Collaborator or Creator? The role of AI in AI-Human Collaborative Creativity

Zhou Qianzhu; Zhang Jiyu; Ji Cancan; Su Jiahao; Wang Yurou; Li Yadan

doi:10.16719/j.cnki.1671-6981.20250604

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Journal of Psychological Science ›› 2025, Vol. 48 ›› Issue (6) : 1333-1345. DOI: 10.16719/j.cnki.1671-6981.20250604

Computational Modeling and Artificial Intelligence

Collaborator or Creator? The role of AI in AI-Human Collaborative Creativity

Zhou Qianzhu, Zhang Jiyu, Ji Cancan, Su Jiahao, Wang Yurou, Li Yadan

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Abstract

Creativity is an inexhaustible driving force for individual and social development. With the advent of artificial intelligence (AI), AI-human collaborative creativity has become a reality. At present, studies on AI-human collaborative creativity are scattered across various fields and lack a systematic analysis of their internal mechanisms. This gap hinders the full utilization of AI in creative activities.
AI-human collaborative creativity is defined as the process in which AI assists humans, AI and humans enhance each other, to collaborate effectively and engage in close cooperation to achieve creative outcomes. Research on AI-human collaborative creativity primarily focuses on four domains of AI: robotics, virtual AI, embedded AI, and intelligent devices in extended reality. Different AI products exhibit varying levels of creativity and collaborative creativity capabilities. These AI products play different roles in the AI-human collaborative creativity process.
To conduct an in-depth analysis of the role of AI in AI-human collaborative creativity, we propose a cognitive framework of "support-promotion-cooperation-generation ". In the domain of AI-supported human creativity, AI does not engage in creative activities and merely executes mechanical and repetitive tasks. As an auxiliary technology, AI frees people from heavy workloads to focus on creative work. In the domain of AI-enhanced human creativity, AI participates in the creative process, but its contribution is less than that of human. AI enhances individual daily creativity through bottom-up process (e.g., creative scaffolding, multisensory stimulation, and knowledge sharing) and top-down process (e.g., creative self-efficacy and self-regulated learning). In addition, AI contributes to prediction, identification, and selection in scientific creativity, while it enhances inspiration in artistic creativity. Besides, AI expands associations in divergent thinking and supports evaluation and selection in convergent thinking. In the domain of AI-human cooperative creativity, AI serves as an agent of creativity, with its contribution equal to that of human in the creative process. AI and human cooperate as independent entities to create, which can be divided into two forms: simultaneous creation (e.g., Shimon/LuminAI collaborate with individuals to create music/dance simultaneously) and alternating creation (e.g., AI and individuals take turns composing poetry). AI relies on data consistency and excels at exploratory creativity, while humans are better at transformational creativity, with the ability to shift across different dimensions. Due to their distinct characteristics, the cooperation can lead to complementary advantages in creativity. In the domain of AI-generated creativity, AI serves as an agent of creativity, contributing more than humans during the creative process. The originality performance of ChatGPT4 can surpass that of average individuals and other generative artificial intelligence (GAI) (e.g., ChatGPT3 and copy.ai). GAI is also capable of independently engaging in scientific and artistic creation. However, since AI cannot construct interpretations based on sensory experience and its writing tends to be homogenized, its performance in tasks such as Figural Interpretation Quest and creative writing is generally inferior to that of individuals.
There are some influencing factors of AI-human collaborative creativity. First, individual factors include AI perception, personal abilities, individual creativity, and individuals’ views on GAI. Second, the AI aspects include temperature parameters, out-of-distribution parameters, robot traits, and sample learning. Lastly, organizational factors include organizational preparation and cohesion.
Building on a comprehensive review of existing literature, future research can delve into the following aspects. First of all, the impact of AI-influenced emotional and cognitive factors on creativity still requires further investigation. AI may negatively impact individual creativity through cognitive interference, the emergence of STARA awareness, the creation of information cocoons, and the use of similar elements in text and artistic creation. Therefore, it is crucial to examine the potential negative impact of AI on creativity. Furthermore, future research should focus on exploring the behavioral and cognitive neural mechanisms through which AI promotes human creativity. Additionally, it's essential to focus on the ethical principles of AI-human collaborative creativity.

