Type

Journal Article

What are patients doing in the loop? Patients as fellow-workers in the everyday use of medical AI

View online source

Authors:

Markus Herrmann

Year:

2024

The American Journal of Bioethics

Return to Search Results

Share

Related Publications

Journal Article

AI in health: Keeping the human in the loop
Journal Article

Care depersonalized: The risk of infocratic "personalized" care and a posthuman dystopia
Journal Article

Epistemic value of digital simulacra for patients
Journal Article

An expert panel discussion embedding ethics and equity in artificial intelligence and machine learning infrastructure
Journal Article

The epistemological nuances of interpreting adaptive machine learning systems through the lens of surgical innovation
Journal Article

Machine learning-generated clinical data as collateral research: A global neuroethical analysis
Journal Article

Adaptive machine learning systems in medicine: The post-authorization phase
Journal Article

Beyond consent: The MAMLS in the room
Journal Article

Prudently evaluating medical adaptive machine learning systems
Journal Article

The fine balance between complete data integrity in medical adaptive machine learning systems and the protection of research participants
Journal Article

Adaptive machine learning in medicine: Not human subjects research, not research at all
Journal Article

Discerning the nature of MAMLS: Research, quality improvement, or both?
Journal Article

Adaptive machine learning systems in medicine – more learner, less machine
Journal Article

Whether designated as research or not, who resolves ethical considerations emerging with healthcare AI?
Journal Article

Adaptive machine learning as research: Does the cure fit the disease?
Journal Article

Designing regulatory frameworks for machine learning systems in medicine—time for balance and practicality
Journal Article

From classification to governance: Ethical challenges of adaptive learning in medicine
Journal Article

Adaptive medical machine learning models should not be classified as perpetual research, but do require new regulatory solutions
Journal Article

A bioethics assessment of continuous learning in medicine and AI
Journal Article

Co-reasoning by humans in the loop as a goal for designers of machine learning-driven algorithms in medicine
Journal Article

Transparency, evaluation and going from “ethics-washing” to enforceable regulation: On machine learning-driven clinician decision aids
Journal Article

Scapegoat-in-the-loop? Human control over medical AI and the (mis)attribution of responsibility
Journal Article

The incommensurability of caring: ML, clinical decision-making, and human reasoning in healthcare
Journal Article

A holistic, multi-level, and integrative ethical approach to developing machine learning-driven decision aids
Journal Article

The black box dilemma: Challenges in human-AI collaboration in ML-CDSS
Journal Article

Reasons in the loop: The role of large language models in medical co-reasoning
Journal Article

A knower without a voice: Co-reasoning with machine learning
Journal Article

Co-reasoning in context: Collaboration in critical care
Journal Article

Limitations of patient-physician co-reasoning in AI-driven clinical decision support systems
Journal Article

What do we do with physicians when autonomous AI-enabled workflow is better for patient outcomes?

+