Virginia Tech Researchers Build AI Chatbot to Train Teens Against Cybergrooming

Computer science researchers at Virginia Tech are developing an artificial intelligence chatbot designed to safely expose teenagers to simulated cybergrooming tactics. As first reported by TechXplore, the interactive tool leads young users through escalating conversational scenarios to teach them how to identify online predatory tactics and practice protective responses.

The initiative aims to pivot internet safety strategies from reactive threat detection to early preventive education. Principal investigator Jin-Hee Cho, an associate professor in Virginia Tech's Department of Computer Science, explained that while existing research primarily targets identifying offender behavior, this project focuses on strengthening potential victims by giving them tools to spot manipulative patterns before abuse occurs.

The simulation builds upon empirical findings presented in a paper titled "From Vulnerable to Resilient: Examining Parent and Teen Perceptions on How to Respond to Unwanted Cybergrooming Advances," presented at the May 2026 Association for Computing Machinery Conference on Human Factors in Computing Systems. Lead author Xinyi Zhang and the research team found that 60 percent of surveyed teenagers reported facing online sexual solicitation—a figure drastically higher than estimates provided by surveyed parents.

To realistically replicate digital threats, the chatbot models the six recognized stages of cybergrooming: establishing initial contact, building trust, assessing engagement risks, creating exclusive relationships, introducing sexual solicitations, and trying to transition interactions toward physical encounters. The software dynamically adapts its responses based on the teenager's decisions, illustrating how specific replies can either de-escalate tension or heighten vulnerability.

Development of the software was split between technical engineers building the underlying AI models and a human-centered design group validating content through testing sessions with volunteer youth. Pamela J. Wisniewski, a principal research scientist at the UC Berkeley-affiliated International Computer Science Institute, noted that the model avoids treating every digital contact as an immediate hazard, allowing participants to navigate realistic social settings and learn boundary management as interactions progress.

Balancing educational accuracy with safety requirements required strict ethical guardrails. Sang Won Lee, an associate professor of computer science at Virginia Tech and project team member, noted that the web platform will eventually allow teens to sign up independently, offering hands-on training on how bad actors manipulate trust over extended periods without exposing users to actual harm.

A beta release of the application is currently undergoing adjustments through collaborative design workshops with teenagers to refresh existing behavioral datasets. The project leaders hope the framework will establish a precedent for future software applications aimed at safeguarding vulnerable demographics through interactive safety instruction.