Jul 2026· AI and Ethics· Vol 6· 0 citations· 54 references
Computer Science
TL;DR
The Qualitative Model of Ethics (QME), a naturalistic and teleological framework grounded in a single evaluative scalar: the generative capacity of the Whole Living System (WLS), provides a unified and operational framework for AI governance at scale.
A Multi-Layer Social-Theoretical AI Ethics Framework (MLST-AEF) that integrates normative ethical reasoning, stakeholder analysis, institutional context, bias and power assessment, and structured decision support is developed.
M. Fakrudeen, J. Otieno· AI and Ethics· 0 citations
A novel methodology for future-proofing global operations against institutional voids and ethical risks in the digital infosphere is provides a novel methodology for future-proofing global operations against institutional voids and ethical risks in the digital infosphere.
Martin Sposato, Eduardo Carlos Dittmar· Journal of Information, Comm...· 0 citations
A reframing of AI unaccountability as a constitutive property of sociotechnical systems, an extension of the four barriers to accountability, and a practical instrument for identifying accountability voids in specific AI deployments are contributed.
Long Hoang Nguyen, Eva Späthe, S. Lins et al.· 0 citations
It is argued that attending to effects complements current approaches by directing ethical inquiry towards the cumulative transformations that emerge through everyday human–LLM interaction.
The argument further holds that AI does not possess moral agency in the classical sense but functions as an infrastructural precondition for the reconfiguration of normative hierarchies—in an empirical rather than transcendental sense.
The study develops a Leo XIV-informed, normatively grounded hybrid model of AI governance that extends beyond the exercise of agency over technology to fostering a more just and inclusive social order in which technology enables human flourishing.
S. Fel, Marta Choroszewicz, Jarosław Kozak· AI and Ethics· 1 citation
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