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 central ethical problem raised by artificial intelligence is not whether AI systems can "reason" in a functional sense, but whether their use preserves a centre of judgment that can be held responsible. Beginning with large language models, it distinguishes linguistic fluency from scientific validity, ethical commi...
Christos A. Koutsotasios, Elias Vavouras· Dianoesis· 0 citations
What if the most influential voices in our epistemic lives are not agents at all, but machines we keep mistaking for them? I argue that contemporary AI systems function more and more like epistemic authorities while lacking the psychological resources that underpin human epistemic agency. Building on work on artificial...
Neumann Saskia Janina· Digital Society· 0 citations
Does artificial intelligence (AI) threaten deliberative democracy? This paper argues that it does, not because it isolates citizens in simplistic “filter bubbles” understood as ideologically homogeneous silos, but because it hijacks the capacities through which beliefs are evaluated. While early accounts emphasized alg...
John Dorsch, Mark Coeckelbergh, Tillmann Vierkant· Synthese· 0 citations
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...
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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