Regulating Highly Automated Robot Ecologies: Insights from Three User Studies

TL;DR

This paper presents three user studies analyzing how regulatory power, decision support, and autonomy affect the effectiveness of regulating highly automated robot ecologies, providing insights for designing better regulatory systems.

Contribution

It offers novel empirical insights into the interactions between regulators and HARE, highlighting how certain mechanisms can impact social welfare and system success.

Findings

Regulator power can reduce social welfare in HARE.

Decision support systems influence regulation effectiveness.

Adaptive autonomy can diminish overall system performance.

Abstract

Highly automated robot ecologies (HARE), or societies of independent autonomous robots or agents, are rapidly becoming an important part of much of the world's critical infrastructure. As with human societies, regulation, wherein a governing body designs rules and processes for the society, plays an important role in ensuring that HARE meet societal objectives. However, to date, a careful study of interactions between a regulator and HARE is lacking. In this paper, we report on three user studies which give insights into how to design systems that allow people, acting as the regulatory authority, to effectively interact with HARE. As in the study of political systems in which governments regulate human societies, our studies analyze how interactions between HARE and regulators are impacted by regulatory power and individual (robot or agent) autonomy. Our results show that regulator power, decision support, and adaptive autonomy can each diminish the social welfare of HARE, and hint at how these seemingly desirable mechanisms can be designed so that they become part of successful HARE.