SBIR Phase I: Safeguard Kids and Maintain Privacy

这项小型企业创新研究(SBIR)第一阶段提案通过使用人工智能技术监控文本交流并实时通知他们的父母潜在危险，使10-14岁儿童的在线和数字互动更加安全。10-14岁的年轻人尤其容易受到在线活动风险的影响，因为他们是虚拟世界的新手，他们很可能是第一次拥有个人通信设备。父母希望他们的孩子有自由和隐私来使用他们的设备，但担心其中的风险。该项目将导致开发一款移动应用程序，该应用程序可以实时监控文本通信，并在检测到潜在危险(例如，在线掠夺、网络欺凌和/或校园暴力)或危险行为(例如，吸毒和酗酒，和/或自我伤害)时向家长发出警报，以便父母可以干预以保护他们的孩子。这款应用程序将为市场上现有的产品提供一个有吸引力的替代方案，因为它有复杂的人工智能引擎，而且它不收集和传输手机的所有数据-该解决方案降低了数据泄露的风险，同时仍能让父母了解情况。这个小企业创新研究(SBIR)第一阶段项目正在通过开发一种完全在移动设备上运行并根据用户的活动定制的检测算法来推动人工智能和机器学习技术的发展。与大型语言模型不同，大型语言模型是通用和广泛的，因此需要在中央服务器上进行大量计算，而这种技术将占用很小的空间，并针对每个家庭进行个性化和调整。在整个项目中，该团队将直接从年轻人那里收集和标记文本交流，并使用这些数据来提高算法的准确性，以精确度和召回率衡量。该项目团队还将开发这项技术，以收集和处理流行型号手机的数据，并在需要时提醒家长。该项目将开发一款移动应用程序，实时监控文本交流，并在发现潜在危险或危险行为时向父母发出警报，以便他们能够主动采取行动，保护自己的孩子免受伤害。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。

This Small Business Innovation Research (SBIR) Phase I proposal is making online and digital interactions safer for children between the ages of 10 – 14 years of age by using artificial intelligence technology to monitor text communication and inform their parents of potential danger in real-time. Youth aged 10 – 14 years are particularly vulnerable to the risks of online activity since they are newcomers to the metaverse and they are likely getting a personal communication device for the first time. Parents want their kids to have the freedom and privacy to use their devices but fear the risks involved. This project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger (e.g., online predation, cyberbullying, and/or school violence) or risky behaviors (e.g., drug and alcohol use, and/or self-harm), so parents can intervene to protect their child. The app will provide an attractive alternative to existing products on the market because of its sophisticated artificial intelligence engine and because it does not collect and transfer all the phone’s data – the solution reduces the risk of data leaks while still keeping parents informed.This Small Business Innovation Research (SBIR) Phase I project is advancing the state of artificial intelligence and machine learning technologies by developing a detection algorithm that runs entirely on a mobile device and is tailored to the user’s activity. Unlike large language models, which are general and wide-ranging, and thus require a lot of computing at a central server, this technology will have a small footprint and be personalized and adapted for each family. Throughout this project, the team will collect and label textual communication directly from youth and use the data to improve the algorithm’s accuracy, as measured by precision and recall. The project team will also develop the technology to collect and process the data on popular models of cell phones and to alert the parent when needed. The project will result in the development of a mobile app that monitors text communication in real-time and alerts parents if it detects potential danger or risky behaviors, so they can act proactively to protect their children from harm.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.