The purpose of the case study is to demonstrate how social media and police (law enforcement) may work together in a thoughtful, ethical, and humanitarian way. By fusing human intelligence with intelligent systems, the case study contends, extraordinary accomplishments can be achieved. Additionally, it underlines the importance of the public-private partnership (PPP) model, in which the joint efforts of two parties; Uttar Pradesh Police (UPP) India and Facebook, representing the public and private sectors, respectively produced incredible results. Phenomenal achievements were made possible by this relationship, and numerous suicide attempts were averted. The case study reviewed cases between March 2022 and February 2024 and found that 321 precious lives were saved due to this partnership. The case study demonstrates how Facebook’s algorithm works to spot any posts that contain language that suggests self-harm or suicide and to issue a warning in the hopes of protecting a precious life. The UP Police’s social media unit gets notified of such posts, thanks to Facebook’s random forest learning algorithms, which then take action to save a priceless life. The case sheds some insight on the privacy concerns of Facebook account holders, the use of sophisticated technology by the police authorities, and its ethical implications as well. It provides some insight into the relevance of management principles to public services.

该案例研究的目的是展示社交媒体和警察（执法部门）如何以深思熟虑、道德和人道主义的方式合作。该案例研究认为，通过将人类智能与智能系统融合，可以取得非凡的成就。此外，它还强调了公私合作（PPP）模式的重要性，在这种模式中，两方共同努力；印度北方邦警察局 (UPP) 和代表公共和私营部门的 Facebook 分别取得了令人难以置信的成果。这种关系使取得了非凡的成就成为可能，并避免了许多自杀企图。该案例研究回顾了2022年3月至2024年2月期间的案例，发现321条宝贵的生命因这种伙伴关系而被拯救。该案例研究展示了 Facebook 的算法如何发现任何包含暗示自残或自杀语言的帖子，并发出警告，以保护宝贵的生命。借助 Facebook 的随机森林学习算法，UP 警察的社交媒体部门会收到此类帖子的通知，然后采取行动拯救无价的生命。该案件让人们对 Facebook 账户持有人的隐私问题、警方对尖端技术的使用及其道德影响有了一些了解。它提供了一些关于管理原则与公共服务的相关性的见解。