DocumentCode :
565800
Title :
Distinguishing defaults and second-line conceptualization in reasoning about humans, robots, and computers
Author :
Levin, Daniel T. ; Saylor, Megan M.
Author_Institution :
Dept. Psychol. & Human Dev., Vanderbilt Univ., Nashville, TN, USA
fYear :
2009
fDate :
11-13 March 2009
Firstpage :
251
Lastpage :
252
Abstract :
In previous research, we demonstrated that people distinguish between human and nonhuman intelligence by assuming that humans are more likely to engage in intentional goal-directed behaviors than computers or robots. In the present study, we tested whether participants who respond relatively quickly when making predictions about an entity are more or less likely to distinguish between human and nonhuman agents on the dimension of intentionality. Participants responded to a series of five scenarios in which they chose between intentional and nonintentional actions for a human, a computer, and a robot. Results indicated that participants who chose quickly were more likely to distinguish human and nonhuman agents than participants who deliberated more over their responses. We suggest that the short-RT participants were employing a first-line default to distinguish between human intentionality and more mechanical nonhuman behavior, and that the slower, more deliberative participants engaged in deeper second-line reasoning that led them to change their predictions for the behavior of a human agent.
Keywords :
human computer interaction; human-robot interaction; inference mechanisms; computers; first-line default; human agent behavior; human intentionality; humans; intentional goal-directed behavior; mechanical nonhuman behavior; nonhuman agents; nonhuman intelligence; nonintentional actions; robots; second-line conceptualization; second-line reasoning; Cognition; Computers; Conferences; Educational institutions; Humans; Plugs; Robots; Concepts; HRI; Theory of Mind;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Human-Robot Interaction (HRI), 2009 4th ACM/IEEE International Conference on
Conference_Location :
La Jolla, CA
ISSN :
2167-2121
Print_ISBN :
978-1-60558-404-1
Type :
conf
Filename :
6256049
Link To Document :
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