Nueva publicación: Relational moral status and moral progress — a social-structural argument in support of relationalism

Antonio Gaitán Torres & Germán Massaguer Gómez (Universidad Carlos III de Madrid).

AI and Ethics, Volume 6, article number 257 (2026)

Enlace al artículo: https://doi.org/10.1007/s43681-026-01101-7

Abstract:

Recent advances in artificial intelligence, particularly in Large Language Models (LLMs) and social robots, have renewed philosophical debates about the moral status of artificial systems. Dominant property-based approaches ground moral consideration in intrinsic features such as consciousness or the capacity to suffer, typically concluding that current AI systems fall outside the moral domain. Relational approaches, by contrast, locate moral status in socially and institutionally mediated relationships. This article advances a novel case in support of relational accounts by situating them within a broader theory of moral progress. The central claim is that relational approaches offer a highly plausible explanation of how historical expansions of moral status have actually occurred. Drawing on the literature on moral progress, the article introduces the concept of relational embedding to describe the processes through which previously excluded beings came to matter morally by being integrated into social roles, institutional practices, and evolving frameworks of meaning. Building on this analysis, the article examines contemporary interactions with AI systems. It argues that social robots and LLMs are already embedded in relational structures that resemble those operating in earlier expansions of the moral circle, particularly in the animal case. While this does not imply that AI systems possess moral status, it points to the emergence of localized and tentative forms of moral recognition that property-based approaches struggle to accommodate. The article concludes by reframing debates about AI moral status around the social conditions under which moral recognition is formed, contested, and potentially expanded.

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Publicación subvencionada por: Proyecto Interagents /PID2024-161933NA-I00, financiado por MICIU/AEI/10.13039/501100011033/ y “FEDER/UE".