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Abracadabra : = Gen Z Uses of Artificial Intelligence Voice Recognition Technology Systems : A Survey of Undergraduate University Students' Motives.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Abracadabra :/
其他題名:
Gen Z Uses of Artificial Intelligence Voice Recognition Technology Systems : A Survey of Undergraduate University Students' Motives.
作者:
Alhashimi, Nadia.
面頁冊數:
1 online resource (61 pages)
附註:
Source: Masters Abstracts International, Volume: 83-01.
Contained By:
Masters Abstracts International83-01.
標題:
Communication. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27832773click for full text (PQDT)
ISBN:
9798522901974
Abracadabra : = Gen Z Uses of Artificial Intelligence Voice Recognition Technology Systems : A Survey of Undergraduate University Students' Motives.
Alhashimi, Nadia.
Abracadabra :
Gen Z Uses of Artificial Intelligence Voice Recognition Technology Systems : A Survey of Undergraduate University Students' Motives. - 1 online resource (61 pages)
Source: Masters Abstracts International, Volume: 83-01.
Thesis (M.S.)--University of Louisiana at Lafayette, 2020.
Includes bibliographical references
This thesis is a quantitative study examining the use of artificial intelligence systems of voice recognition technology amongst Gen Zers (ages 18 to 25; born between 1995 and 2002). A structured survey was conducted on 763 undergraduate students to understand their uses and motivations for use of voice recognition technology. With a basis in Uses and Gratifications Theory, this study found that hedonic benefits (entertainment and social) were significant (and equal) motivators for this sample set of Gen Zers as utilitarian motivators. Indications from this study are that the adoption of voice recognition technology among this generation is becoming more ubiquitous. This study hopes to contribute to a better understanding of motivations behind the use and adoption of AI systems in the next consumer market and contributes to the growing literature that supports these findings of the growing significance of hedonic benefits. This research contributes not only to research and development of artificially intelligent media and understanding motives of the next generation of consumers, but also informs future policy research to maximize the benefits of AI while minimizing potential risks. This research contributes to the growing social science contributions to this emergent field of machine-human interactions and hopes to inform the field's research, development, and policy.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023
Mode of access: World Wide Web
ISBN: 9798522901974Subjects--Topical Terms:
524709
Communication.
Subjects--Index Terms:
Artificial IntelligenceIndex Terms--Genre/Form:
542853
Electronic books.
Abracadabra : = Gen Z Uses of Artificial Intelligence Voice Recognition Technology Systems : A Survey of Undergraduate University Students' Motives.
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This thesis is a quantitative study examining the use of artificial intelligence systems of voice recognition technology amongst Gen Zers (ages 18 to 25; born between 1995 and 2002). A structured survey was conducted on 763 undergraduate students to understand their uses and motivations for use of voice recognition technology. With a basis in Uses and Gratifications Theory, this study found that hedonic benefits (entertainment and social) were significant (and equal) motivators for this sample set of Gen Zers as utilitarian motivators. Indications from this study are that the adoption of voice recognition technology among this generation is becoming more ubiquitous. This study hopes to contribute to a better understanding of motivations behind the use and adoption of AI systems in the next consumer market and contributes to the growing literature that supports these findings of the growing significance of hedonic benefits. This research contributes not only to research and development of artificially intelligent media and understanding motives of the next generation of consumers, but also informs future policy research to maximize the benefits of AI while minimizing potential risks. This research contributes to the growing social science contributions to this emergent field of machine-human interactions and hopes to inform the field's research, development, and policy.
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