Alignment Plausibility: A New Standard for Assuring AI in Healthcare
Large language models (LLMs) have become significant providers of mental health support, yet they remain products of an attention economy whose operational and commercial targets favour sustained engagement over the friction that effective psychological support often requires. Developers' safety responses have been largely reactive, addressing the most visible and acute harms while subtler, longer-term patterns of risk (e.g., dependency, boundary erosion, the amplification of distorted beliefs) receive less attention. We contend that making LLMs structurally safe requires alignment organised at three levels that mirror how society assures the safety of human clinical practice: 1) explicit...
| Authors | Gwydion Williams, Sara Zannone, Bilal A Mateen |
|---|---|
| Primary category | cs.AI |
| Published | 8 July 2026 |
| Last updated at source | 8 July 2026 |
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