Operationalizing Perceptions of Agent Gender: Foundations and Guidelines
This work tackles the problem of inconsistent and limited methods for studying agent gender perceptions, which hinders comparability and inclusivity in research, making it incremental by providing guidelines rather than a new paradigm.
The paper addresses the lack of standards in measuring perceptions of agent gender in human-computer interaction, finding that one-third of studies manipulate but do not measure it, and contributes a framework for more rigorous and inclusive operationalization.
The "gender" of intelligent agents, virtual characters, social robots, and other agentic machines has emerged as a fundamental topic in studies of people's interactions with computers. Perceptions of agent gender can help explain user attitudes and behaviours -- from preferences to toxicity to stereotyping -- across a variety of systems and contexts of use. Yet, standards in capturing perceptions of agent gender do not exist. A scoping review was conducted to clarify how agent gender has been operationalized -- labelled, defined, and measured -- as a perceptual variable. One-third of studies manipulated but did not measure agent gender. Norms in operationalizations remain obscure, limiting comprehension of results, congruity in measurement, and comparability for meta-analyses. The dominance of the gender binary model and latent anthropocentrism have placed arbitrary limits on knowledge generation and reified the status quo. We contribute a systematically-developed and theory-driven meta-level framework that offers operational clarity and practical guidance for greater rigour and inclusivity.