Limits of trust in medical AI
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | Hatherley, Joshua |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Are clinicians ethically obligated to disclose their use of medical machine learning systems to patients?
par: Hatherley, Joshua
Publié: (2025)
par: Hatherley, Joshua
Publié: (2025)
A moving target in AI-assisted decision-making: Dataset shift, model updating, and the problem of update opacity
par: Hatherley, Joshua
Publié: (2025)
par: Hatherley, Joshua
Publié: (2025)
In defence of post-hoc explanations in medical AI
par: Hatherley, Joshua, et autres
Publié: (2025)
par: Hatherley, Joshua, et autres
Publié: (2025)
Federated learning, ethics, and the double black box problem in medical AI
par: Hatherley, Joshua, et autres
Publié: (2025)
par: Hatherley, Joshua, et autres
Publié: (2025)
Data over dialogue: Why artificial intelligence is unlikely to humanise medicine
par: Hatherley, Joshua
Publié: (2025)
par: Hatherley, Joshua
Publié: (2025)
High hopes for "Deep Medicine"? AI, economics, and the future of care
par: Sparrow, Robert, et autres
Publié: (2025)
par: Sparrow, Robert, et autres
Publié: (2025)
Diachronic and synchronic variation in the performance of adaptive machine learning systems: The ethical challenges
par: Hatherley, Joshua, et autres
Publié: (2025)
par: Hatherley, Joshua, et autres
Publié: (2025)
Update Opacity: Epistemic Accessibility and Governance Under AI System Change
par: Ferrario, Andrea, et autres
Publié: (2026)
par: Ferrario, Andrea, et autres
Publié: (2026)
Practical Application and Limitations of AI Certification Catalogues in the Light of the AI Act
par: Autischer, Gregor, et autres
Publié: (2025)
par: Autischer, Gregor, et autres
Publié: (2025)
Can You Trust an LLM with Your Life-Changing Decision? An Investigation into AI High-Stakes Responses
par: Cahyono, Joshua Adrian, et autres
Publié: (2025)
par: Cahyono, Joshua Adrian, et autres
Publié: (2025)
Not someone, but something: Rethinking trust in the age of medical AI
par: Beger, Jan
Publié: (2025)
par: Beger, Jan
Publié: (2025)
Thousands of AI Authors on the Future of AI
par: Grace, Katja, et autres
Publié: (2024)
par: Grace, Katja, et autres
Publié: (2024)
Optimizing HIV Patient Engagement with Reinforcement Learning in Resource-Limited Settings
par: Periáñez, África, et autres
Publié: (2024)
par: Periáñez, África, et autres
Publié: (2024)
On the Unknowable Limits to Prediction
par: Yan, Jiani, et autres
Publié: (2024)
par: Yan, Jiani, et autres
Publié: (2024)
AI Toolkit: Libraries and Essays for Exploring the Technology and Ethics of AI
par: Ho, Levin, et autres
Publié: (2025)
par: Ho, Levin, et autres
Publié: (2025)
Lessons for Editors of AI Incidents from the AI Incident Database
par: Paeth, Kevin, et autres
Publié: (2024)
par: Paeth, Kevin, et autres
Publié: (2024)
Regulating AI Adaptation: An Analysis of AI Medical Device Updates
par: Wu, Kevin, et autres
Publié: (2024)
par: Wu, Kevin, et autres
Publié: (2024)
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle
par: Deck, Luca, et autres
Publié: (2024)
par: Deck, Luca, et autres
Publié: (2024)
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
par: Olteanu, Alexandra, et autres
Publié: (2025)
par: Olteanu, Alexandra, et autres
Publié: (2025)
Beware! The AI Act Can Also Apply to Your AI Research Practices
par: Wernick, Alina, et autres
Publié: (2025)
par: Wernick, Alina, et autres
Publié: (2025)
AI-Cybersecurity Education Through Designing AI-based Cyberharassment Detection Lab
par: Okpala, Ebuka, et autres
Publié: (2024)
par: Okpala, Ebuka, et autres
Publié: (2024)
