Giuseppe Vecchietti , Gajendra Liyanaarachchi , Giampaolo Viglia
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Managing deepfakes with artificial intelligence: Introducing the business privacy calculus
This paper explores the profound implications of artificial intelligence-driven deepfake technology. We introduce a novel business privacy calculus model by delving into the impact of deepfakes through a qualitative explanatory study involving twenty-seven bank managers from three global banks across nine countries. Building on psychological reactance and privacy calculus theories, the evidence shows how data integrity can mitigate deepfake threats, manage business risks, and ensure operational continuity. We propose an AI system architecture that operationalizes responsible AI practices aligned with the business privacy calculus framework. The study contributes to understanding deepfake threats and facilitates the development of a privacy-centric framework for AI governance to safeguard businesses, consumers, and all stakeholders more widely.
期刊介绍:
The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.