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artificial intelligence / AI-human collaborative creativity / creativity / recognition framework

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Zhou Qianzhu, Zhang Jiyu, Ji Cancan, Su Jiahao, Wang Yurou, Li Yadan. Collaborator or Creator? The role of AI in AI-Human Collaborative Creativity[J]. Journal of Psychological Science. 2025, 48(6): 1333-1345 https://doi.org/10.16719/j.cnki.1671-6981.20250604

References

[1] 胡卫平. (2001). 论科学创造力的结构. 教育科学研究, 4, 5-8.
[2] 胡卫平, 张阳, 吕元婧, 徐晶晶. (2024). 人工智能创造力探究. 现代教育技术, 34(1), 17-25.
[3] 李育辉, 庞菊爱, 谭北平. (2023). 人工智能与人类的创造力比较研究:基于专家和消费者的双重视角. 商业经济与管理, 10, 23-25.
[4] 王春丽, 陈艳艳, 顾小清, & 邢海风. (2024). 协作学习中生成式人工智能促进创造性潜能的机理研究. 电化教育研究, 45(11), 76-83.
[5] 王思遥, 黄亚婷. (2024). 促进或抑制:生成式人工智能对大学生创造力的影响. 中国高教研究, 11, 29-36.
[6] 王涛, 占小军, 余薇. (2024). AI感知对员工心理和行为的影响及理论解释. 心理科学进展, 32(7), 1195-1208.
[7] 尹萌, 牛雄鹰. (2024). 与 AI“共舞”:系统化视角下的 AI-员工协作. 心理科学进展, 32(1), 162-167.
[8] Ali S., Devasia N., Park H. W., & Breazeal C. (2021). Social robots as creativity eliciting agents. Frontiers in Robotics and AI, 8, 673730.
[9] Allen, A. P., & Thomas, K. E. (2011). A dual process account of creative thinking. Creativity Research Journal, 23(2), 109-118.
[10] Amabile, T. M. (2020). Creativity, artificial intelligence, and a world of surprises. Academy of Management Discoveries, 6(3), 351-354.
[11] Andonova V., Reinoso-Carvalho F., Ramirez M. A. J., & Carrasquilla D. (2023). Does multisensory stimulation with virtual reality (VR) and smell improve learning? An educational experience in recall and creativity. Frontiers in Psychology, 14, 1176697.
[12] Atkinson, D. P., & Barker, D. R. (2023). AI and the social construction of creativity. Convergence, 29(4), 1054-1069.
[13] Azevedo R., Moos D. C., Johnson A. M., & Chauncey A. D. (2010). Measuring cognitive and metacognitive regulatory processes during hypermedia learning: Issues and challenges. Educational Psychologist, 45(4), 210-223.
[14] Bellaiche L., Shahi R., Turpin M. H., Ragnhildstveit A., Sprockett S., Barr N., Christensen A., & Seli P. (2023). Humans versus AI: Whether and why we prefer human-created compared to AI-created artwork. Cognitive Research: Principles and Implications, 8(1), 42.
[15] Berente N., Gu B., Recker J., & Santhanam R. (2021). Managing artificial intelligence. MIS Quarterly, 45(3), 1135-1178.
[16] Boiko D. A., MacKnight R., Kline B., & Gomes G. (2023). Autonomous chemical research with large language models. Nature, 624(7992), 570-578.
[17] Boldt, G. (2019). Artistic creativity beyond divergent thinking: Analysing sequences in creative subprocesses. Thinking Skills and Creativity, 34, 100606.
[18] Buyukgoz S., Pandey A. K., Chamoux M., & Chetouani M. (2021). Exploring behavioral creativity of a proactive robot. Frontiers in Robotics and AI, 8, 694177.
[19] Carlson K., Schiphorst T., & Pasquier P. (2011). Scuddle: Generating movement catalysts for computer-aided choreography. In D. Ventura, P. Gervas, D. F. Harrell, M. L. Maher, A. Pease, & G. Wiggins (Eds.), Proceedings of the second international conference on computational creativity (pp. 123-128). Universidad Autónoma Metropolitana.
[20] Carrasquilla, J., & Melko, R. G. (2017). Machine learning phases of matter. Nature Physics, 13(5), 431-434.
[21] Cropley, A. (2006). In praise of convergent thinking. Creativity Research Journal, 18(3), 391-404.
