Detecting modern slavery in extended supply chains
a research project by the University of Kassel and the Technical University of Munich, funded by the Hans Böckler Foundation
Despite international efforts, nearly 50 million people worldwide are affected by modern slavery in 2021 (ILO, 2022). It is woven into global complex networks of supply chains and actors which makes it difficult to detect and prevent. To respond to these challenges, this research project leverages machine learning methods that enable the detection of non-obvious patterns and identification of risk factors in large datasets on modern slavery. With that, it seeks to provide data-based tools that improve transparency in supply chains and support civil society actors and researchers in responding to risks of modern slavery more effectively.
To achieve this, the research project is designed transdisciplinary, combining expertise in digital transformation (Department of Digital Transformation Management at the University of Kassel) with social sustainability and supply chain management (Chair of Sustainability Management at the TU Munich). In particular, we provide two research results:
= a comprehensive database with information on cases of modern slavery.
Large datasets of worldwide cases of modern slavery were systematically selected from sources, such as court case files, to filter and analyse those with a high risk of modern slavery.
= a machine-learning based tool to analyse cases and uncover underlying drivers of modern slavery.
Considering the perspective of AI ethics and users through intensive collaboration, this software prototype enables to analyze new cases of modern slavery, receive risk indications, and generate aggregated evaluations to support informed decision-making.