Summary

Many large-scale urban infrastructure systems, such as traffic networks and smart electric grids, serve self-interested users that interact non-cooperatively in a shared environment. The lack of coordination between users who seek to optimize their individual objectives often results in inefficient outcomes, which has spurred interest in the design of intervention and control schemes to cope with these efficiency losses by steering users towards system efficient outcomes. However, a vast majority of such control mechanisms (e.g., congestion pricing for road traffic mitigation) remain unimplemented as some users are made disproportionately worse off in the pursuit of system efficiency. Even worse, the efficacy of such control mechanisms relies on access to complete information on users’ attributes and preferences, which may not be available in practice.

Despite the lack of direct access to user preferences, the proliferation of user and system data unlocks opportunities to better inform the design of fair algorithmic decision making systems for large-scale urban infrastructure problems. While the machine learning community has demonstrated the power of gathering enormous amounts of data in applications such as reducing the bias of machine learning algorithms towards disadvantaged groups and making prescriptive real-time decisions in resource allocation problems (e.g., the allocation of food to food banks), the power of data to fairly operate urban infrastructure and networked systems is largely untapped. As a result, the goal of this workshop is two-fold. First, the workshop aims to provide a platform to discuss the problems of and explore new research directions geared towards addressing equity challenges in urban infrastructure systems. In doing so, the workshop will bring together researchers from across operations research, computer science, and transportation. Furthermore, the workshop will emphasize data-driven machine learning techniques to foster discussion at the intersection of fairness and learning in the context of urban infrastructure and networked systems.

Organizers

Alexandre Bayen (UC Berkeley)

Devansh Jalota (Stanford University)

Jessica Lazarus (UC Berkeley)

Marco Pavone (Stanford University)