Featured Topic: Artificial intelligence

With the release of our policy on usage of generative artificial intelligence (AI) in scholarly papers, along with an editorial on the subject, it seemed timely to explore which aspects of this polarizing technology have caught the research interest of SBP authors.

The first paper we published on this topic was focused on the design of personalized AI agents (Kim & Yoo, 2021). With a large sample of over 800 participants from five countries, the authors examined user preference for two-dimensional versus three-dimensional designs and male versus female external appearance, and found varying patterns in preference by country and gender. Guan and Chen (2023) likewise found that acceptance of chatbots, compared to human agents, differed among their respondents. Specifically, the negative effect of AI (vs. human) service on customer citizenship behavior became weaker in the context of competent (vs. warm) brand service. Jang (2023) further found that factors such as higher levels of AI anthropomorphism and a growth creative mindset were associated with stronger acceptance of art generated by AI.

Various industries now incorporate AI in daily tasks, including in healthcare settings as an assistive diagnostic tool. Liu et al. (2024) tested the efficacy of a machine learning algorithm in identifying varying brain characteristics produced by structural magnetic resonance imaging. They found that personality styles, but not personality traits, could be discriminated using the algorithm, and extrapolated this to the potential of machine learning to be incorporated into early individual psychological risk assessments. For accurate measurement of the effect of AI on human creativity and practices, Tao et al. (2024) developed a scale to assess cognitive outsourcing behavior, using both qualitative and quantitative data to inform their scale building.

Development of a technology is one thing, but whether it will be embraced and used on an ongoing basis is another issue. Shen et al. (2024) examined the use of AI sports coaching services, reporting that emphasizing benefits and minimizing costs was crucial for enhancing users’ engagement and perceived value of these services. Xu and Xue (2024) explored whether employees hid their role knowledge when they perceived their employment was threatened by the introduction of AI tools. They concluded that their findings may help companies in promoting active knowledge sharing among employees when organizational processes are disrupted/transformed by the introduction of AI.

Keen to find out more about the pros and cons of machine learning from a behavioral and social psychology perspective? Our journal archive contains dozens of published and upcoming articles on this and other, related subjects over our five decades of publication. Sign up for a personal subscription to SBP to gain access to several thousand papers spanning the fields of social, behavioral, and developmental psychology.

Cross-cultural comparison of preferences for the external appearance of artificial intelligence agents – Youngsang Kim and Hoonsik Yoo, 2021, 49(11), Article e10824.

Artificial intelligence service reduces customer citizenship behavior for warm brands versus competent brands – Biyu Guan and Haiquan Chen, 2023, 51(11), Article e12727.

Anthropomorphism, perceived learning for creation, and growth creative mindset as predictors of acceptance toward artificial intelligence creativity – YeiBeech Jang, 2023, 51(8), Article e12536.

Predicting individual personality styles using macrostructural information: A multivariate pattern study – Huijuan Liu, Xinshuo Song, and Yinghui Guo, 2024, 52(10), Article e13191.

Mastering delegation to artificial intelligence creative tools: The concept, dimensions, and development of a scale to measure cognitive outsourcing – Wei Tao, Mengqiu Zhang, and Yichuan Liu, 2024, 52(12), Article e13907.

Continued use of artificial intelligence coaching services: Application of the value-based acceptance model – YaWen Shen, Hye Ji Sa, and Jee-Hoon Han, 2024, 52(9), Article e13493.

Unemployment risk perception and knowledge hiding under the disruption of artificial intelligence transformation – Guanglu Xu and Ming Xue, 2023, 51(2), Article e12106.