用户如何感知混合倡议式AI：在解决问题中对帮助的态度
How Users Perceive Mixed-Initiative AI: Attitudes Toward Assistance in Problem Solving
AI总结：
研究探讨了混合倡议式AI中帮助交付方式对用户感知的影响，发现预设定时器方式能提升用户对AI的积极评价，即使预算有限。
摘要：
在混合倡议系统中，AI帮助的交付方式可能与帮助本身一样具有决定性影响。我们研究了两种帮助交付方式：按需帮助（用户通过按钮请求）和预先安排的帮助（在用户选定的时间间隔内提供帮助，用户操作会重置定时器）。为了评估这些方式，我们选择了“ Rush Hour ”谜题作为人机协作任务，因为它们捕捉了现实世界问题解决中的元素，如分析、资源管理以及在约束条件下做决策。为了提高生态效度，我们对时间和AI帮助施加了货币成本，模拟了人们必须在时间压力、财务限制或机会成本等隐性或显性权衡中做出平衡的场景。尽管在两种方式下的任务表现相当，但使用预先安排（定时器）方式的参与者对AI的积极感知更强烈，即使他们的最终预算较低。这表明，帮助的交付方式可以独立于任务结果影响用户体验，表明人机系统可能需要在提高任务表现的同时，考虑如何交付AI帮助。
英文摘要：
In mixed-initiative systems, the mode of AI assistance delivery can be as consequential as the assistance itself. We investigated two assistance delivery modes: on-demand help (users request via Button) and pre-scheduled help (assistance delivered at user-selected intervals, with user actions resetting the Timer). To evaluate these modes, we selected Rush Hour puzzles as the human-AI collaborative task because they capture elements of real-world problem solving such as analysis, resource management, and decision-making under constraints. To enhance ecological validity, we imposed monetary costs for both time and AI assistance, simulating scenarios where people must balance implicit or explicit trade-offs such as time pressure, financial limitations, or opportunity costs. Although task performance was comparable across modes, participants who used the pre-scheduled (Timer) mode reported more positive perceptions of the AI, even when their ending budget was low. This suggests that assistance delivery mode can shape user experience independent of task outcomes, indicating that human-AI systems may need to consider how AI assistance is delivered alongside improving task performance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
