To be able to train robots to think, act and react like human beings has intrigued experts worldwide. The response to the launch of ChatGPT, which prompted almost every individual to explore the chatbot and interact with it, showcases the curiosity around AI and how the unfamiliar experience has drawn people to it.
In the technology world, Artificial Intelligence and Machine Learning are predicted to be game changers where almost every aspect of the field is expected to be integrated with highly skilled AI tools, software and eventually machines.
However, can the advancement in AI tools help rescue a 12-year-old abducted from her home in Maharashtra, trafficked to Kolkata and forced into prostitution? Can AI be used to bridge the gap and help children, women and men who are struggling to break away from the shackles of modern slavery?
According to a market research report published by Fortune Business Insights, the global AI market size is projected to grow from USD 387.45 billion in 2022 to USD 1394.30 billion in 2029 at a CAGR of 20.1% in the forecast period.
Parallelly, the number of people trafficked and forced into modern slavery has risen significantly over the years. The latest Global Estimates of Modern Slavery noted that there are over 50 million people – approximately one of every 150 — forced to work against their will, whether in the form of sex work, bonded labor, domestic servitude or forced marriage. More than 3.3 million of these are children.
Despite the awareness projects, nationwide enforcement campaigns, and combined work of government agencies and non-profit organizations, the situation has failed to improve, and more people have been pushed into modern slavery.
Criminal networks profit an estimated $150 billion a year via 40 million victims worldwide, a Forbes report stated. India (7,989,000), China (3,864,000), North Korea (2,640,000), and Nigeria (1,386,000) are among the countries with the highest prevalence of modern slavery
In the year 2025, the United Nations aims to end forced child labor and, by 2030, abolish all slavery. However, to achieve these targets, it is essential to not only tackle the issue head-on but also make the most of the current AI technology to win the fight against human trafficking and modern slavery.
Understanding Modern Slavery
The United Nations Office on Drugs and Crime (UNODC) describes human trafficking as “the recruitment, transportation, transfer, harboring or receipt of people through force, fraud or deception, with the aim of exploiting them for profit.” However, over the years, human trafficking, as a phrase, has switched over to modern slavery, explains Matthew Friedman, CEO of The Mekong Club and Global Expert on modern slavery.
“Earlier, the term human trafficking was selected because many of the cases initially had a person go from one country to another. Trafficking is the movement of something in order to exploit it. Over time, people said, why are we focusing on the movement? Shouldn’t we focus on exploitation?”
“So, when you look at a person who doesn’t get paid, can’t leave a situation, and other things, the closest word was slavery. But because people think of slavery that happened a long time ago, they put the word modern before it. So, modern slavery is the outcome of human trafficking. It’s just been redefined for this day and age. But as they say, over 50 million people continue to be in this situation,” adds Friedman.
Based in Hong Kong, Friedman is the founder of The Mekong Club, a non-profit organization that works along with the private sector to bring about sustainable practices against modern slavery across the globe. Established in 2011, through his organization, Friedman has built a community across various industries and is working towards creating a slave-free world.
Can AI tools be used to help fight modern slavery?
Over the past years, Friedman elaborated on how the evolution of the tech industry has trickled its way into his work. Citing an example, Friedman shared an incident where he and his team developed a tool to track responses from workers at a factory they had to audit.
“The auditor goes up to the workers and gets them to press the flag from where they come from. And then, with headphones on attached to the phone, it would ask them about 20 questions in their language. Some of them are safe, but others may reveal vital information, such as do you have any indebtedness? Do you work overtime and not get paid? Do you have your passport being withheld by somebody? And then, they answer these questions honestly. Through this simple technology, you are able to identify the extent to which there’s exploitation in a factory that in the past, despite being audited 20 times, were never found.”
In 2019, the Mekong Club, the key partner for UNUMACAU’s Apprise Audit app, was awarded the Public Affairs Asia (PAA) Gold Standard Award in the “Thought Leadership” category for their work and contribution in “harnessing technology to end modern slavery” for the digital application
While Friedman and his team are spreading awareness and focusing on various procedures, techniques, methods and platforms to combat modern slavery, a US-based artificial intelligence company, Marinus Analytics, is developing and providing AI tools to law enforcement to help them disrupt human trafficking, child abuse and cyber fraud.
Based in Pittsburgh, Pennsylvania, Marinus Analytics is an internationally recognized women-owned start-up. Their mission, as described by the company’s website, is to protect the vulnerable and end systemic exploitation.
At 16, Emily Kennedy found purpose during her trip through Europe when she spotted street children being exploited by the Russian mob. “In Eastern Europe, we came across orphans begging on the streets, and the Russian mob had forced them to bring back any money they made that day. If the children didn’t make their daily quota, they would be punished,” she told the AWS Blog. “It struck me that this kind of exploitation was a reality, and then I quickly learned that similar abuse also happens in the United States, particularly through sex trafficking.”
