Moral Agency and Responsibility in Artificial Intelligence: Can Autonomous Systems Be Held Ethically Accountable
Sunjida Mukta ()
Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2025, vol. 8, issue 1, 198-207
Abstract:
Progress of artificial intelligence technologies has led to emerged acute ethical queries as to whether AI can be conceived as ethically responsible beings. This work aims at reviewing the concept of moral agency and analysis based on the degree to which artificial systems can be moral agent as determined by certain factors such as intentionality, autonomy, and moral reasoning. Conducting theoretical conceptualization and case study methodology, the study compares theoretical approaches in terms of their applicability to AI in self-driving cars and algorithms in healthcare. The discussion uses other concepts such as ethical learning and professional responsibility as postulated by Luhanga, Myrick and Yonge (2010) on moral reasoning and honesty in the aspects of responsibility. Hamrouni et al. (2023) present a timely adjunct to this by discussing newer forms of accountability for AI The narrative approach is brought into focus by Penman (2018) who emphatically focuses on the importance of creating humanity in technologies and applying the framework of responsibility. The author determined that present-day AI systems remain preconscious, a-rational and hence, unable to exhibit moral subjectness; however, he observed increasing rationale for distributed responsibility between those designing, operating the infrastructures and the systems involved. Therefore, this paper concludes that the concept of ethical responsibility of AI should be reimagined in a collective manner while paving the way for human-centric and explainable rules, regulations, and guidelines for the management of AI systems.
Keywords: Ethical Accountability; Autonomous Systems; Artificial Intelligence Ethics; Responsibility Attribution; Machine Morality (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:das:njaigs:v:8:y:2025:i:1:p:198-207:id:363
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