TY - GEN
T1 - Acceptance of Generative AI in the Creative Industry
T2 - 25th International Conference on Human-Computer Interaction, HCII 2023
AU - Yin, Ming
AU - Han, Bingxu
AU - Ryu, Sunghan
AU - Hua, Min
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - With the boosting entrenchment of Generative artificial intelligence (AI) across the creative markets, little is explored around the opinions of those who are within the influenced industries. How well professionals in the creative domains are viewing and embracing this newly emerged technology awaits verification. Using a survey method, this study shed light on the underpinning factors that could predict professionals’ acceptance and usage intention of Generative AI under the status quo. By integrating the expanded Unified Theory of Acceptance and Use of Technology (UTAUT2) model, the study incorporates the dimension of AI anxiety into the framework. Regression analyses reveal that acceptance and usage intention of Generative AI can be predicted by factors including performance expectancy, social influence, hedonic motivation, habit, and AI anxiety, while effort expectancy, facility conditions, and price value cannot predict users’ intention yet at current situations. The study shows the importance of the emotional attitudes of users and provides stakeholders with insights to develop Generative AI products to better fit the adaptability of users. Findings suggest that people who are actively involved in the creative and cultural economies favour using Generative AI, even when undergoing AI learning anxiety. Participants with a relatively higher level of education perform with more resilience and stability when faced with AI-related situations, as they are less possible to withdraw from future usage though undergoing the fear of Generative AI products, and they appear to less addictively rely on Generative AI tools despite all the merits.
AB - With the boosting entrenchment of Generative artificial intelligence (AI) across the creative markets, little is explored around the opinions of those who are within the influenced industries. How well professionals in the creative domains are viewing and embracing this newly emerged technology awaits verification. Using a survey method, this study shed light on the underpinning factors that could predict professionals’ acceptance and usage intention of Generative AI under the status quo. By integrating the expanded Unified Theory of Acceptance and Use of Technology (UTAUT2) model, the study incorporates the dimension of AI anxiety into the framework. Regression analyses reveal that acceptance and usage intention of Generative AI can be predicted by factors including performance expectancy, social influence, hedonic motivation, habit, and AI anxiety, while effort expectancy, facility conditions, and price value cannot predict users’ intention yet at current situations. The study shows the importance of the emotional attitudes of users and provides stakeholders with insights to develop Generative AI products to better fit the adaptability of users. Findings suggest that people who are actively involved in the creative and cultural economies favour using Generative AI, even when undergoing AI learning anxiety. Participants with a relatively higher level of education perform with more resilience and stability when faced with AI-related situations, as they are less possible to withdraw from future usage though undergoing the fear of Generative AI products, and they appear to less addictively rely on Generative AI tools despite all the merits.
KW - AI anxiety
KW - creative professionals
KW - Generative AI
KW - UTAUT
UR - http://www.scopus.com/inward/record.url?scp=85178606124&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-48057-7_18
DO - 10.1007/978-3-031-48057-7_18
M3 - Conference contribution
AN - SCOPUS:85178606124
SN - 9783031480560
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 288
EP - 310
BT - HCI International 2023 – Late Breaking Papers - 25th International Conference on Human-Computer Interaction, HCII 2023, Proceedings
A2 - Degen, Helmut
A2 - Ntoa, Stavroula
A2 - Moallem, Abbas
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 23 July 2023 through 28 July 2023
ER -