Robotic Pets in Human Lives: Implications for the Human-Animal Bond and for Human Relationships with Personified Technologies

Robotic “pets” are being marketed as social companions and are used in the emerging field of robot‐assisted activities, including robot‐assisted therapy (RAA). However, the limits to and potential of robotic analogues of living animals as social and therapeutic partners remain unclear. Do children a...

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Bibliographic Details
Published inJournal of social issues Vol. 65; no. 3; pp. 545 - 567
Main Authors Melson, Gail F., Kahn, Jr, Peter H., Beck, Alan, Friedman, Batya
Format Journal Article
LanguageEnglish
Published Malden, USA Blackwell Publishing Inc 01.09.2009
Blackwell Publishing Ltd
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Summary:Robotic “pets” are being marketed as social companions and are used in the emerging field of robot‐assisted activities, including robot‐assisted therapy (RAA). However, the limits to and potential of robotic analogues of living animals as social and therapeutic partners remain unclear. Do children and adults view robotic pets as “animal‐like,”“machine‐like,” or some combination of both? How do social behaviors differ toward a robotic versus living dog? To address these issues, we synthesized data from three studies of the robotic dog AIBO: (1) a content analysis of 6,438 Internet postings by 182 adult AIBO owners; (2) observations and interviews with 80 preschoolers during play periods with AIBO and with a stuffed dog; and (3) observations and interviews with 72 children, aged 7–15 years, who played with AIBO and a living dog. Overall, the studies revealed that “hybrid” cognitions and behaviors about AIBO emerged: the robotic dog was treated as a technological artifact that also embodied attributes of living animals, such as having mental states, being a social other, and having moral standing (although this latter finding remained difficult to interpret). Implications for use of robotic pets as companions and in interventions or therapy are explored.
Bibliography:ark:/67375/WNG-Q46TBMC9-5
istex:929E82CE4B74B8BEE0CC9CBBF420A110842D5E68
ArticleID:JOSI1613
We thank Brian Gill for assistance with statistical analyses. We also thank the following individuals (in alphabetical order) for assistance with data collection, transcript preparation, and coding: Jocelyne Albert, Nathan Freier, Erik Garrett, Oana Georgescu, Brian Gilbert, Jennifer Hagman, Migume Inoue, and Trace Roberts.
This material is based on work supported by the National Science Foundation under Grant No. IIS‐0102558 and IIS‐0325035. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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ISSN:0022-4537
1540-4560
DOI:10.1111/j.1540-4560.2009.01613.x