Artificial Intelligence and Persuasion: A Construal-Level Account

Kim, TW; Duhachek, A

Artificial Intelligence and Persuasion: A Construal-Level Account

Kim, TW Duhachek, A

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Publisher:: SAGE Publications
Publication Type:: Journal Article
Citation:: Psychological Science, 2020, 31, (4), pp. 363-380
Issue Date:: 2020-03-30

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Field	Value	Language
dc.contributor.author	Kim, TW
dc.contributor.author	Duhachek, A
dc.date.accessioned	2020-09-30T21:51:52Z
dc.date.available	2019-11-16
dc.date.available	2020-09-30T21:51:52Z
dc.date.issued	2020-03-30
dc.identifier.citation	Psychological Science, 2020, 31, (4), pp. 363-380
dc.identifier.issn	0956-7976
dc.identifier.issn	1467-9280
dc.identifier.uri	http://hdl.handle.net/10453/142949
dc.description.abstract	<jats:p> Although more individuals are relying on information provided by nonhuman agents, such as artificial intelligence and robots, little research has examined how persuasion attempts made by nonhuman agents might differ from persuasion attempts made by human agents. Drawing on construal-level theory, we posited that individuals would perceive artificial agents at a low level of construal because of the agents’ lack of autonomous goals and intentions, which directs individuals’ focus toward how these agents implement actions to serve humans rather than why they do so. Across multiple studies (total N = 1,668), we showed that these construal-based differences affect compliance with persuasive messages made by artificial agents. These messages are more appropriate and effective when the message represents low-level as opposed to high-level construal features. These effects were moderated by the extent to which an artificial agent could independently learn from its environment, given that learning defies people’s lay theories about artificial agents. </jats:p>
dc.format	Print-Electronic
dc.language	en
dc.publisher	SAGE Publications
dc.relation.ispartof	Psychological Science
dc.relation.isbasedon	10.1177/0956797620904985
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	1701 Psychology, 1702 Cognitive Sciences
dc.subject.classification	Experimental Psychology
dc.title	Artificial Intelligence and Persuasion: A Construal-Level Account
dc.type	Journal Article
utslib.citation.volume	31
utslib.location.activity	United States
utslib.for	1701 Psychology
utslib.for	1702 Cognitive Sciences
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Marketing Discipline
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
pubs.consider-herdc	true
dc.date.updated	2020-09-30T21:51:43Z
pubs.issue	4
pubs.publication-status	Published
pubs.volume	31
utslib.citation.issue	4

Abstract:

Although more individuals are relying on information provided by nonhuman agents, such as artificial intelligence and robots, little research has examined how persuasion attempts made by nonhuman agents might differ from persuasion attempts made by human agents. Drawing on construal-level theory, we posited that individuals would perceive artificial agents at a low level of construal because of the agents’ lack of autonomous goals and intentions, which directs individuals’ focus toward how these agents implement actions to serve humans rather than why they do so. Across multiple studies (total N = 1,668), we showed that these construal-based differences affect compliance with persuasive messages made by artificial agents. These messages are more appropriate and effective when the message represents low-level as opposed to high-level construal features. These effects were moderated by the extent to which an artificial agent could independently learn from its environment, given that learning defies people’s lay theories about artificial agents.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/142949