Defining AI Models and AI Systems: A Framework to Resolve the Boundary Problem
par: Sun, Yuanyuan, et autres
Publié: (2026)
par: Sun, Yuanyuan, et autres
Publié: (2026)
Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies
par: Cao, Yuefan, et autres
Publié: (2025)
par: Cao, Yuefan, et autres
Publié: (2025)
Towards AI Transparency and Accountability: A Global Framework for Exchanging Information on AI Systems
par: Buckley, Warren, et autres
Publié: (2023)
par: Buckley, Warren, et autres
Publié: (2023)
Measuring What AI Systems Might Do: Towards A Measurement Science in AI
par: Voudouris, Konstantinos, et autres
Publié: (2026)
par: Voudouris, Konstantinos, et autres
Publié: (2026)
International AI Safety Report
par: Bengio, Yoshua, et autres
Publié: (2025)
par: Bengio, Yoshua, et autres
Publié: (2025)
AI Alignment at Your Discretion
par: Buyl, Maarten, et autres
Publié: (2025)
par: Buyl, Maarten, et autres
Publié: (2025)
Towards Environmentally Equitable AI
par: Hajiesmaili, Mohammad, et autres
Publié: (2024)
par: Hajiesmaili, Mohammad, et autres
Publié: (2024)
Exploring the sustainable scaling of AI dilemma: A projective study of corporations' AI environmental impacts
par: Desroches, Clément, et autres
Publié: (2025)
par: Desroches, Clément, et autres
Publié: (2025)
AI and Generative AI Transforming Disaster Management: A Survey of Damage Assessment and Response Techniques
par: Raj, Aman, et autres
Publié: (2025)
par: Raj, Aman, et autres
Publié: (2025)
Position: Model Collapse Does Not Mean What You Think
par: Schaeffer, Rylan, et autres
Publié: (2025)
par: Schaeffer, Rylan, et autres
Publié: (2025)
Scaling Laws For Scalable Oversight
par: Engels, Joshua, et autres
Publié: (2025)
par: Engels, Joshua, et autres
Publié: (2025)
A New Paradigm for Counterfactual Reasoning in Fairness and Recourse
par: Bynum, Lucius E. J., et autres
Publié: (2024)
par: Bynum, Lucius E. J., et autres
Publié: (2024)
AssurAI: Experience with Constructing Korean Socio-cultural Datasets to Discover Potential Risks of Generative AI
par: Lim, Chae-Gyun, et autres
Publié: (2025)
par: Lim, Chae-Gyun, et autres
Publié: (2025)
Transparent AI: The Case for Interpretability and Explainability
par: Ramachandram, Dhanesh, et autres
Publié: (2025)
par: Ramachandram, Dhanesh, et autres
Publié: (2025)
Generative AI Training and Copyright Law
par: Stober, Sebastian, et autres
Publié: (2025)
par: Stober, Sebastian, et autres
Publié: (2025)
A Collectivist, Economic Perspective on AI
par: Jordan, Michael I.
Publié: (2025)
par: Jordan, Michael I.
Publié: (2025)
Towards Socially and Environmentally Responsible AI
par: Li, Pengfei, et autres
Publié: (2024)
par: Li, Pengfei, et autres
Publié: (2024)
AI in Manufacturing: Market Analysis and Opportunities
par: Abdelaal, Mohamed
Publié: (2024)
par: Abdelaal, Mohamed
Publié: (2024)
Introduction to AI Safety, Ethics, and Society
par: Hendrycks, Dan
Publié: (2024)
par: Hendrycks, Dan
Publié: (2024)
Documents similaires
-
Are clinicians ethically obligated to disclose their use of medical machine learning systems to patients?
par: Hatherley, Joshua
Publié: (2025) -
A moving target in AI-assisted decision-making: Dataset shift, model updating, and the problem of update opacity
par: Hatherley, Joshua
Publié: (2025) -
In defence of post-hoc explanations in medical AI
par: Hatherley, Joshua, et autres
Publié: (2025) -
Federated learning, ethics, and the double black box problem in medical AI
par: Hatherley, Joshua, et autres
Publié: (2025) -
Data over dialogue: Why artificial intelligence is unlikely to humanise medicine
par: Hatherley, Joshua
Publié: (2025)