设计人机协作以支持反言论写作中的学习
Designing Human-AI Collaboration to Support Learning in Counterspeech Writing
AI总结：
本文提出CounterQuill人机协作系统，通过三阶段工作流程教育用户学习识别仇恨言论、头脑风暴并共同撰写反言论，用户研究表明其能帮助用户自信地掌握反言论写作技能。
摘要：
在线仇恨言论在社交媒体上日益泛滥，对个人和社会造成伤害。尽管自动化内容审核已受到广泛关注，但用户驱动的反言论（counterspeech）仍是一种探索较少但前景广阔的方法。然而，许多人在撰写有效回应时面临困难。我们介绍了CounterQuill，一个人类与AI协作的系统，帮助普通用户撰写富有同理心的反言论——不是通过生成自动回复，而是通过反思和回应来教育他们。CounterQuill遵循基于计算思维的三阶段工作流程：（1）学习环节，建立对仇恨言论和反言论的理解；（2）头脑风暴环节，识别有害模式并构思反言论想法；（3）共同写作环节，帮助用户完善其反回应，同时保留个人声音。通过一项用户研究（N = 20），我们发现CounterQuill帮助参与者培养了自信且可控地进行头脑风暴和起草反言论的技能。我们的研究结果突显了AI系统如何通过结构化、以人为中心的工作流程来支撑复杂的沟通任务，教育用户如何识别、反思并回应在线仇恨言论。
英文摘要：
Online hate speech has become increasingly prevalent on social media, causing harm to individuals and society. While automated content moderation has received considerable attention, user-driven counterspeech remains a less explored yet promising approach. However, many people face difficulties in crafting effective responses. We introduce CounterQuill, a human-AI collaborative system that helps everyday users with writing empathetic counterspeech - not by generating automatic replies, but by educating them through reflection and response. CounterQuill follows a three-stage workflow grounded in computational thinking: (1) a learning session to build understanding of hate speech and counterspeech, (2) a brainstorming session to identify harmful patterns and ideate counterspeech ideas, and (3) a co-writing session that helps users refine their counter responses while preserving personal voice. Through a user study (N = 20), we found that CounterQuill helped participants develop the skills to brainstorm and draft counterspeech with confidence and control throughout the process. Our findings highlight how AI systems can scaffold complex communication tasks through structured, human-centered workflows that educate users on how to recognize, reflect on, and respond to online hate speech.
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。
