Dr Zsofia Toth zsofia.toth@durham.ac.uk
Associate Professor
Dr Zsofia Toth zsofia.toth@durham.ac.uk
Associate Professor
Professor Markus Blut markus.blut@durham.ac.uk
Professor
Service research and business ethics literature intersect concerning the question of artificial intelligence (AI) service robot accountability. In financial services, there is a broad spectrum of potential ethical issues, from data usage to customer vulnerabilities. This article scrutinizes the impact of morality and where accountability resides in the use of AI service robots in financial services. To address this challenge, we discuss the role of Corporate Digital Responsibility (CDR) for firms and illustrate how to implement a conceptual framework on the ethical implications of AI service robot applications, drawing on normative ethical theory. The framework elaborates on how the locus of morality (from human to AI agency) and moral intensity combine within context-specific AI service robot applications, and how this might influence associated accountability. We provide examples of AI robots' use for different purposes, differentiating between four 'accountability clusters': (1) professional norms, (2) business responsibility, (3) inter-institutional normativity, and (4) supra-territorial regulations cluster. We also discuss the CDR implications in different clusters. Ethical implications of using AI service robots and associated accountability challenges are relevant for a network of actors-from customers and designers to firms and the government. Implementation of the framework incorporates a range of internal and external stake-holders that firms need to consider. We also provide a CDR roadmap to incorporate a time perspective and to inform implementation efforts.
Tóth, Z., & Blut, M. (2024). Ethical compass: The need for Corporate Digital Responsibility in the use of Artificial Intelligence in financial services. Organizational Dynamics, 53(2), Article 101041. https://doi.org/10.1016/j.orgdyn.2024.101041
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 21, 2024 |
Online Publication Date | Feb 29, 2024 |
Publication Date | 2024-04 |
Deposit Date | Mar 1, 2024 |
Publicly Available Date | Mar 1, 2024 |
Journal | Organizational Dynamics |
Print ISSN | 0090-2616 |
Electronic ISSN | 1873-3530 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 53 |
Issue | 2 |
Article Number | 101041 |
DOI | https://doi.org/10.1016/j.orgdyn.2024.101041 |
Keywords | Organizational Behavior and Human Resource Management; Sociology and Political Science; Applied Psychology |
Public URL | https://durham-repository.worktribe.com/output/2291740 |
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