Workshop on desiderata for a multimodal dataset for objectionable content detection

孩子和年轻人越来越依赖电子设备作为他们的主要娱乐来源。在这段屏幕时间内，用户可以在多种平台上观看电影、视频和玩网络游戏。虽然许多平台都有家长控制，但许多此类特定于应用程序的过滤器被发现不可靠，很容易被欺骗。有证据表明，让儿童和年轻观众接触令人反感的内容与青少年的暴力行为、过早开始性行为和酒精使用以及儿童的焦虑和恐惧有关。因此，迫切需要开发能够帮助检测不良内容的人工智能方法。开发这项技术需要新的研究基础设施，其形式是一个广泛的存储库，其中包含目前不存在的一致标记的电影和视频内容。通过迷你研讨会系列，研究团队将为设计和创建这个新的不良内容存储库奠定基础。由此产生的基础设施将有助于推动技术进步，为为年轻用户提供更安全的在线空间这一关键目标做出贡献。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Kids and young adults are increasingly relying on electronic devices as their main source of entertainment. During this screen time, users can watch movies, videos, and play online games on a multitude of platforms. While many platforms have parental controls, many of these app-specific filters have been found to be unreliable and easy to deceive. Exposing kids and young viewers to objectionable content has been documented to correlate with violent behavior and early initiation of sex and alcohol usage in teenagers, and anxiety and fear among children. Therefore, there is an urgent critical need to develop Artificial Intelligence methods that can help detect objectionable content. Developing this technology requires new research infrastructure in the form of an extensive repository of consistently labeled movies and video content that currently does not exist. Through the mini-workshop series, the research team will lay the groundwork to design and create this new repository of objectionable content. The resulting infrastructure will help advance technology that will contribute to the crucial goal of providing a safer online space for young users.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.