More Process, Less Principles: The Ethics of Deploying AI and Robotics in Medicine
This academic article argues that current governance for AI and robotics focuses too heavily on ethical design principles rather than ethical deployment, particularly in medical settings. The authors propose a practical decision-making model called Participatory Deliberative Conservatism (PDC) to guide medical institutions in purchasing and deploying ready-made advanced technologies. The model integrates local stakeholder participation, structured deliberation of underlying values, and adherence to established medical and legal standards.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Healthcare administrators, clinicians, bioethicists, and researchers seeking a practical model for evaluating the deployment of AI and robotics in medical environments.
What the document contains
The document addresses the shortcomings of current top-down, principlist ethical guidelines for advanced technologies in medicine. It introduces a four-step practical framework (PDC) incorporating preliminary value identification, stakeholder deliberation, policy formulation, and iterative evaluation.
It does not provide legal mandates, software engineering specifications, or a universal ranking of ethical values that applies across all jurisdictions.
- Medical institutions primarily face challenges of ethical deployment for ready-made technologies rather than ethical design.
- Generalist ethical principles often suffer from ambiguity, ranking challenges, and tacit exclusion of local values.
- The Participatory Deliberative Conservatism (PDC) model prioritizes procedural safeguards over abstract ethical lists.
- PDC integrates stakeholders, including patients, nurses, and administrators, into a structured deliberative process.
- The conservative element ensures deployment decisions remain bounded by professional, legal, and medical codes of ethics.
· Introduction · Principles and Processes: Two Distinctions · Participatory Deliberative Conservatism · The Virtues of Deliberative Participatory Conservatism · Conclusion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Although patient values and concerns inform deployment, the moral and legal responsibility for deployment (and its consequences) rests with medical practitioners and administrators.
Introduction
screening score · 2026-10-23
Fairness
2/5Non-discrimination and equitable treatment
Although there appears to be some convergence on broad ethical principles (e.g., respect for autonomy, harm prevention, fairness, and explicability)
Introduction
screening score · 2026-10-23
Human Dignity
2/5Respect for the inherent worth of persons
Researchers explore how these technologies impact values such as patient autonomy, dignity, welfare, nonmaleficence, privacy, safety, transparency, human capabilities
Introduction
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-23
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
Satisfying these various oversight groups often requires running a pilot study to demonstrate that the technology meets the various institutional requirements and demands.
Two Forms of Proceduralism
screening score · 2026-10-23