Gendered Actions with a Genderless Robot: Gender Attribution to Humanoid Robots in Action

Aşkın, Gaye; Saltık, İmge; Boz, Tuğçe Elver; Ürgen, Burcu A.

doi:10.1007/s12369-022-00964-0

Cited by 5 publications

(1 citation statement)

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“…The second is anthropomorphism, which is measured through an openended question that asks participants to express their views on the agents. 3 The third question focuses on competency level (aka functional appropriateness-FA), with participants asked to evaluate the adequacy of an action's execution 4 on a scale of 1 to 5, ranging from very bad to very good. Lastly, the gender attribution question (GA) seeks participant opinions on the gender evaluation 5 of agents with their corresponding names, and the rating is between [-3: masculine,0: neutral +3: feminine]…”

Section: Designmentioning

confidence: 99%

Autonomy and Robotonomy: The Role of Gender

Askin,

Urgen

2024

Preprint

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This study investigates how an agent's name (masculine, feminine, neutral, technical, no-name) and type (human, robot) can impact evaluations of autonomy, which is characterized both by explicit and implicit measurements. Explicit measurements include questions regarding agency, anthropomorphism, competency, and (gender) identity attribution. Implicit measurements are assessed using the implicit association task. Participants viewed 18 videos and responded to autonomy-related questions for the explicit part. They also completed three implicit association tasks for the implicit part regarding the variable’s agent type, independence, and gender. Correlation analyses were also conducted to evaluate the relationship between explicit and implicit responses. Finally, a thematic analysis was conducted to analyze qualitative inputs in the explicit part, which were then categorized into nine themes. Our explicit results indicate that agent type has a main effect on agency-level attribution. However, regarding competency and gender attribution, agents did not differ from each other. On the other hand, the effect of the agent’s name remained marginal, suggesting that effective manipulation of names may influence our perceptions of agents' autonomy. In the implicit part, man participants showed strong bias to men/independent and women/dependent associations whereas woman participants showed a reverse pattern (IAT-1). Both groups of participants showed a strong bias to robot/dependent and human/independent associations (IAT-2). Lastly, woman participants showed strong biases to men/robot and women/human associations whereas men showed a reverse pattern (IAT-3). However, participants' explicit and implicit perceptions differed, indicating biases at implicit levels.

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Section: Designmentioning

confidence: 99%