用过程式支持提升生成式AI辅助决策，避免人类认知被替代。
Augmenting Human Cognition With Generative AI: Lessons From AI-Assisted Decision-Making
- 采用渐进式支持，让用户参与解决过程而非直接接收答案
- 实验显示过程式支持提升用户决策质量与控制感
- 适合需要人机协作的复杂任务场景
本文通过回顾我们在人工智能辅助决策领域的研究，探讨如何设计不取代人类认知、而是增强其能力的生成式AI工具。当前主流做法是向用户提供端到端的AI生成解决方案，用户可接受、拒绝或修改。另一种方式是提供更渐进的支持，帮助用户自主完成任务，称为过程导向支持。我们分析了端到端方案的挑战，并验证过程导向支持在复杂决策任务中的有效性。基于近期使用大语言模型（LLMs）的对比实验，发现过程导向支持能显著提升用户对决策过程的掌控感与最终结果质量，为生成式AI在认知增强场景的设计提供了实践启示。
原文摘要 · Abstract (English)
How can we use generative AI to design tools that augment rather than replace human cognition? In this position paper, we review our own research on AI-assisted decision-making for lessons to learn. We observe that in both AI-assisted decision-making and generative AI, a popular approach is to suggest AI-generated end-to-end solutions to users, which users can then accept, reject, or edit. Alternatively, AI tools could offer more incremental support to help users solve tasks themselves, which we call process-oriented support. We describe findings on the challenges of end-to-end solutions, and how process-oriented support can address them. We also discuss the applicability of these findings to generative AI based on a recent study in which we compared both approaches to assist users in a complex decision-making task with LLMs.
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