Cybergrooming emerges as a growing threat to adolescent safety and mental health. One way to combat cybergrooming is to leverage predictive artificial intelligence (AI) to detect predatory behaviors in social media. However, these methods can encounter challenges like false positives and negative implications such as privacy concerns. Another complementary strategy involves using generative artificial intelligence to empower adolescents by educating them about predatory behaviors. To this end, we envision developing state-of-the-art conversational agents to simulate the conversations between adolescents and predators for educational purposes. Yet, one key challenge is the lack of a dataset to train such conversational agents. In this position paper, we present our motivation for empowering adolescents to cope with cybergrooming. We propose to develop large-scale, authentic datasets through an online survey targeting adolescents and parents. We discuss some initial background behind our motivation and proposed design of the survey, such as situating the participants in artificial cybergrooming scenarios, then allowing participants to respond to the survey to obtain their authentic responses. We also present several open questions related to our proposed approach and hope to discuss them with the workshop attendees.

翻译：网络诱拐已成为青少年安全和心理健康日益增长的威胁。应对网络诱拐的一种方法是利用预测性人工智能（AI）检测社交媒体中的捕食性行为。然而，这些方法可能面临误报等挑战以及隐私担忧等负面后果。另一种补充策略涉及使用生成式人工智能，通过教育青少年识别捕食性行为来增强其防范能力。为此，我们计划开发最先进的对话代理，模拟青少年与诱拐者之间的对话以用于教育目的。然而，关键挑战在于缺乏训练此类对话代理的数据集。在本立场文件中，我们阐述了赋能青少年应对网络诱拐的动机。我们提议通过针对青少年及家长的在线调查开发大规模真实数据集。我们讨论了相关背景动机及调查设计的初步构想，例如将参与者置于模拟网络诱拐场景中，通过调查收集其真实反应。同时，我们提出了若干与该方法相关的开放性问题，期待与研讨会参与者共同探讨。