Disrupting Illicit Supply Networks: New Applications of Operations Research and Data Analytics to End Modern Slavery

Report from a 2017 National Science Foundation workshop on promising research directions for applications of operations research and data analytics toward the disruption of illicit supply networks like human trafficking. The workshop was funded by the NSF’s Operations Engineering (ENG) and the Law & Social Sciences Program (SBE) under grant # CMMI-1726895. The report addresses the opportunity to apply advances from the fields of operations research, management science, analytics, machine learning, and data science toward the development of disruptive interventions against illicit networks. Such an extension of the current research agenda for trafficking would move understanding of such dynamic systems from descriptive characterization and predictive estimation toward improved dynamic operational control.Bureau of Business Researc

A Survey of Operations Research and Analytics Literature Related to Anti-Human Trafficking

Human trafficking is a compound social, economic, and human rights issue occurring in all regions of the world. Understanding and addressing such a complex crime requires effort from multiple domains and perspectives. As of this writing, no systematic review exists of the Operations Research and Analytics literature applied to the domain of human trafficking. The purpose of this work is to fill this gap through a systematic literature review. Studies matching our search criteria were found ranging from 2010 to March 2021. These studies were gathered and analyzed to help answer the following three research questions: (i) What aspects of human trafficking are being studied by Operations Research and Analytics researchers? (ii) What Operations Research and Analytics methods are being applied in the anti-human trafficking domain? and (iii) What are the existing research gaps associated with (i) and (ii)? By answering these questions, we illuminate the extent to which these topics have been addressed in the literature, as well as inform future research opportunities in applying analytical methods to advance the fight against human trafficking.Comment: 28 pages, 6 Figures, 2 Table

The Big Data of International Migration: Opportunities and Challenges for States under International Human Rights Law

This is the author accepted manuscript. The final version is available via HeinOnline.Technology, as the epitome of our contemporary society, permeates the realm of international migration. Migrants and refugees are increasingly using mobile phones and digital features available online to prepare for migration and while on the move. Concurrently, advances in computer science allow for progressively more accurate analysis of the data generated by mobile devices and online searches. In particular, big data can be used to determine specific behavioural patterns, geolocation and human interactions. This article investigates the implications of these technological advances for States under international human rights law. It argues that big data can and should be used as a tool for the protection of migrants’ human rights by enhancing both decision-making and measures to prevent unnecessary deaths at sea, ill-treatment and human trafficking of migrants. Consequently, the article examines whether the development of new technologies can affect States’ capabilities for the identification of individuals in need of protection. It posits that to the extent that protection is mandated by human rights instruments, States may have a positive obligation to use available technologies to identify and assist vulnerable migrants. It evaluates this possibility against the protection of migrants’ right to life, the prohibition of torture, inhuman and degrading treatment, and the prohibition of slavery and forced labour. In doing so, the article also emphasizes the limits and risks posed by the unrestrained use of new technologies, notably with respect to the protection of migrants’ right to privacy and data protection

Good Tech, Bad Tech: Policing Sex Trafficking with Big Data

Technology is often highlighted in popular discourse as a causal factor in significantly increasing sex trafficking. However, there is a paucity of robust empirical evidence on sex trafficking and the extent to which technology facilitates it. This has not prevented the proliferation of beliefs that technology is essential for disrupting or even ending sex trafficking. Big data analytics and anti-trafficking software are used in this context to produce knowledge and intelligence on sex trafficking. This paper explores the challenges and limitations of understanding exploitation through algorithms and online data. It also highlights the key dimensions of exploitation ignored in big data-oriented research on sex trafficking. By doing so, the paper seeks to advance our theoretical understanding of the trafficking–‍technology nexus, and it is argued that sex trafficking must be reframed along a continuum of exploitation that is sensitive to the social context of exploitation within the sex market

Data analytics and human trafficking

Human trafficking is recognized internationally as an extreme form of violence against women, children, and men. Despite the fact that human trafficking is universally understood to be a burgeoning social problem, a paucity of data and insight into this issue exists. Data analytics has immense potential to elucidate trends in complex social data and inform future policy. We undertook a design science-inspired research approach to build datasets on human trafficking. Three prototypes are presented that describe the methodologies of human traffickers, display correlations between calls reporting suspected trafficking activity and various demographic data, and explicate the effectiveness of US anti-trafficking funding projects