Leveraging Victim Voices: Unveiling True Needs Through Natural Language Processing in Trauma Narratives

Abstract

This article explores the intersection of technology, particularly artificial intelligence and anti-human trafficking and child sexual exploitation (CSE) initiatives. Despite the promises of technology, the overall effectiveness in addressing these crimes is limited. The authors argue that a key factor contributing to this limitation is the insufficient understanding of the crimes, rooted in the absence of meaningful engagement with victims. To address these challenges, the authors propose two strategies. First, they advocate for data-sharing partnerships to access extensive textual data held by organizations. Second, they highlight the use of natural language processing (NLP) to systematically analyse victim narratives without causing further interview fatigue. Embracing NLP is seen as a way to expedite research, enhance scalability and provide a fresh perspective on combating human trafficking and CSE. The article is structured to define key terminology, make a case for a victim-led response, demonstrate the application of NLP and conclude with insights from in-house research. The authors urge stakeholders to consider this new approach in their efforts to combat human trafficking and CSE.