Non-profit organizations such as the Anti-Human Trafficking Intelligence Initiative help to partner with law enforcement agencies and private sector companies to pool together resources in the fight against human trafficking.

"We have many partners that collaborate with us to develop innovative ways in which we can us their software, tools, and resources in the fight against human trafficking. Many of the companies that we work with are practicing corporate responsibility around a number of issues, not only human trafficking. Our partnerships are mutually beneficial to the organizations we collaborate with as we help to introduce them to other organizations, financial institutions and law enforcement while receiving their assistance and resources in combating trafficking."

- Aaron Kahler, Founder and CEO of Anti-Human Trafficking Intelligence Initiative (ATII)

One of the apps that the Anti-Human Trafficking Intelligence Initiative developed is an app that can be used on the victim’s cell phones. Victims can scan QR codes that are put up in the bathrooms of hotels, and other highly suspicious public places. Once the data is received, law enforcement can follow up on the lead by requesting a subpoena immediately to obtain cell phone records to verify whether it is indeed criminal activity. Once that occurs, victims can be rescued immediately as opposed to waiting for days.

Private and Public Sector Cooperation Enables Technology

Money laundering is at the center of any crime organization. When profits from illegitimate businesses mix with profits from legitimate businesses, it’s difficult to untangle the web of financial transactions inside the organization. Forensic Accounting is often used to track the finances of crime organizations. In the last few years, law enforcement built tools to uncover patterns of irregular financial activities. However, public sector technology still relies on data reported by the private sector banking industry.

"The problem with detecting human trafficking is that it’s not easy to identify what is a good transaction from a bad one. You can have an example of a business that’s booking hotel rooms frequently. That’s showing up on bank records. With AI and machine learning, you can bring in other information to associate that with information related to human traffickers."

- Alma Agnotti, Partner, Practice-Leader - Global Investigations and Compliance at Guidehouse

In the U.S., per the Bank Secrecy Act (BSA), each bank is required to send a Suspicious Activities Report (SAR) to government agencies as a part of enforcing money-laundering laws. The accuracy of this report becomes increasingly important when AI and machine learning are involved.

"If your system or your bank is 95% wrong in your Suspicious Activities Report (SAR) from last year, by the way this is the standard right now,  then when you bring in machine learning, you are going to very efficiently re-create all the mistakes that you made last year."

- Dr. Gary M. Shiffman, Founder of Giant Oak

In March 2019, Dr. Shiffman testified in front of the House Subcommittee on National Security, International Development, and Monetary Policy about the importance of data cooperation between private sector banks and public sector law enforcement agencies. The legislative intent for the suspicious activities report is to help law enforcement agencies to identify terrorism, money laundering, drug trafficking, and human trafficking. But, the current implementation prevents the banks from obtaining relevant data to build good models to generate the right data to send to law enforcement to impact investigations.

"The banks spend a lot of money generating SARs everyday to send it to FinCEN. In the absence of knowing which of their SARs are highly valued or not valued, the banks do not send SARs that are valuable and can impact outcomes. There needs to be a three way communication loop established between banks, regulators (FinCEN) and law enforcement. Law enforcement can inform on what data they’d like to see and the banks can cooperate in sending that information through the regulators."

- Dr. Gary M. Shiffman, Founder of Giant Oak

Technological Cooperation Implies Responsibility

As AI and machine learning proliferate into corporate settings, there’s a real sense that the world is working closely together. A programmer in India may assist in a project located in the U.S..That project can be deployed in Europe where most of the user base are located. The underlying data that AI and machine learning learns from can come from anywhere in the world.

The world’s problems such as human trafficking, money laundering, drug trafficking and terrorisms become problems in every country and can affect the activities in many industries regardless of the size of the company and the size of the marketplace.

Responsibility still resides on the humans that are making judgments on when to use the technology and how to use the technology.

"People who are in favor of technology and against technology are both a little bit wrong. By that, I mean that technology, AI and machine learning, at its core is pattern recognition. You need a good training set to identify the pattern that you want to find. You need clean data that you can run your algorithm through to identify the pattern. There could be problems in your training data. There could be problems in the data that you are running your algorithm against. You need a human in the loop to ensure that someone’s applying human reasoning, common sense, and judgement to the inputs and output."

- Dr. Gary M. Shiffman, Founder of Giant Oak

The human factor in the usage of technology not only impacts the outcome of human trafficking investigations but ultimately has a real impact on the GDP of specific countries. From government’s loss of tax revenue, to decreased sector competition and innovation, to loss of investment, to increase in uncertainty of market conditions, there are many reasons why GDP depends on a healthy economy with minimal criminal activities.

When law enforcement and financial institutions look at human trafficking investigations as entrepreneurial business activities of criminal organizations, then it’s easy to realize the potential impact on the domestic economy as well as on the global economy.

So, who is ultimately responsible for solving this problem of human trafficking?

As machine learning and AI tells us, in the age of innovation, we have powerful technological tools to impact outcomes. But ultimately, it’s still all of us who are responsible for our collective problem of human trafficking.