Empathy and AI: Achieving Equitable Microtransit for Underserved Communities

Empathy and AI: Achieving Equitable Microtransit for Underserved Communities

Eleni Bardaka, Pascal Van Hentenryck, Crystal Chen Lee, Christopher B. Mayhorn, Kai Monast, Samitha Samaranayake, Munindar P. Singh

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence
AI for Good. Pages 7179-7187. https://doi.org/10.24963/ijcai.2024/794

This paper describes a newly launched project that will produce a new approach to public microtransit for underserved communities. Public microtransit cannot rely on pricing signals to manage demand, and current approaches face the challenges of simultaneously being underutilized and overextended. This project conceives of the setting as a sociotechnical system. Its main idea is to engage users through AI agents in conjunction with platform constraints to find solutions that purely technical conceptions cannot find. The project was specified over an intense series of discussions with key stakeholders (riders, city government, and nongovernmental agencies) and brings together expertise in the disciplines of AI, Operations Research, Urban Planning, Psychology, and Community Development. The project will culminate in a pilot study, results from which will facilitate the transfer of its technology to additional communities.
Keywords:
Agent-based and Multi-agent Systems: General
AI Ethics, Trust, Fairness: General
Multidisciplinary Topics and Applications: General