Imbalanced user-AI relationships form a distinct front-end ethical failure in healthcare AI that design choices such as restricted inputs and suppressed uncertainty can undermine agency and that reciprocity offers a path to more balanced interactions.
Medical Principles and Practice 30(1):17–28
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A prototype framework collects legal requirements and translates them into machine-actionable policies for federated data processing networks via policy-as-code and LLMs.
citing papers explorer
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The Imbalanced User-AI Relationships as an Ethical Failure of Front-End Design in Healthcare AI
Imbalanced user-AI relationships form a distinct front-end ethical failure in healthcare AI that design choices such as restricted inputs and suppressed uncertainty can undermine agency and that reciprocity offers a path to more balanced interactions.
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Compliance Management for Federated Data Processing
A prototype framework collects legal requirements and translates them into machine-actionable policies for federated data processing networks via policy-as-code and LLMs.