AnZoMa
Anthropomorphism and Affective Perception: Dimensions, Measurements, and Interdependencies in Aerial Robotics
Journal
IEEE Transactions on Affective Computing
Authors
Viviane Herdel 1
Anastasia Kuzminykh 2
Yisrael Parmet 1
Jessica R. Cauchard 1
1 Magic Lab, Department of Industrial Engineering and Management, Ben Gurion University of the Negev
Be'er Sheva, Israel
2 Faculty of Information, University of Toronto, Canada
Abstract
Assigning lifelike qualities to robotic agents (Anthropomorphism) is associated with complex affective interpretations of their behavior. These anthropomorphized perceptions are traditionally elicited through robots' designs. Yet, aerial robots (or drones) present a special case due to their -- traditionally -- non-anthropomorphic design, and prior research shows conflicting evidence on their perception as either person-like, animal-like, or machine-like. In this work, we explore how people perceive drones in a cross-dimensional space between these three dimensions by varying the affective state presented on the drone. To capture these perceptions, we developed a novel measurement instrument AnZoMa. We describe the design, use, and deployment of the instrument in an online study (N=98). The study results suggest that different drone emotions triggered people to attribute various characteristics to the drone (e.g., interaction metaphors, traits, and features) and variations in acceptability of drone affective states. These results demonstrate the interdependencies between affective perceptions and anthropomorphism of drones. We conclude by discussing the necessity to integrate cross-dimensional perception of anthropomorphism in human-drone interaction and affective computing. This work contributes a novel tool to measure the dimensions and gravity of anthropomorphism and insights into interdependencies between different affective states displayed on drones and their anthropomorphized perception.
Methodology
We conducted a study to explore whether and how the display of different emotions through facial features affects (i) the perceived life-likeness of drones in a cross-dimensional space between: person-, animal-, and machine-likeness and (ii) the perception of drone characteristics. We employed a mixed-methods approach using the AnZoMa tool (developed to measure the perceived life-likeness).
Key Results
Through a presented novel AnZoMa tool, we explored these perceptions in a cross-dimensional space between the three dimensions: person-likeness (anthropomorphization), animal-likeness (zoomorphization), and machine-likeness.
Our results show that the presented drone is predominantly anthropomorphized rather than zoomorphized. While these dimensional perceptions are rather stable across emotions, the life-like traits and intentions attributed to the drone are emotion-dependent.
For additional findings, we invite you to read the full paper.
Contribution in a nutshell:
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A new method to capture the dimensions and gravity of life-likeness (AnZoMa tool)
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Insights into how the display of different emotions affects the perception of (i) drones in a cross-dimensional space between the three dimensions: person-, animal-, and machine-likeness; and (ii) drone characteristics