Human Capabilities as Guiding Lights for the Field of AI-HRI: Insights from Engineering Education

TL;DR

This paper examines how AI-HRI research aligns with social justice principles, analyzing recent papers and proposing that adopting the Engineering for Social Justice framework could foster more equitable technological development.

Contribution

It introduces the application of the E4SJ framework to AI-HRI, highlighting current misalignments and proposing guidance for future research to better serve human needs.

Findings

Current AI-HRI research is not well aligned with social justice principles.

Applying E4SJ can guide AI-HRI towards more equitable outcomes.

Future work guided by E4SJ could improve societal impact.

Abstract

Social Justice oriented Engineering Education frameworks have been developed to help guide engineering students' decisions about which projects will genuinely address human needs to create a better and more equitable society. In this paper, we explore the role such theories might play in the field of AI-HRI, consider the extent to which our community is (or is not) aligned with these recommendations, and envision a future in which our research community takes guidance from these theories. In particular, we analyze recent AI-HRI (through analysis of 2020 AI-HRI papers) and consider possible futures of AI-HRI (through a speculative ethics exercise). Both activities are guided through the lens of the Engineering for Social Justice (E4SJ) framework, which centers contextual listening and enhancement of human capabilities. Our analysis suggests that current AI-HRI research is not well aligned with the guiding principles of Engineering for Social Justice, and as such, does not obviously meet the needs of the communities we could be helping most. As such, we suggest that motivating future work through the E4SJ framework could help to ensure that we as researchers are developing technologies that will actually lead to a more equitable world.