Discouraging the Demand That Fosters Sex Trafficking: Collaboration through Augmented Intelligence

• NCJ Number: 308288
• Journal: Societies Volume: 13 Issue: 4 Dated: 2023
• Author(s): Marcel Van der Watt
• Date Published: 2023
• Length: 21 pages
• Grant Number(s): 2020-75-CX-0011
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical)
• Award: A National Assessment of Demand Reduction Efforts, Part II: New Developments in the Primary Prevention of Sex Trafficking

Annotation

This study examines the use of augmented intelligence to combat technology-facilitated sex trafficking.

Abstract

This paper explores the issue of technology-facilitated trafficking in the online sexual exploitation marketplace and juxtaposes this with the use of augmented intelligence in collaborative responses to these crimes. Augmented intelligence—as the fusion of human and artificial intelligence—is effectively being employed in response to a spectrum of risks and crimes that stem from the online sexual exploitation marketplace. As part of a study that was sponsored by the National Institute of Justice, the National Center on Sexual Exploitation has documented 15 tactics that have been used in more than 2650 US cities and counties to deter sex buyers from engaging with prostitution and sex trafficking systems. One of these tactics, technology-based enforcement and deterrence methods, has been used in more than 78 locations in the United States. Illustrative case studies are presented that describe how two organizations employ technology that utilizes the complementary strengths of humans and machines to deter sex buyers at the point of purchase. The human(e) touch of these organizations, combined with artificial intelligence, natural language processing, constructed websites, photos, and mobile technology, show significant potential for operational scaling, and provide a template for consideration by law enforcement agencies, criminal justice systems, and the larger multidisciplinary counter-trafficking community for collaborative replication in other settings. (Published Abstract Provided)