Hortensius, R. and Cross, E. S. (2018) From automata to animate beings: the scope and limits of attributing socialness to artificial agents. Annals of the New York Academy of Sciences, 1426(1), pp. 93-110. (doi: 10.1111/nyas.13727) (PMID:29749634)
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Abstract
Understanding the mechanisms and consequences of attributing socialness to artificial agents has important implications for how we can use technology to lead more productive and fulfilling lives. Here, we integrate recent findings on the factors that shape behavioral and brain mechanisms that support social interactions between humans and artificial agents. We review how visual features of an agent, as well as knowledge factors within the human observer, shape attributions across dimensions of socialness. We explore how anthropomorphism and dehumanization further influence how we perceive and interact with artificial agents. Based on these findings, we argue that the cognitive reconstruction within the human observer is likely to be far more crucial in shaping our interactions with artificial agents than previously thought, while the artificial agent's visual features are possibly of lesser importance. We combine these findings to provide an integrative theoretical account based on the “like me” hypothesis, and discuss the key role played by the Theory‐of‐Mind network, especially the temporal parietal junction, in the shift from mechanistic to social attributions. We conclude by highlighting outstanding questions on the impact of long‐term interactions with artificial agents on the behavioral and brain mechanisms of attributing socialness to these agents.
Item Type: | Articles |
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Additional Information: | Funding acknowledged from the European Research Council to E. S. C. (H2020 ERC-2015-StG-67720-SOCIAL ROBOTS). |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Hortensius, Dr Ruud and Cross, Professor Emily |
Authors: | Hortensius, R., and Cross, E. S. |
College/School: | College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience |
Journal Name: | Annals of the New York Academy of Sciences |
Publisher: | New York Academy of Sciences |
ISSN: | 0077-8923 |
ISSN (Online): | 1749-6632 |
Published Online: | 11 May 2018 |
Copyright Holders: | Copyright © 2018 New York Academy of Sciences |
First Published: | First published in Annals of the New York Academy of Sciences 1426(1): 93-110 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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