Human-AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support
Human-AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support
复制标题
人类-人工智能协作在基于文本的点对点心理健康支持中实现更多移情对话
DOI：
10.1038/s42256-022-00593-2
复制
发表时间：
2023-01-01
影响因子：
23.8
通讯作者：
Althoff, Tim
中科院分区：
文献类型：
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作者：
Sharma, Ashish;Lin, Inna W.;Althoff, Tim
人工智能（AI）的进步使一些系统能够辅助人类并与人类协作，以执行诸如安排会议和检查文本语法等简单的机械性任务。然而，这种人机协作在更复杂的任务上带来了挑战，比如进行有同理心的对话，这是因为AI系统在处理复杂的人类情感方面面临困难，而且这些任务具有开放性。在此，我们聚焦于点对点的心理健康支持，在这种情境下，同理心对成功至关重要，并研究AI如何与人类协作，以在文本形式的在线支持性对话中促进同伴间的同理心。我们开发了HAILEY，一种AI介入式智能体，它提供即时反馈，以帮助提供支持的参与者（同伴支持者）对寻求帮助的人（受助者）做出更有同理心的回应。我们在TalkLife（N = 300）这个大型在线点对点支持平台上，通过一项非临床随机对照试验，让现实中的同伴支持者对HAILEY进行了评估。我们发现，我们的人机协作方法使同伴之间对话中的同理心总体上提高了19.6%。此外，我们发现在那些自认为在提供支持方面有困难的同伴支持者子样本中，同理心提高得更多，达到了38.9%。我们系统地分析了人机协作模式，发现同伴支持者能够直接和间接地使用AI反馈，而不会过度依赖AI，同时在反馈后报告自我效能有所提高。我们的研究结果展示了反馈驱动的、AI介入式写作系统在诸如有同理心的对话等开放性、社会性和高风险任务中赋予人类能力的潜力。在过去十年中，AI语言建模和生成方法发展迅速，为人机协作开辟了充满希望的新方向。我们开发了一种名为HAILEY的AI介入式对话系统，以增强同伴支持者对心理健康受助者做出有同理心回应的能力。
Advances in artificial intelligence (AI) are enabling systems that augment and collaborate with humans to perform simple, mechanistic tasks such as scheduling meetings and grammar-checking text. However, such human-AI collaboration poses challenges for more complex tasks, such as carrying out empathic conversations, due to the difficulties that AI systems face in navigating complex human emotions and the open-ended nature of these tasks. Here we focus on peer-to-peer mental health support, a setting in which empathy is critical for success, and examine how AI can collaborate with humans to facilitate peer empathy during textual, online supportive conversations. We develop HAILEY, an AI-in-the-loop agent that provides just-in-time feedback to help participants who provide support (peer supporters) respond more empathically to those seeking help (support seekers). We evaluate HAILEY in a non-clinical randomized controlled trial with real-world peer supporters on TalkLife (N = 300), a large online peer-to-peer support platform. We show that our human-AI collaboration approach leads to a 19.6% increase in conversational empathy between peers overall. Furthermore, we find a larger, 38.9% increase in empathy within the subsample of peer supporters who self-identify as experiencing difficulty providing support. We systematically analyse the human-AI collaboration patterns and find that peer supporters are able to use the AI feedback both directly and indirectly without becoming overly reliant on AI while reporting improved self-efficacy post-feedback. Our findings demonstrate the potential of feedback-driven, AI-in-the-loop writing systems to empower humans in open-ended, social and high-stakes tasks such as empathic conversations.AI language modelling and generation approaches have developed fast in the last decade, opening promising new directions in human-AI collaboration. An AI-in-the loop conversational system called HAILEY is developed to empower peer supporters in providing empathic responses to mental health support seekers.