In 2014, Emily Kennedy, along with Cara Jones, converted her passion into her mission and founded Marinus Analytics. Their team of engineers and data scientists at the company provide SaaS applications to get “actionable insights out of big data for detectives, social workers, and cyber fraud investigators that enable data-driven, people-centric responses in the modern age.”
Via its flagship tool Traffic Jam, the company has managed to assist law enforcement officers in speeding up investigations, catching human traffickers, recovering missing persons and more.
The company claims to have saved an estimated 70,000 investigative hours in 2020, recovered a missing person within a week of her going missing and arrested a trafficker, who was earning around $250,000 a year by exploiting over 20 women.
Using purpose-driven algorithms and analyzing data, the AI tool played a crucial role in disrupting organized criminal networks.
Polaris, formerly known as Polaris Project, is another US-based non-profit organization that has been extensively using data analysis to combat human trafficking. Named after the North Star, which was a historical symbol of freedom, the organization was founded in 2002 with the aim to combat and prevent sex and labor trafficking.
Over the years, Polaris has evolved its workings to adapt to the rapidly changing nature of the illegal human trade. Polaris, which runs the U.S. National Human Trafficking Hotline, is reportedly building the largest known U.S. data set on trafficking incidents and is using this data to advance its research to identify and disrupt trafficking networks.
Since its inception, Polaris has analyzed hundreds of thousands of human trafficking cases and created a classification system that is able to identify 25 types of human trafficking in the United States. The organization has also partnered with the tech industry to create better tools to gather and analyze information.
How AI tools can help detect suspicious activities related to human trafficking and modern slavery
It is interesting to note how various AI tools can help accelerate manual procedures, especially in terms of unstructured data.
Say, for instance, if a person has gone missing, the usual procedure would include manually matching the picture with the data available online. However, via tools such as Traffic Jam, detectives and investigators can instantly get assistance and scan through thousands and millions of online ads, websites and more to get faster results.
Such tools can also assist in detecting patterns, networks and a vast amount of uncharted information. Carrie Chai, Director, AI and Machine Learning, AML/ATF Risk Models, along with her team, has created two AI-based models for financial services company Scotiabank to detect child sexual exploitation and another to detect human trafficking related to sexual exploitation.
According to a Scotiabank report, these two models use machine-learning techniques to observe and detect transactional data that include online withdrawals, use of credit cards, electronic money transfers and more to co-relate and connect these with suspicious activities linked to human trafficking criminal mafias.
“It’s usually a combination of red flags and suspicious transactional behaviours in the context of a network or criminal ring that give the whole story,” Chai said in the report.
Another research revealed an algorithm developed to scan and detect escort similarities in escort advertisements to identify human traffickers and victims.
The Fredkin Professor in Artificial Intelligence in CMU’s School of Computer Science, Christos Faloutsos stated in a CMU report that the algorithm could assist law enforcement during their investigation. The team claimed that the algorithm “InfoShield” outperformed others and was able to identify trafficking ads with 85% precision.
At present, AI tools are no more limited to certain sectors and are being explored by experts to tap the benefits of this advancement. It is evident that AI tools can be utilized to not only fight modern slavery but also provide approachable options for victims and survivors.
AI – the double edge sword
While AI tools visibly are a way forward, they can be equally exploited by traffickers and criminal gangs. A large percentage of people recruited into forced labor or sex trafficking are targeted and trapped through chat rooms, social networking, advertisement, and so forth.
Friedman explained how across Asia, a person works for over 14 hours a day to scam people highlighting how organized people in these crime networks are.
“You have phony websites, phony apps, phony data collection mechanisms, and so forth that are being developed. And so there are manuals, and there’s training. The people in organised crime are using technology as a means to both traffic people, and then to use it to go after these people at the same time.”
AI technology obviously is a double edge sword, which law enforcement, government organizations and NGOs need to crack in order to stay one step ahead of criminals in today’s day and age.
According to a FintechFutures report, traffickers are adopting various tools to evade detection, such as acquiring legitimate assets that include bank accounts, insurance numbers and bank details. This also allows the victim to be exploited further by forcing them into supply chain jobs without giving access to the bank accounts.
It is essential for employment and law enforcement agencies to spot these loopholes and use analytics to detect these links and prevent violations. Enhanced screening using AI tools can assist in tracking those perpetrating slavery.
Moreover, data fusion techniques in machine learning are also able to extract more from both structured and unstructured data, helping various agencies in building evidence and creating detailed knowledge graphs to track cases and criminal networks.
The integration of data fusion and AI tools can play a key role in fighting and drastically reducing the exponentially high number of people forced into modern slavery. However, the potential of the field is yet to be tapped into, and more data, analytics, and visualization tools need to be incorporated and used in order to win the fight.
