OSINT Helps Law Enforcement Detect and Prevent Human Trafficking

In Cambodia, 10,000 people — often entire families, including children — work as bonded laborers in the massive brick kilns that fuel China’s construction industry.[1] Kiln owners lend money to destitute Cambodian farmers, then use those debts to trap borrowers into labor — often for generations. When borrowers die or grow too frail to work, debts are transferred to their children. 

In the United Kingdom, a 14-year-old Ukrainian girl seeks asylum after a Russian airstrike kills her parents. While she stays at a shelter awaiting processing, a British man offers her a waitressing job. Chasing employment, she leaves the shelter to follow him. The man enslaves this child as a sex worker.[2]

An African nurse responsible for the financial support of her entire family is recruited for a high-paying job in Lebanon. Upon her arrival in the Middle East, the “recruiter” steals her passport and forces her to work as a caregiver for his elderly mother, under abusive conditions and without pay.[3]

Human trafficking is a worldwide travesty. Increasingly, border security organizations, law enforcement agencies and other government entities and non-governmental organizations turn to open-source intelligence (OSINT) technologies to help stop the scourge.

The scope of human trafficking

The United Nations defines human trafficking, in part, as recruiting, harboring, or obtaining a person for labor “through the use of force, fraud, or coercion … for the purpose of involuntary servitude, peonage, debt bondage, or slavery.”[4] According to Global Estimates of Modern Slavery: Forced Labour and Forced Marriage, 27.6 million worked in forced labor during any given day in 2021.[5] This population includes children forced into labor, and adults and children trafficked for sex work. In fact, the United Nations Office on Drugs and Crime estimates that 20% of human trafficking victims worldwide are children.[6]

The problem is so severe that more than 180 countries have ratified or acceded to the United Nations Protocol to Prevent, Suppress, and Punish Trafficking in Persons.[7] And Target 8.7 of the United Nations Sustainable Development Goals calls for “immediate and effective measures to eradicate forced labour” and “end human slavery.”[8]

Prosecution challenges

Human trafficking is big business. According to the International Labour Organization, the crime generates profits of about $150 billion annually.[9]

Traffickers are difficult for border security and law enforcement agencies to detect and prosecute.[10] The State Department's Trafficking in Persons Report notes that, while there were more than 15,150 prosecutions for human trafficking globally in 2019, many more cases go uninvestigated.[11]

Several factors make trafficking hard to spot. First, traffickers prey on vulnerable people who may never be officially listed as “missing”[12]: the young; people living in extreme poverty; people without a strong family or social network; people living in politically disorganized or unstable regions; and people living through natural disasters. Second, trafficked persons are unlikely to ever report the crime; they too often blame themselves for their predicament.[13]

Third, law enforcement officials often suffer from lack of understanding of trafficking crimes.[14] Officers frequently mistake trafficked agricultural workers for illegal aliens. Women trafficked for sex are mistaken for prostitutes. They are treated as criminals rather than victims. Finally, tight budgets often leave law enforcement agencies without the funding for personnel to detect and prosecute traffickers.[15]

Border security and law enforcement agencies need a more insightful approach to trafficker detection. The Trafficking in Persons Report notes that “effective partnerships for furthering investigations can be established between actors with data-collection capabilities” and “intelligence sharing skills.”[16] New OSINT technologies are vital to those partnerships.

AI-powered data analysis helps stop human trafficking

We live in a world with more data than ever before. In fact, analysts estimate that roughly 90 percent of the world’s data has been created over just the last two years.[17] Properly examined, this information can provide law enforcement with the insights needed to halt human trafficking.

Babel Street Insights is an AI-powered OSINT platform that searches thousands of sources of publicly available information (PAI) and commercially available information (CAI) for indications of human trafficking. These include dozens of social media sites worldwide, along with millions of message boards, online comments, and public chats. Babel Street Insights scours this information to identify keywords associated with trafficking and can alert users in border security and law enforcement agencies.

The Insights platform further enhances investigations through searches of the deep web and dark web — or web sites that are inaccessible by standard search engines. Because the nature of the tools used to access the dark web ensure anonymity, it is a hotbed of illegal activity — including human trafficking. Deep- and dark-web search capabilities enable investigators to quickly and efficiently find information they wouldn’t otherwise be able to access. Persistent search technology keeps search operations running regardless of whether someone is actively using them, recording updates and changes, then automatically appending this information to search terms.

