Adaptive AI as Collaborator: Examining the Impact of an AI's Adaptability and Social Role on Individual Professional Efficacy and Credit Attribution in Human–AI Collaboration.
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| Title: | Adaptive AI as Collaborator: Examining the Impact of an AI's Adaptability and Social Role on Individual Professional Efficacy and Credit Attribution in Human–AI Collaboration. |
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| Authors: | Du, Tianshu (AUTHOR), Li, Xiaoqian (AUTHOR), Jiang, Naifei (AUTHOR), Xu, Yichen (AUTHOR), Zhou, Yushu (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Oct2025, Vol. 41 Issue 19, p12422-12433. 12p. |
| Subjects: | Artificial intelligence, Social role, Adaptive control systems, Attribution (Social psychology), Interpersonal relations, Occupational achievement, Participation |
| Abstract: | Human–AI collaboration has become increasingly prevalent, integrating sophisticated AI systems into various professional and personal domains. To explore how AI with trainability, dynamic participation, and real-time feedback positively, companies by different social role labels, promotes human–AI collaboration relationships, a 2 (static/adaptable AI) *2 (expert/peer) experiment was conducted in a laboratory with 96 university students. The study found that collaboration with adaptable AI teammates can greatly enhance human professional efficacy, promote individuals to attribute credit to themselves, and promote the establishment of directive and guided human–robot collaboration relationships. When collaborating with an AI expert, the individual gives more credit to the expert; individuals take credit for themselves. When collaborating with an AI peer. This study supplements the evaluation dimension of human-computer collaboration from personal long-term well-being and teamwork relationships. It provides important theoretical and practical design significance for promoting positive, healthy, and sustainable human–AI collaborative development. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Header | DbId: pbh DbLabel: Psychology and Behavioral Sciences Collection An: 188157088 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Adaptive AI as Collaborator: Examining the Impact of an AI's Adaptability and Social Role on Individual Professional Efficacy and Credit Attribution in Human–AI Collaboration. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Du%2C+Tianshu%22">Du, Tianshu</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Xiaoqian%22">Li, Xiaoqian</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Naifei%22">Jiang, Naifei</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Yichen%22">Xu, Yichen</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhou%2C+Yushu%22">Zhou, Yushu</searchLink> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Oct2025, Vol. 41 Issue 19, p12422-12433. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Social+role%22">Social role</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+control+systems%22">Adaptive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Attribution+%28Social+psychology%29%22">Attribution (Social psychology)</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+relations%22">Interpersonal relations</searchLink><br /><searchLink fieldCode="DE" term="%22Occupational+achievement%22">Occupational achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Participation%22">Participation</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Human–AI collaboration has become increasingly prevalent, integrating sophisticated AI systems into various professional and personal domains. To explore how AI with trainability, dynamic participation, and real-time feedback positively, companies by different social role labels, promotes human–AI collaboration relationships, a 2 (static/adaptable AI) *2 (expert/peer) experiment was conducted in a laboratory with 96 university students. The study found that collaboration with adaptable AI teammates can greatly enhance human professional efficacy, promote individuals to attribute credit to themselves, and promote the establishment of directive and guided human–robot collaboration relationships. When collaborating with an AI expert, the individual gives more credit to the expert; individuals take credit for themselves. When collaborating with an AI peer. This study supplements the evaluation dimension of human-computer collaboration from personal long-term well-being and teamwork relationships. It provides important theoretical and practical design significance for promoting positive, healthy, and sustainable human–AI collaborative development. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=188157088 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/10447318.2025.2462120 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 12422 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Social role Type: general – SubjectFull: Adaptive control systems Type: general – SubjectFull: Attribution (Social psychology) Type: general – SubjectFull: Interpersonal relations Type: general – SubjectFull: Occupational achievement Type: general – SubjectFull: Participation Type: general Titles: – TitleFull: Adaptive AI as Collaborator: Examining the Impact of an AI's Adaptability and Social Role on Individual Professional Efficacy and Credit Attribution in Human–AI Collaboration. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Du, Tianshu – PersonEntity: Name: NameFull: Li, Xiaoqian – PersonEntity: Name: NameFull: Jiang, Naifei – PersonEntity: Name: NameFull: Xu, Yichen – PersonEntity: Name: NameFull: Zhou, Yushu IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10447318 Numbering: – Type: volume Value: 41 – Type: issue Value: 19 Titles: – TitleFull: International Journal of Human-Computer Interaction Type: main |
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