5th Year Master of MIDS student Ben Chu has been awarded the Summer 2021 Jack Larson Data Science for Good Fellowship for his work on improving supply chain transparency. The fellowship supports Master’s of Information and Data Science (MIDS) students who desire to use data science to benefit society.
Chu, a 2020 graduate of UC Berkeley with a degree in economics and minors in data science and music, said he never expected to use his data science skills in the fight against human exploitation. He studied development and labor economics abroad and knew he wanted to test his skills and work with real-world datasets to lead companies along sustainable paths of purchase.
So in the summer of 2021, he decided to forgo a desirable internship opportunity with a well-known aerospace company, and instead interned with FRDM, a small East Bay start-up trying to end human trafficking and forced labor by increasing transparency within the global supply chain.
FRDM works as a sort of 23andMe for global supply chains: any product or material supplied to their clients is deconstructed to its respective sub-manufacturers and analyzed for their risk of human trafficking. FRDM’s software helps to identify whether the conference room chairs your business is buying are tied to human trafficking and slave labor; their software identifies suppliers of risk in product genomes and incentivizes large corporations to buy better.
Chu worked to develop applications to expedite workflows and derive valuable information for FRDM, and constructed a program to extract names of sub-materials for client product genomes. “By identifying child materials of products (the subproducts of a product: for instance, the screws or wood used in the parent product of a conference table),” he explained, “you can then look at the Observatory of Economic Complexity country trade data for screws or wood, which can then help us understand the likelihood of supply chain risk.” Chu was also able to break down major country exporters within each requested item.
He also had the opportunity to design a web crawler article selector to analyze news articles in order to find ones that contained new information about human trafficking discoveries, and he used natural language processing to conduct sentiment analysis and categorize positive or negative news documents relating to such issues as child labor, court cases, and recent COVID-19 developments.
“These crucial improvements allowed us to swiftly identify products shipped from high-risk countries and provide updates to large corporations to combat human trafficking,” Chu said.
He’ll soon begin work with a government entity’s imports dataset and will assist companies in upgrading their yearly statements of supply chain transparency. He hopes to continue applying the knowledge gained in the MIDS program to improving labor conditions around the world.
“With the gift of cutting-edge data science tools, an advanced statistical background, and the passion to solve real-world problems, I foresee no limits to the change we can accomplish as the next generation of data scientists,” Chu said. “It’s our responsibility to use our talents to make ethically and morally just decisions that directly benefit the greater population.”