论文标题
在线面对虐待语言：从道德和人权的角度进行的调查
Confronting Abusive Language Online: A Survey from the Ethical and Human Rights Perspective
论文作者
论文摘要
互联网上滥用内容的普遍性会导致严重的心理和身体伤害。 Significant effort in Natural Language Processing (NLP) research has been devoted to addressing this problem through abusive content detection and related sub-areas, such as the detection of hate speech, toxicity, cyberbullying, etc. Although current technologies achieve high classification performance in research studies, it has been observed that the real-life application of this technology can cause unintended harms, such as the silencing of under-represented groups.我们回顾了大量关于自动滥用探测的NLP研究，并将重点放在道德挑战上，该研究组织了大约八个既定的道德原则：隐私，问责制，安全和安全，透明度和解释性，公平性和非歧视性，人类对技术，专业责任和促进人类价值的控制。在许多情况下，这些原则不仅与情境伦理守则有关，这可能与上下文有关，而且实际上与普遍人权有关，例如隐私权，免于歧视和言论自由。我们强调了需要研究该技术的广泛社会影响，并将道德和人权的考虑到应用程序生命周期的每个阶段，从任务配方和数据集设计，到模型培训和评估，再到应用程序部署。在这些原则的指导下，我们为享有权利的，社会技术解决方案找到了几个机会，以检测和面对在线虐待，包括“裸露”，“隔离”，价值敏感的设计，反叙事，风格转移和AI-drien驱动的公共教育应用。
The pervasiveness of abusive content on the internet can lead to severe psychological and physical harm. Significant effort in Natural Language Processing (NLP) research has been devoted to addressing this problem through abusive content detection and related sub-areas, such as the detection of hate speech, toxicity, cyberbullying, etc. Although current technologies achieve high classification performance in research studies, it has been observed that the real-life application of this technology can cause unintended harms, such as the silencing of under-represented groups. We review a large body of NLP research on automatic abuse detection with a new focus on ethical challenges, organized around eight established ethical principles: privacy, accountability, safety and security, transparency and explainability, fairness and non-discrimination, human control of technology, professional responsibility, and promotion of human values. In many cases, these principles relate not only to situational ethical codes, which may be context-dependent, but are in fact connected to universal human rights, such as the right to privacy, freedom from discrimination, and freedom of expression. We highlight the need to examine the broad social impacts of this technology, and to bring ethical and human rights considerations to every stage of the application life-cycle, from task formulation and dataset design, to model training and evaluation, to application deployment. Guided by these principles, we identify several opportunities for rights-respecting, socio-technical solutions to detect and confront online abuse, including `nudging', `quarantining', value sensitive design, counter-narratives, style transfer, and AI-driven public education applications.
