Oral Session 1-KZ – Robots & Artificial Agents 1
Chair: Jonathan Gratch
Empathizing with Robots: Fellow Feeling along the Anthropomorphic Spectrum
Laurel D. Riek, Tal-Chen Rabinowitch, Bhismadev Chakrabarti, Peter Robinson
Abstract: A long-standing question within the robotics community is about the degree of human-likeness robots ought to have when interacting with humans. We explore an unexamined aspect of this problem: how people empathize with robots along the anthropomorphic spectrum. We conducted a web-based experiment (n = 120) that measured how people empathized with four different robots shown to be experiencing mistreatment by humans. Our results indicate that people empathize more strongly with more human-looking robots and less with mechanical looking robots. We also found that a person’s general ability to empathize has no predictive value for expressed empathy toward robots.
How about laughter? Perceived naturalness of two laughing humanoid robots
Christian Werner Becker-Asano, Takayuki Kanda, Carlos Ishi, Hiroshi Ishiguro
Abstract: As humanoid robots will have to behave socially adequate
in a future society, we started to investigate laughter
as an important para-verbal signal influencing relationships
among humans quite easily. As a first step we investigate,
how humanoid robots might laugh within a situation,
which is suitable for laughter. Given the variety of human
laughter, do people prefer a certain style for a robot’s
laughter? And if yes, how does a robot’s outer appearance
affect this preference, if at all?
Accordingly, we combined six recordings of female
laughter with body movements for two different humanoid
robots with the aim to evaluate their perceived naturalness
using two types of video-based surveys. We not only found
that people indeed prefer one type of laughter when being
forced to choose, but the results also suggest significant differences
in the perceived naturalness of laughter with regard
to the participant’s cultural background. The outer
appearance seems to change the perceived naturalness of a
humanoid robot’s laughter only on a global level.
It is evident, however, that further research on this rather
unexplored topic is needed as much as it promises to provide
valuable means to support the development of social robots.
"Don't think too much!" - Artificial Somatic Markers for Action Selection
César F. Pimentel, Maria R. Cravo
Abstract: Humans could not effectively perform everyday decisions if they could only count on purely rational evaluations of the available response options. According to the Somatic Marker hypothesis, before such evaluations take place, emotional signals drastically reduce the space of available options and provide essential biases for decision making.
Within the context of action selection, we present a model of the somatic markers' mechanism, encompassing three related processes of an AI agent: 1) Creating markers from the agent's experiences; 2) Combining markers and producing generalizations; 3) Using existing markers to aid in action selection.
Computer simulations in two different domains respectively show: a) a resulting behavior that is similar to that obtained from an experiment with human subjects, and b) an intuitive creation and effect of generalized markers.