‘Democratizing AI in transportation through international Collaboration: A case study of Open-Source mobility platforms in the Global South
Article / Journal
Author(s) / editor(s):
Mahesh Chougule
Year: 2026
Language(s): English
Abstract:
This article examines how international collaboration (North–South and South–South) and open-source mobility platforms can democratize AI in transportation by enabling capacity building, technology transfer and local adaptation for public transport optimization and traffic management. Through comparative case studies, it identifies enablers—shared ethical frameworks, mutual learning, decentralized innovation and transparent data-sharing—and barriers—infrastructure gaps, policy misalignments and power asymmetries in data and algorithm design. It argues that well-structured partnerships enhance transparency, local agency and culturally sensitive applications, and offers policy recommendations (multilateral support, open standards, co-creation) for equitable AI in transport and broader global AI governance.
https://doi.org/10.1016/j.trip.2025.101801
Post created by: Virginia Signorini