Gender is a social framework through which people organize themselves-and non-human subjects, including robots. Research stretching back decades has found evidence that people tend to gender artificial agents unwittingly, even with the slightest cue of humanlike features in voice, body, role, and other social features. This has led to the notion of gender neutrality in robots: ways in which we can avoid gendering robots in line with human models, as well explorations of extra-human genders. This rapid review critically surveyed the literature to capture the state of art on gender neutrality in robots that interact with people. We present findings on theory, methods, results, and reflexivity. We interrogate the very idea that robot gender/ing can be neutral and explore alternate ways of approaching gender/ing through the design and study of robots interacting with people.
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