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Gender Neutrality in Robots: An Open Living Review Framework | IEEE Conference Publication | IEEE Xplore

Gender Neutrality in Robots: An Open Living Review Framework


Abstract:

Gender is a primary characteristic by which people organize themselves. Previous research has shown that people tend to unknowingly ascribe gender to robots based on feat...Show More

Abstract:

Gender is a primary characteristic by which people organize themselves. Previous research has shown that people tend to unknowingly ascribe gender to robots based on features of their embodiment. Yet, robots are not necessarily ascribed the same, or any, gender by different people. Indeed, robots may be ascribed non-human genders or used as “genderless” alternatives. This underlies the notion of gender neutrality in robots: neither masculine nor feminine but somewhere in between or even beyond gender. Responding to calls for gender as a locus of study within robotics, we offer a framework for conducting an open living review to be updated periodically as work emerges. Significantly, we provide an open, formalized submission process and open access dataset of research on gender neutrality in robots. This novel and timely approach to consensus-building is expected to pave the way for similar endeavours on other key topics within human-robot interaction research.
Date of Conference: 07-10 March 2022
Date Added to IEEE Xplore: 29 September 2022
ISBN Information:
Conference Location: Sapporo, Japan

I. Introduction

Gender is an important feature of people-and increasingly of robots, too. Decades of work has shown that people can and do read human characteristics in the design of robots and other agents, even when anthropomorphic cues are subtle. Nass, Brave, Moon, Lee, and colleagues [1], [2] were forerunners in researching this phenomenon. Their work on computer voice led to the Computers Are Social Actors (CASA) model, a widely recognized descriptive paradigm that shows how people tend to react to computer agents that have humanlike characteristics as if they are people, usually unthinkingly and in stereotyped ways. The implications of this early research were vast, spurning studies on gender in robots and other artificial agents [3]–[6].

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