Teachers vs. Chat GPT: identifying and naming acts of online sexual abuse

Abstract

Digital media and social networks offer adolescents a space for various social and sexual interactions. While the internet fosters healthy sexual exploration, it also facilitates online sexual abuse, such as non-consensual intimate image creation or dissemination, sextortion, sexual harassment, grooming, and gender-based hate speech. This abuse often goes underreported, especially when parents and teachers minimize or blame victims, or fail to recognize the abuse. This study examined how Israeli teachers and artificial intelligence (AI) identify and attribute blame in cases of sexual abuse. Six vignettes, depicting various sexual scenarios, were presented to 153 teachers and analyzed by ChatGPT-3.5 and ChatGPT-4. Findings revealed that teachers struggled to identify online sexual abuse and often blamed victims. ChatGPT-3.5 also tended to blame victims, but ChatGPT-4 accurately identified the abuse without victim-blaming. The study suggests GPT-4 can be an effective tool for identifying and naming sexual abuse when teachers lack proper training.