AI辅助用户学习如何写出有同理心的反仇恨言论。
Designing Human-AI Collaboration to Support Learning in Counterspeech Writing
- 通过三阶段流程引导用户理解仇恨言论并构思回应
- 20人实验显示用户能自信地独立撰写反制内容
- 适合想提升网络对话能力的普通用户
在线仇恨言论在社交媒体上日益普遍，对个人与社会造成伤害。尽管自动化内容审核受到广泛关注，但用户自发的反仇恨言论仍是一个较少探索却前景广阔的方向。然而，许多人难以写出有效回应。我们提出CounterQuill，一个以人为本的协同系统，帮助普通用户通过反思与协作来撰写具有同理心的反仇恨言论——并非自动生成回复，而是通过教育实现自我表达。该系统基于计算思维设计三阶段工作流：(1) 学习环节，建立对仇恨言论与反仇恨言论的理解；(2) 头脑风暴环节，识别有害模式并构思回应策略；(3) 协作写作环节，在保持个人语调的同时优化回应内容。通过一项包含20名参与者的用户研究发现，CounterQuill有效提升了用户在全过程中的信心与自主控制感。研究揭示了AI可通过结构化、以用户为中心的工作流，协助人们识别、反思并应对网络仇恨言论。
原文摘要 · Abstract (English)
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.
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