Issue
This project examined how an artificial intelligence platform designed to deliver actionable intelligence and identify institutional risks in relation to human rights violations, environmental abuses, and foreign malign influence can be used to assess risks across selected supply chains. This project provides an opportunity to test the capacity of investigatory processes and resolution assistance in assessing risks and provides a basis for identifying supply chain risks on a global scale.
Objectives
1) Define the necessary new risk typologies and data sets required for discovering supply chain risks. 2) Establish clear standards, definitions, and training data examples for target risk factors and supply chain vulnerabilities. 3) Train risk models and prove the ability of discovered features to identify threats optimizing for balance between minimal false positives and false negatives (precision and recall). 4) Demonstrate time and cost savings, as well as enhanced coverage by automating supply chain risk identification.
Value Propositions
This project represented a crucial advancement in the development of AI tools needed to help manage and mitigate supply chain vulnerabilities, while increasing the ability to detect hidden risks within supply chains, allowing for more informed decision-making.
As a result, Quantifind has contracted with the DHHS – ASPR, the House Select Committee on the Strategic Competition Between the United States and the Chinese Communist Party, and the U.S. Air Force AFWerx procurement to examine supply chain risks.
| Project Lead | Quantifind, Inc. |
| Research Team | PI: John Stockton, Ph.D., Quantifind Inc. Co-PI: Ari Tuchman, Ph.D., Quantifind Inc. Co-PI: Jennifer Roy, Quantifind Inc. |
| Budget | $729, 762 |
| Duration | Jan. 2023 – July 2024 |