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Using technology to stop human trafficking

AI, facial recognition, geo-location and innovative solutions can be applied to get the general public involved in identifying and reporting suspected victims.

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Participants of the worldwide Walk For Freedom marching silently in Berlin last month. Citizens' understanding and assistance are crucial, as their support and vigilance are key to spurring action by the public, private, and not-for-profit sectors.

IT WAS in December 1865, exactly 154 years ago, that slavery was legally outlawed in the United States when the 13th Amendment was ratified and passed on Dec 6 that year. That, however, has not stopped the trade in human beings. On the contrary, men, women and children seeking a better life are tricked all the more into travelling far from home and forced into what amounts to modern slavery.

Forced labour in the private economy generates US$150 billion in illegal profits per year, about three times more than previously estimated, according to a new report from the International Labour Organization (ILO). The ILO report Profits and Poverty: The Economics of Forced Labour notes that 66 per cent, or US$99 billion, comes from commercial sexual exploitation, while another US$51 billion is the result of forced economic exploitation, including domestic work, agriculture and other exploits.

In a recent UK case that is being investigated for trafficking or illegal smuggling of Vietnamese people, more than half the victims were suspected to be female and children. Today, nearly 40.3 million people worldwide are affected. Nearly one million people are trafficked across American borders each year, according to the US State Department. The FBI names human trafficking the third-largest criminal activity in the world, after drugs and white-collar crimes.

Even in Singapore, the Ministry of Manpower is currently prosecuting the first labour trafficking case resulting in a sentence in Singapore since 2015, when the Prevention of Human Trafficking Act came into effect. There are currently three labour trafficking cases before Singapore's courts. The accused were found guilty of abusing their power to exploit their employees by various means, including verbal abuse, onerous financial penalties, controlling their movements and forced prostitution.

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It is time to look at modern slavery, not just from the physical and emotional toll it exacts on its victims, but from a financial lens as well. Modern slavery is a pervasive financial crime with horrible human consequences. As such, it demands pursuit of its financial masterminds; better coordination between government, the general public, companies and not-for-profit organisations; improved collaboration that transcends borders; and the use of technology to follow the trail that trafficking leaves behind.

For example, a trafficking network was unearthed in Britain during the summer of 2019, in which Polish victims were tricked into manual labour. Groups of conspicuously fatigued, nervous or disoriented people took up residence in the same, rundown places where they would work. They were not allowed to speak for themselves, and their bank accounts were controlled by their captors. They were accompanied by more affluent appearing people when performing routine errands or going to banks. Banks and financial institutions in Asia may have a pivotal role, given that Asia is a key source and easy target for traffickers.

The paradox about human trafficking is that many victims are hidden in plain sight. However, most people are reluctant to get involved as they may be unclear about who to notify, or are unsure of any ongoing investigations. Citizens' understanding and assistance are crucial, as their support and vigilance are key to spurring action by the public, private, and not-for-profit sectors.

With advances in new technologies such as artificial intelligence (AI), facial recognition, geo-location and apps development, innovative solutions can be designed and applied for the general public to also get involved in identifying and reporting suspected human trafficking cases.

Use tech to tackle

Until recently, isolated and relatively small databases held by organisations existed, and the information contained was not easily shared, narrowly focused, and did not have AI to help analysts. Now, that is about to change in a major way.

Non-governmental organisations (NGOs) such as Stop The Traffik have addressed these concerns with solutions such as Stop App - a free app that supports eight languages and allows submissions to be made from anywhere in the world, quickly and anonymously via a range of mediums, including text messages, photos and video - to be reviewed by expert analysts.

The Stop App was designed through a collaborative process between IBM Ireland's TechForGood team and the subject matter experts at Stop The Traffik. The analytics is done by Stop The Traffik data scientists who can then alert authorities if the circumstances warrant action.

Behind the scenes, there is now more coordination and better technology to analyse information. One such promising development is the first international data clearinghouse that connects NGOs, law enforcement and financial institutions. These include Liberty Shared, Europol, Western Union, Barclays, and Lloyd's Banking Group. This Traffik Analysis (TA) Hub enables members to collect, share and analyse data in the digital cloud. AI is applied to analyse clues and unexpected patterns of data that betray the movement and machinations of trafficking rings.

The TA Hub is probably the first always-on AI resource that bridges public, private and not-for-profit sectors worldwide. With 100,000 meta-data rows, it is already one of the largest repositories of data describing possible trafficking-related activity. One could not have imagined this to be a reality till a few years ago. But today, combined with the power of AI and cloud services, technology is helping the world save millions of lives and billions of dollars

How can you or members of the public get involved? First, download the Stop App from the relevant app store. Then find a safe way to capture evidence to submit in the app. If you suspect that someone is being taken by traffickers and they are in immediate danger, report it to the relevant authorities first, and then on the app.

By combining shared data, AI and machine learning, law enforcement will be better able to analyse and match incident patterns, and can generate predictive analyses of future incidents based on the volume and history of incidents at a certain location. The agencies can get more success in enforcement actions against traffickers.

Why can't the police handle this alone? Law enforcement, even when effectively combined with the rescue and rehabilitation of survivors, is not enough to alleviate human trafficking. To stop the problem, multiple agencies need to be part of the effort and put the latest technologies to use. In fact, the TA Hub will enable anti-trafficking analysts to do their jobs more quickly and efficiently by automating manual processes for collecting open-source intelligence

The TA Hub also helps predict future incidents of human trafficking before they occur. For example, if there are a certain number of incidents reported during a specific time of year with a similar financial pattern, one could better predict these occurrences happening in advance.

The genesis of the tech lies in using AI's natural language processing (NLP) capabilities. After gathering insights about what analysts were primarily interested in learning, IBM trained Watson AI in 2019 on what terms were most important. Watson will learn more terms over time, using additional public data.

The combination of training the model specifically for the human trafficking domain with both private and public data will allow NGO analysts, bank associates, law enforcement officers and intelligence officers to go beyond what they currently know and bring the perpetrators to justice.

  • The writer is CEO and chairman, IBM Asia-Pacific