Jeff Blom

Today the world is facing one of the greatest injustices in our society today, human slavery. The forcible enslavement of another human being for the purpose of exploitation is the worst form of inequality and debasement. Modern day slavery, also known as human trafficking, is categorized as "the recruitment, transport, transfer, harbouring or receipt of a person by such means as threat or use of force or other forms of coercion, abduction, fraud or deception for the purpose of exploitation" (UNODC, 2017). Global efforts to eradicate human trafficking have failed to have a significant impact on the global trafficking of persons. According to the U.S. Department of State Trafficking in Persons report, (2017) all these efforts have failed to reduce the number of trafficked persons, as millions of victims are still being exploited yearly around the world through forced labor and commercial sexual exploitation. The identification of victims, and their willingness to prosecute, has been the main challenge to law enforcement and why human trafficking will continue to be a low-risk, high-reward crime. (UNODC, 2017) This research will begin the process for the development of an operational theory of human trafficking, from which, an evidence-based learning agent will be developed that will help guide counter-human trafficking stakeholders in quickly and accurately determining the status of an individual through a structured and guided interview process.

This case study will focus on human trafficking interventions, but will specifically concentrate on prosecution, which is one particular aspect of the “3P paradigm – Prosecution, Protection, and Prevention, which continues to serve as the fundamental framework used around the world to combat human trafficking” (Trafficking in Persons Report. 2016. 7). This case study is intended to assist in the identification and disruption of organized human trafficking networks, specifically the process of moving victims through border crossings by traffickers by analyzing existing patterns of movements by the traffickers, which can then be used to guide disruptive and intervention strategies by border monitoring organizations.
    This poses the question, can existing crime theories, along with game theory simulations be used to create predictive models of trafficker movements which can be used to predict and then disrupt human trafficking networks?  By using a combination of rational choice theory, agent-based modeling, and discrete event simulation, predictive models can be developed to simulate trafficker movements across a border and to forecast changes in trafficker behaviors and the numbers of victims identified and intercepted by varying the number of monitors, time of day and days of the ​week. This case study is focused on the international border between Nepal and India