Rapid Risk Assessment Using AI-Enhanced Due Diligence: Trust and Safety Risk Identification via Public Signals and Human Judgment

This paper presents an applied governance case study of rapid trust and safety risk assessment in a professional context. It documents a structured decision-making process that combined AI-assisted open-source research with human judgment to evaluate potential safety, reputational, and ethical risks when formal institutional vetting was unavailable.The study contributes to emerging work in AI governance, organizational risk management, and human oversight by articulating a repeatable framework for precautionary, proportionate decision-making under uncertainty. Emphasis is placed on documentation, ethical restraint, and the role of practitioners as de facto gatekeepers in informal professional environments.Intended for researchers and practitioners in technology policy, institutional governance, and trust and safety, this paper bridges academic inquiry and real-world practice. It offers a model that can inform internal governance design, risk protocols, and professional due diligence standards.