Operationalizing Perceptions of Agent Gender: Foundations and Guidelines

Abstract

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.

Figures (7)

• Figure 1: PRISMA flow diagram. Generated using the online tool by Haddaway2022prisma.
• Figure 2: Study goals, with study counts by topic. Note: Each study could have multiple goals, so the sum does not equal $N=51$.
• Figure 3: Agent gender options used by researchers.
• Figure 4: Agent gender options and combinations over time.
• Figure 5: Manipulation checks, including counts of no checks.