arXiv：cs.AI· Michaela Benk, Kacper Sokol·· 16 小时前
信任阻碍人机双向对齐：NeurIPS 2026 工作坊论文提出 AI 辅助决策三新维度
Trust Hinders Bidirectional Human-AI Alignment
AI 导读
NeurIPS 2026 BiAlign 工作坊论文指出，信任校准框架将 AI 辅助决策过度窄化为"适当依赖"，作者提出三个维度重新理解这一问题：信任 AI 只是管理不确定性的策略之一，信任校准在"大世界"决策问题中常被误用，此类场景下人机对齐需处理更高阶的决策过程。
正文
Abstract:Trust calibration remains the dominant framing of AI-assisted decision making: the goal is to close the gap between perceived and actual trustworthiness of AI systems so that users exhibit appropriate reliance on them. We argue that this approach, while useful for decision problems that are well-defined and clearly scoped, overly restricts what it means to make a decision with AI support. To overcome this limitation, we develop three dimensions of AI-assisted decision making. First, trusting AI is only one of several possible strategies for managing uncertainty. Second, trust calibration is often misapplied when AI models "large-world" decision problems, i.e., ill-defined situations where goals and states are only partially known or unknowable. Third, in such settings human-AI alignment requires addressing higher-order decision processes. We conclude by reflecting on the implications of our observations on the design of process-oriented human-AI coupled systems that jointly identify and negotiate uncertainty throughout the decision-making task.
| Comments: | 40th Conference on Neural Information Processing Systems (NeurIPS 2026). Workshop: Dynamic Alignment in Human-AI Coupled System (BiAlign Workshop) |
| Subjects: | Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC) |
| Cite as: | arXiv:2610.15136 [cs.AI] |
| (or arXiv:2610.15136v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.15136 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Michaela Benk [view email]
[v1]
Sat, 10 Oct 2026 19:26:37 UTC (43 KB)
来源：arXiv：cs.AI · arxiv.org