Jul 2026· AI and Ethics· Vol 6· 0 citations· 69 references
Computer Science
TL;DR
This work builds on and extends the Beneficent Intelligence (BI) framework from [23] to clarify the mediating role that such AI systems play, how this impacts alignment with the goals of a range of parties, and identify conditions necessary for such systems to confer meaningful benefit.
Abstract
Technologies are being rapidly developed that enable artificial intelligence (AI) systems to dynamically emulate the voice, appearance, and mannerisms of real people. Although concerns about the potential harms from such systems are widespread, there is comparatively little discussion of the conditions under which they might be used to benefit impacted parties. Recent efforts to provide a formal model of benefit represent an advance, but do not represent with sufficient clarity how such systems mediate social relationships in a way that can make a wide range of parties vulnerable to failure modes such as deception and domination. We build on and extend the Beneficent Intelligence (BI) framework from [23] to clarify the mediating role that such AI systems play, how this impacts alignment with the goals of a range of parties, and identify conditions necessary for such systems to confer meaningful benefit. Our analysis can assist developers, users, and other interested parties in better managing the risks associated with emulating technologies.
This book offers a clear, concise introduction to trustworthy AI, treating AI not just as a technical artifact but as a socio-technical system embedded in human contexts, designed for teaching and learning in computer science, data science, law, policy, business, and related fields.
Andrea Aler Tubella, Virginia Dignum, Marçal Mora-Cantallops et al.· 0 citations
A comprehensive model for integrating ethical standards into the phases of the Software Development Life Cycle (SDLC) is proposed, founded on the pillars of fairness, transparency, accountability, and sustainability, offering practical recommendations aimed at developers, organizations, and policymakers.
A. Alaswad· Al-Farooq Journal of Science...· 0 citations
AI development agents are increasingly used to support and partially automate software architecture tasks. To explore how practitioners perceive this shift, specifically what changes, what remains, and what new responsibilities emerge, we conducted a focus group at the 31st European Conference on Pattern Languages of P...
U. van Heesch, Olaf Zimmermann, Christian Kohls· 0 citations
The article examines how the pursuit of technological sovereignty in the field of artificial intelligence, instead of bringing true autonomy, generates a wide range of hybrid dependencies. These dependencies arise at the levels of computing infrastructure, data governance, AI system evaluation methodologies, and deploy...
There is an objective need for a more detailed examination of the theoretical and practical issues surrounding the emergence and subsequent development of the legal framework governing AI, with a view to formulating proposals for its modernization in light of current realities and security requirements, including cyber...
This conceptual and normative paper links together research on anthropomorphism, mental models, trust calibration and AI-assisted decision-making into a single end-to-end chain, proposing a conceptual model with propositions for empirical testing.
L. van der Linden· AI and Ethics· 0 citations
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