Concern 619 · Working draft · editorial review in progress
Dignity in end-of-life AI care
Dignity risks in end-of-life AI care arise when a person's wishes and relationships are reduced to predictions, scores or automated interactions.
Understanding the concern
Palliative care aims to support quality of life in the context of serious illness. AI may help identify needs or organize information, but it cannot decide what matters most to a person simply from a pattern in data. Comfort, privacy, beliefs and family relationships may not fit neatly into a model.
A scoping review describes potential applications alongside concerns about autonomy and depersonalization. The question is whether technology creates more room for attentive care or replaces it. People should remain involved in decisions to the extent they wish and are able, with appropriate support. A prediction about what often happens is not a statement of what this person wants.
An example
A care plan follows an automated recommendation without a conversation about the patient's priorities.
Illustrative unless identified as a documented case.
Words in plain English
- AI
- Software that learns patterns from examples or uses rules to perform tasks such as recognizing images or generating text. It can make mistakes and does not understand every situation as a person would.
- Model
- The learned part of an AI system. It uses patterns found during training to produce an answer or prediction.
Evidence and its limits
The review covers a small and varied evidence base. It does not establish that every AI tool diminishes dignity or provide individualized medical guidance.
Nikoloudi and Mystakidou · American Journal of Hospice and Palliative Care 2026 · Scoping review
Artificial Intelligence in Palliative Care: A Scoping Review of Current Applications, Challenges, and Future Directions ↗ (opens in a new tab)Seven included studies and ethical concerns; not proof that every AI tool depersonalizes end-of-life care.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
A question to discuss
How can AI support end-of-life care while keeping the person's own wishes central?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Dignity
Dignity means recognizing each person's worth regardless of usefulness, status, or a system's score. People deserve respect and a voice in matters that affect them.
Explain important decisions, avoid humiliating treatment, and keep room for a person's story. Do not treat a prediction as a complete account of who someone is.
Ask together: Does this use treat each person as someone whose experience matters?
Listening
Listening means trying to understand someone's experience before preparing an answer. People who use a service, work with it, or are judged by it may notice problems its designers miss.
Invite people to describe what happened in their own words. Repeat back what you understood and let them correct it. A quiet person or a complaint that is hard to measure may still reveal something important.
Ask together: Whose experience have we not heard yet?
Seeing potential
Seeing potential means recognizing people's capacity to learn, contribute, and grow. It resists reducing someone to a score or to the tasks a machine can perform faster.
Use tools to support people's development. Give learners time, feedback, and real opportunities to practice. A prediction about someone's performance should not close off their future.
Ask together: How could this help people develop abilities they value?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
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