society for Marketing Science (ISMS); The James M. Kilts Center for Marketing (The University of Chicago Booth School of Business), Jun 2022, Chicago (Virtual conference), United States

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03692600

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