Let’s Build A World Where Child Labor and Manufacturing Are Not Synonomous

AI, collaboration with law enforcement, and supply chain visibility detection is shining a light on the reporting of potential human trafficking and forced labor.

Last year, we wrote about forced child labor, human trafficking, how the supply chain  creates an ecosystem for these to thrive, and what we need to start doing to interrupt these crimes against humanity. Since that supply chain human trafficking article went live, so much has changed, and I wanted to share those updates with you, because the more lights we shine into the darkness, the less we can’t see.

There’s A Lot of Darkness

According to the International Labour Organization, Human Trafficking is a one hundred fifty billion dollar industry with forty million victims today who might be making your clothes, cleaning your hotel room, or building a sports arena as modern day slaves. This is happening all around us. California, has three of the top five US cities cited for human trafficking abuses: San Francisco, Los Angeles, and San Diego. Right now, there are over forty million men, women, and children in labor and sex slavery and here is the most important you should know about that number:

Statistics are on the rise and don’t reflect the actual number or breadth and depth of human trafficking in the United States and abroad.

Kimberly Adams, Founder of Flying Bridges, a business that is making the connections between law enforcement, brands, and technology, has been developing a reporting and tracking tool called Griffin – a machine learning tool to share and gather information across sectors but will help business – who are also victims of human trafficking – detect criminal networks infiltrating their supply chain. Adams noted when I checked in with her recently:

“We are excited to use the power of AI to, and for the first time, accurately report the number of human trafficking cases and detect vulnerable populations and their traffickers.  Currently, most human trafficking cases are misclassified as domestic violence, child abuse, labor violations or prostitution. Moreover because of its complex definition, involving the use of fraud, coercion​, or force, victims rarely report or understand they have been trafficked.  This creates policies and enforcement resource allocations that cannot possibly combat human trafficking. Machine learning is ideal for this and Griffin is being designed to identify and report the bigger picture.”