Combining AI and OR/MS for Better Trustworthy Decision Making – Bridge Program



Combining AI and OR/MS for Better Trustworthy Decision Making
For information about current and past AI + ORMS bridges, please consult the following pages:
Description of the Bridge Program
Artificial Intelligence (AI), including Generative AI, and Operations Research/Management Science (OR/MS) offer proven but distinct approaches to decision-making with data and models. However, challenges persist in applying them to vital socio-technical environments where human and artificial systems interact. These include the need to combine AI and OR/MS for the best solution, aligning models with human values and promoting trust, and the expertise and time required for their application, which limit wider use.
Main Objectives
It is the goal of this bridge program to unite AI and OR/MS practitioners and researchers to improve trustworthy decision-making in key socio-technical areas such as supply chains, healthcare, crisis management, homeland security, robotics, wildlife conservation, medicine, transportation, and finance. It aims to equip them with better tools by familiarizing them with each other’s techniques and domains, and bringing the disciplines together to advance the research and application at the intersection of AI and OR/MS so as to improve decision-making.
Topics
- Utilizing AI, OR/MS, and their integration for decision-making.
- Exploring current state-of-the-art research and identifying new directions in combining AI and OR/MS for improved trustworthy decision-making, including integrating Large Language Models with OR/MS and other AI tools to democratize advanced decision-making capabilities and integrating OR/MS and AI to improve trustworthiness.
- Identifying key domains and use cases where AI and OR/MS can improve decision-making.
Bridge Steering Committee
- J. Christopher Beck (University of Toronto) – jcb@mie.utoronto.ca
- Sven Koenig (University of California, Irvine) – sven.koenig@uci.edu
- Michela Milano (Università di Bologna) – michela.milano@unibo.it
- Willem-Jan Van Hoeve (Carnegie Mellon University) – vanhoeve@andrew.cmu.edu
- Segev Wasserkrug (IBM Research) – segevw@il.ibm.com
