全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Systematic Reviews: Exploring Consumer Acceptance of AI

DOI: 10.4236/ojbm.2025.132042, PP. 809-812

Keywords: Artificial Intelligence (AI), Algorithm Aversion, Consumer Trust, AI Decision-Making, Personalization in AI, AI Bias, Explainable AI (XAI), Human-AI Interaction, AI in Healthcare, AI Recommendations, Consumer Resistance to AI, Anthropomorphism In AI, Affective Computing, AI Acceptance Strategies, Transparent AI Systems, Fairness in AI, AI and Emotional Decision-Making, AI in Everyday Life, AI Perception, Trust-Building in AI

Full-Text   Cite this paper   Add to My Lib

Abstract:

This paper explores the factors influencing consumer acceptance and resistance to artificial intelligence (AI) technologies. It examines AI’s role in decision-making across industries such as personalized recommendations, healthcare, and finance, while highlighting the mixed consumer responses influenced by optimism, pessimism, and misconceptions. Notably, “algorithm aversion” emerges as a significant barrier, where consumers prefer human judgment despite AI’s superior accuracy due to concerns about personal nuances and error-learning limitations. This review outlines strategies to enhance AI acceptance, including consumer education, personalized outputs, and anthropomorphism, while acknowledging associated risks. The paper concludes by emphasizing the importance of aligning AI design with consumer relationship norms and ethical considerations to foster trust and adoption.

References

[1]  Bonezzi, A., & Ostinelli, M. (2021). Can Algorithms Legitimize Discrimination? Journal of Experimental Psychology: Applied, 27, 447-459.
https://doi.org/10.1037/xap0000294
[2]  Castelo, N., Bos, M. W., & Lehmann, D. R. (2019). Task-Dependent Algorithm Aversion. Journal of Marketing Research, 56, 809-825.
https://doi.org/10.1177/0022243719851788
[3]  Cave, S., Coughlan, K., & Dihal, K. (2019). Scary Robots. In Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society (pp. 331-337). ACM.
https://doi.org/10.1145/3306618.3314232
[4]  Khaleel, M., & Jebrel, A. (2024). Artificial Intelligence in Computer Science. International Journal of Electrical Engineering and Sustainability, 2, 1-21.
https://doi.org/10.5281/Zenodo.10937515.
[5]  Longoni, C., Bonezzi, A., & Morewedge, C. K. (2019). Resistance to Medical Artificial Intelligence. Journal of Consumer Research, 46, 629-650.
https://doi.org/10.1093/jcr/ucz013
[6]  Puntoni, S., Reczek, R. W., Giesler, M., & Botti, S. (2021). Consumers and Artificial Intelligence: An Experiential Perspective. Journal of Marketing, 85, 131-151.
https://doi.org/10.1177/0022242920953847
[7]  von Walter, B., Wentzel, D., & Raff, S. (2023). Should Service Firms Introduce Algorithmic Advice to Their Existing Customers? The Moderating Effect of Service Relationships. Journal of Retailing, 99, 280-296.
https://doi.org/10.1016/j.jretai.2023.05.001

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133