Designing Conversational AI systems to support older adults requires these systems to explain their behavior in ways that align with older adults' preferences and context. While prior work has emphasized the importance of AI explainability in building user trust, relatively little is known about older adults' requirements and perceptions of AI-generated explanations. To address this gap, we conducted an exploratory Speed Dating study with 23 older adults to understand their responses to contextually grounded AI explanations. Our findings reveal the highly context-dependent nature of explanations, shaped by conversational cues such as the content, tone, and framing of explanation. We also found that explanations are often interpreted as interactive, multi-turn conversational exchanges with the AI, and can be helpful in calibrating urgency, guiding actionability, and providing insights into older adults' daily lives for their family members. We conclude by discussing implications for designing context-sensitive and personalized explanations in Conversational AI systems.

翻译：设计支持老年人的对话式AI系统时，需要系统以符合老年人偏好和情境的方式解释其行为。尽管先前研究强调了AI可解释性在建立用户信任中的重要性，但关于老年人对AI生成解释的需求和认知仍知之甚少。为填补这一空白，我们与23名老年人开展了一项探索性的快速约会研究，以了解他们对情境化AI解释的反应。我们的研究结果揭示了解释的高度情境依赖性，其形态受对话线索（如解释的内容、语气和框架）的影响。我们还发现，解释常被理解为与AI进行的交互式多轮对话交流，有助于调节紧迫感、指导行动可行性，并为家庭成员提供洞察老年人日常生活的窗口。最后，我们讨论了设计情境敏感且个性化的对话式AI系统解释的实践意义。