DISTRIBUTED AGENCY AND DISTRIBUTED RESPONSIBILITY IN ARTIFICIAL AI SYSTEMS: AN INFOETHICAL ANALYSIS
DOI:
https://doi.org/10.18372/2412-2157.42.21006Keywords:
artificial intelligence, information ethics, distributed agency, distributed responsibility, AI governance, accountability, infosphere, socio-technical systems, trustworthy AI, ethics of technologyAbstract
The article examines distributed agency and distributed responsibility in artificial intelligence systems within contemporary information ethics. AI is considered as a socio-technical phenomenon that reshapes the philosophical understanding of action, responsibility, and human participation in technologically mediated environments. The aim and tasks. The article aims to provide a philosophical and ethical analysis of distributed agency and distributed responsibility in AI systems. The study revisits classical views of moral action, agency, and responsibility; examines the transformation of agency in the context of AI; clarifies the notion of artificial agency in Luciano Floridi’s information ethics; analyzes the responsibility gap; and outlines the significance of accountability, governance, and auditability for the ethical assessment of AI. Research methods. The study is based on an interdisciplinary methodology combining conceptual analysis, information ethics, philosophy of technology, philosophical anthropology, and socio-technical systems analysis. It also employs historical-philosophical reconstruction, comparative analysis, hermeneutic interpretation, and generalization. Research results. The article shows that the classical subject-centered model of moral action is insufficient for analyzing contemporary AI systems. In AI environments, action emerges through the interaction of human, artificial, institutional, and infrastructural components. AI is therefore interpreted not as a moral subject in the human sense, but as a form of artificial agency, while responsibility acquires a distributed and procedural character. Discussion. The discussion supports the view that the ethical problem of AI should be framed not only in terms of individual blame, but also in terms of accountability, traceability, governance, and socio-technical conditions of action. Conclusions. The spread of AI transforms the normative conditions under which agency, responsibility, and trust are understood. Responsibility is no longer reducible to retrospective blame alone; it increasingly depends on the ethical and institutional organization of the environments in which AI systems are designed, deployed, monitored, and used.
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Johnson, Deborah G., and Mario Verdicchio. 2017. “Reframing AI Discourse.” Minds and Machines 27 (4): 575–90.
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