The State Department estimates that as many as 800,000 people are trafficked across international borders every year with about half of those children. These individuals, about 80 percent female, are forced into prostitution or other involuntary servitude.
This is not just an international problem, but one that is prevalent here in the United States. In fact, as many as 17,500 people are trafficked into the United States each year, with California and Texas serving as hotbeds of activity. Industrialized countries account for nearly half of the illegal money made each year through human trafficking.
Government organizations, law enforcement agencies, healthcare providers and private companies around the world continue to fight this scourge. Despite these efforts, though, human trafficking has remained the third-largest criminal industry in the world, trailing only illegal drugs and arms trafficking.
Human trafficking remains one of the world’s largest humanitarian problems, as well. The organizations trying to stop it need all tools available at their disposable. That is where advanced analytics, machine learning, and artificial intelligence can begin to make a real difference.
The Value of Text Analytics in Human Trafficking
Analytics, machine learning, and artificial intelligence have already shown their merit in helping organizations address social issues. Analytics have been used to combat the opioid epidemic, improve high school graduation rates, fight fraud, and many other areas of concern.
With human trafficking, organizations have already found success using text analytics. As its name implies, text analytics is the process of taking data from written documents and turning it into larger insights.
For example, the State Department publishes more than 200 reports each year about human trafficking in various countries. Organizations can use text analytics to look through these reports to find patterns. Before text analytics, organizations would have to read through these reports manually to find insights. Not only is this process time-consuming, but it relies entirely on human analysts who may miss some possible connections or insights.
By combing text analytics with machine learning and artificial intelligence, as well as insight and overview by analysts, organizations can gain deeper understanding of the subject. They can use visualization technologies to better find connections or to more clearly understand trends and use that information to help make decisions.
Creating an Enterprise Framework to Support Analytics
As noted, analytics technologies work with available data sets to help find new connections and insights that were unclear or undetected before. These discoveries can then be used to create new programs and policies, adjust actions already in place, or help decision makers rethink overall strategies. And, this type of system could certainly benefit those helping to reduce human trafficking.
The goal for organizations involved in the fight against human trafficking should be to develop an enterprise framework that supports analytics. This framework would:
- Improve the accuracy of their current programs using strategic data and visualizations. This will provide stakeholders with a more complete picture of what is happening, improving strategic decisions.
- Improve specific responses to certain situations. For example, law enforcement officials in the field could have better guidelines for shared characteristics of human trafficking cases.
- Create an enhanced data model that would improve how organizations organize and categorize human trafficking events. This would take existing data models and enhance them, or create entirely new models from previously unstructured data to provide new insights.
- Increase the number of data sources without the need to add additional analytical operations. Envision a system where state and local law enforcement can share information with national security agencies, hospitals, departments of motor vehicles or any other organization that can link individuals to draw connections and anomalies.
An enterprise framework would allow these organizations to enhance how they currently use analytics. While some of these organizations have taken advantage of these technologies, a more organized architecture built with analytics in mind could create a sizable difference in the ability to use, understand, and create actionable outcomes with data.
The Path Forward
It is with this kind of framework that organizations can truly use analytics to provide full value. In doing so, they can be better equipped to fight human trafficking.
Like most issues today, human trafficking is made up of many components. There is no silver bullet to magically make the problem disappear. It takes a multi-pronged approach and requires those involved to be able to truly look at the problem, but also be flexible to changing conditions to alter approaches as needed.
January is National Human Trafficking Awareness Month, but the issue should be a focus year-round. Organizations should do everything in their power to enhance their ability to fight this horrible injustice. An enterprise framework to support analytics capabilities would do a lot to move that needle.