How can these capabilities help law enforcement detect human traffickers? Investigators may find a foreign company advertising on Facebook, targeting impoverished people in their country with offers of suspiciously well-paying overseas agricultural jobs or domestic positions. They may find men continuously advertising for female companions. (Dating sites have emerged as a vector for sex trafficking.) They may find suspicious postings for overseas jobs that appear at the time of a natural disaster — when vulnerable people are desperate to leave their countries. Any of this information may indicate human trafficking.

Using Babel Street can help border security and law enforcement officials:

• Analyze PAI, CAI and deep- and dark web data for insights into trafficking patterns, criminal recruitment methods, and recruitment advertising
• Use geolocation and telemetry data to track suspected human traffickers during surveillance and enforcement operations, increasing the likelihood of successful outcomes
• Close the Risk-Confidence Gap, or the widening divide between the escalating volume and variety of data that must be examined to identify potential traffickers, and the resources organizations have available to monitor that data

New, AI-powered OSINT technologies can help border security and law enforcement agencies stem the horrors of human trafficking. 

End Notes

1. United States Department of State, “Trafficking in Persons Report 2023,” accessed October 2023, https://www.state.gov/reports/2023-trafficking-in-persons-report/

2. Ibid

3. Ibid

4. United Nations Office on Drugs and Crime, “Human Trafficking,” accessed October 2023, https://www.unodc.org/unodc/en/human-Trafficking/Human-Trafficking.html

5. International Labour Organization, “Statistics on Forced Labour, Modern Slavery and Human Trafficking,” accessed October 2023, https://www.ilo.org/global/topics/forced-labour/statistics/lang--en/index.htm

6. United Nations Office on Drugs and Crime, “UNODC report on human trafficking exposes modern form of slavery,” accessed October 2023, https://www.unodc.org/unodc/en/human-trafficking/global-report-on-trafficking-in-persons.html

7. United Nations, “Protocol to Prevent, Suppress and Punish Trafficking in Persons, Especially Women and Children, supplementing the United Nations Convention Against Transnational Organized Crime,” November 2000, https://www.ohchr.org/en/instruments-mechanisms/instruments/protocol-prevent-suppress-and-punish-trafficking-persons

8. United Nations Sustainable Development Goals, accessed October 2023, https://www.unodc.org/roseap/en/sustainable-development-goals.html#:~:text=Target%208.7%20%2D%20Take%20immediate%20and,labour%20in%20all%20its%20forms.

9. International Labour Organization, “Statistics on Forced Labour, Modern Slavery and Human Trafficking,” accessed October 2023, https://www.ilo.org/global/topics/forced-labour/statistics/lang--en/index.htm

10. United States Department of State, “Trafficking in Persons Report 2023,” accessed October 2023, https://www.state.gov/reports/2023-trafficking-in-persons-report/

11. Ibid

12. National Institute of Justice, “Federally Backed Human Trafficking Task Force Models Yields Progress and Opportunities for Continued Growth,” January 2022, https://nij.ojp.gov/topics/articles/federally-backed-human-trafficking-task-force-model-yields-progress#note1

13. United States Department of State, “Trafficking in Persons Report 2023,” accessed October 2023, https://www.state.gov/reports/2023-trafficking-in-persons-report/

14. International Labour Organization, “Statistics on Forced Labour, Modern Slavery and Human Trafficking,” accessed October 2023, https://www.ilo.org/global/topics/forced-labour/statistics/lang--en/index.htm

15. United States Department of State, Trafficking in Persons Report 2023,” accessed October 2023, https://www.state.gov/reports/2023-trafficking-in-persons-report/

16. Ibid

17. Duarto, Fabio, “Amount of Data Created Daily (2023),” Exploding Topics, April 3 2023, https://explodingtopics.com/blog/data-generated-per-day

Disclaimer: 

All names, companies, and incidents portrayed in this document are fictitious. No identification with actual persons (living or deceased), places, companies, and products are intended or should be inferred.