arXiv:2608. 05583v1 Announce Type: cross Abstract: As large language models (LLMs) enter high-stakes domains such as healthcare, understanding their moral reasoning becomes essential.
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As large language models (LLMs) enter high-stakes domains such as healthcare, understanding their moral reasoning becomes essential. Decisions about scarce medical resources often hinge on judgments of responsibility, particularly when patients' own actions contribute to illness.
The study presents a benchmark of 208 rare‑disease clinical vignettes to evaluate how large language models (LLMs) handle ethically charged decision‑making. Across 11 state‑of‑the‑art LLMs, the models consistently favored justice—specifically equal resource allocation—over other bioethical principles such as beneficence, non‑maleficence, and autonomy. The authors also found that the framing of authority (committee vs. clinician vs. patient) influences which ethical principle the models prioritize, suggesting that institutional pressures may shape LLM decision support in rare‑disease care.
arXiv:2608. 12368v1 Announce Type: new Abstract: Agreement with human judgments is a common proxy for evaluating the alignment of large language models (LLMs).
arXiv:2608. 08061v1 Announce Type: new Abstract: The key question in moral judgement is not simply whether someone chooses the "right" answer, but how they decide what matters most when moral principles conflict.
arXiv:2603.23114v2 Announce Type: replace Abstract: A human's moral decision depends heavily on the context. Yet research on LLM morality has largely studied fixed scenarios. We address this gap by i...
arXiv:2603. 00048v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in sensitive applications including psychological support, healthcare, and high-stakes decision-making.