How Data Science Can Be Used to Stop Human Trafficking
- Identifying At-Risk People
- Locating Victims
- Locating Traffickers
- Tracking Financial Information
- Disrupting Networks
People may tend to think of law enforcement and aid organizations instead of data scientists in fighting human trafficking. However, analysis of big data and the work of data scientists can play a significant role in stopping human trafficking. The ability of big data and data scientists to collect and analyze vast amounts of data and detect patterns within that data creates a number of opportunities to find victims and traffickers.
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1. Identifying At-Risk People
There are several factors that increase the likelihood that a person might be at risk for human trafficking. These include unemployment, poverty and escaping from a war-torn region. Data scientists can fight human trafficking by identifying these populations as well as locations where people might be vulnerable to false offers of employment or romance. Organizations can then direct resources toward these places.
2. Locating Victims
Big data can be used to identify when victims have contact with medical professionals or law enforcement in scenarios that suggest trafficking is taking place. For example, an article in The Conversation explains that victims may steal such items as sanitary supplies or soap since they may not be provided with them. Certain patterns in charges to hotels may also indicate that trafficking activity is underway. This may help locate traffickers themselves as well.
3. Locating Traffickers
There are additional ways to use data to locate traffickers online. Perhaps surprisingly, traffickers sometimes hide in plain sight, using social media or dating sites. Some individuals might change their identity frequently, but data analytics can use facial recognition and other technology to identify them. Just as analytics can identify at-risk populations, they can also identify events where human traffickers may be operating. They can then alert law enforcement as well as work to get structures in place to help victims.
4. Tracking Financial Information
IBM has developed a secure data hub to help banks and other financial institutions identify money laundering and other trafficking-related transactions. Both artificial intelligence and machine learning can be used by data scientists to fight human trafficking. The hub also gathers huge amounts of news feeds and other data to better identify how traffickers recruit and transport their victims. AI puts this information into a format that makes it usable for financial institutions along with both NGOs and governments.
5. Disrupting Networks
Disrupting networks requires the cooperation of law enforcement and governments. Unfortunately, in some countries, they are not always cooperative. However, data scientists can fight human trafficking through the use of sophisticated data analysis and help break up those networks. Data analysis can be used in several different ways to detect patterns indicating that human trafficking is occurring. It can analyze users, their interactions and their connections on social media to identify traffickers, victims, and customers.
Millions of people are trafficked into slavery each year working in many different industries, including factories, sex work, and domestic labor. Big data offers an unprecedented opportunity to find patterns that indicate trafficking. It is clear that there are growing opportunities in the years ahead for data scientists to fight human trafficking.