Designing for Fairness in Human-Robot Interactions

TL;DR

This paper explores how robots can be designed to understand and apply fairness principles in human-robot interactions, especially within multi-human teams, to improve collaboration and group dynamics.

Contribution

It introduces approaches for enabling robots to consider human notions of fairness in decision-making within team settings.

Findings

Robots can be programmed to allocate resources fairly among humans.

Fair decision-making by robots enhances team performance.

Incorporating fairness principles improves human-robot collaboration.

Abstract

The foundation of successful human collaboration is deeply rooted in the principles of fairness. As robots are increasingly prevalent in various parts of society where they are working alongside groups and teams of humans, their ability to understand and act according to principles of fairness becomes crucial for their effective integration. This is especially critical when robots are part of multi-human teams, where they must make continuous decisions regarding the allocation of resources. These resources can be material, such as tools, or communicative, such as gaze direction, and must be distributed fairly among team members to ensure optimal team performance and healthy group dynamics. Therefore, our research focuses on understanding how robots can effectively participate within human groups by making fair decisions while contributing positively to group dynamics and outcomes. In this paper, I discuss advances toward ensuring that robots are capable of considering human notions of fairness in their decision-making.