Aug 2026· Philosophy and Medicine· Vol 7· 0 citations· 5 references
Abstract
Increasingly, scholars warn that artificial intelligence (AI) may replicate or intensify epistemic injustice (EI) in biomedical contexts. This paper argues that such concerns require demonstrable evidence on (i) the actual presence of EI, and (ii) whether EI, if present, makes system effects normatively undesirable. Without evidence on (i), the EI framework is, by its own lights, inapplicable. Evidence on (ii) is needed because reflective equilibrium can, in principle, prioritize competing considerations over epistemic justice. A key challenge is that discourses on (i) and (ii) can themselves be sites of EI. Two steps are proposed: distinguishing AI’s effects on problem constructions from its effects on abilities to address constructed problems, and foregrounding relative accuracy and real-world impact on the quality of care in assessments of AI-induced EI.
The Stoic concept of the hegemonikon—the capacity for assent that directs the mind—is used as a framework for understanding intellectual creation and decision-making, clarifying when AI supports human judgment and when it replaces decision-making authority.
Christos A. Koutsotasios, Elias Vavouras· Dianoesis· 0 citations
An ethics of non-agentive AI is sketched: the authors should see these systems as powerful, instrument-like extensions of human cognition, not as knowers in their own right, and design institutions, interfaces and norms of trust accordingly.
Neumann Saskia Janina· Digital Society· 0 citations
A mechanistic account according to which AI-driven engagement architectures reconfigure the cues by which beliefs are evaluated, producing unwarranted confidence in one’s own judgments and undermining the conditions for deliberative compromise is developed.
John Dorsch, Mark Coeckelbergh, Tillmann Vierkant· Synthese· 1 citation
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
The central thesis is that AI, by processing vast “Data Lakes,” generates a “hyper-vision” that makes previously unattainable patterns visible, dramatically expanding the domain of what is “reasonably predictable” and creates AI-Augmented Consequentialism, where the agent's moral duty comes to include consideration of...
Marcus Gansauskas Bruzzo· AI and Ethics· 0 citations
Artificial intelligence (AI) is increasingly used in public administration, yet its opacity raises concerns about arbitrary exercises of state power. This article argues that alongside regulatory frameworks, the Rule of Law supplies an independent basis for limiting state deployment of AI. Drawing on widely accepted...
P. Burgess· Law and Governance· 0 citations
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