[22] Davis N., Hsiao C. P., Popova Y., & Magerko B. (2015). An enactive model of creativity for computational collaboration and co-creation. In N. Zagalo & P. Branco (Eds.)., Creativity in the digital age (pp.109-133). Springer.
[23] Diedrich J., Benedek M., Jauk E., & Neubauer A. C. (2015). Are creative ideas novel and useful? Psychology of Aesthetics Creativity and the Arts, 9(1), 35-40.
[24] Doshi, A. R., & Hauser, O. P. (2024). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290.
[25] Elgarf M., Salam H., & Peters C. (2024). Fostering children' s creativity through LLM-driven storytelling with a social robot. Frontiers in Robotics and AI, 11, 1457429.
[26] Eshraghian, J. K. (2020). Human ownership of artificial creativity. Nature Machine Intelligence, 2(3), 157-160.
[27] Fleming, P., & Sturdy, A. (2011). 'Being yourself' in the electronic sweatshop: New forms of normative control. Human Relations, 64(2), 177-200.
[28] Flick, C., & Worrall, K. (2022). The ethics of creative AI. In C. Vear & F. Poltronieri (Eds.), The language of creative AI: Practices, aesthetics and structures (pp. 73-91). Springer.
[29] Fucinato K., Niebuhr O., Nørskov S., & Fischer K. (2023). Charismatic speech features in robot instructions enhance team creativity. Frontiers in Communication, 8, 1115360.
[30] Garcia, M. B. (2024). The Paradox of Artificial Creativity: Challenges and Opportunities of Generative AI Artistry. Creativity Research Journal, 36, 1-14.
[31] Glikson, E., & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. Academy of Management Annals, 14(2), 627-660.
[32] Gobet, F., & Sala, G. (2019). How artificial intelligence can help us understand human creativity. Frontiers in Psychology, 10, 397524.
[33] Grassini, S., & Koivisto, M. (2025). Artificial Creativity? Evaluating AI Against Human Performance in Creative Interpretation of Visual Stimuli. International Journal of Human-Computer Interaction, 41(7), 4037-4048.
[34] Grilli, L., & Pedota, M. (2024). Creativity and artificial intelligence: A multilevel perspective. Creativity and Innovation Management, 33(2), 234-247.
[35] Guzik E. E., Byrge C., & Gilde C. (2023). The originality of machines: AI takes the Torrance Test. Journal of Creativity, 33(3), 100065.
[36] Haase, J., & Hanel, P. H. (2023). Artificial muses: Generative artificial intelligence chatbots have risen to human-level creativity. Journal of Creativity, 33(3), 100066.
[37] Habib S., Vogel T., Anli X., & Thorne E. (2024). How does generative artificial intelligence impact student creativity? Journal of Creativity, 34(1), 100072.
[38] Han E., Yin D., & Zhang H. (2023). Bots with feelings: Should AI agents express positive emotion in customer service? Information Systems Research, 34(3), 1296-1311.
[39] Harris, L. T. (2024). The neuroscience of human and artificial intelligence presence. Annual Review of Psychology, 75, 433-466.
[40] Hitsuwari J., Ueda Y., Yun W., & Nomura M. (2023). Does human-AI collaboration lead to more creative art? Aesthetic evaluation of human-made and AI-generated haiku poetry. Computers in Human Behavior, 139, 107502.
[41] Hoffman, G., & Weinberg, G. (2011). Interactive improvisation with a robotic marimba player. Autonomous Robots, 31, 133-153.
[42] Hsu, L. (2022). To CALL or not to CALL: Empirical evidence from neuroscience. Computer Assisted Language Learning, 35(4), 792-815.
[43] Huang K. L., Liu Y. C., Dong M. Q., & Lu C. C. (2024). Integrating AIGC into product design ideation teaching: An empirical study on self-efficacy and learning outcomes. Learning and Instruction, 92, 101929.
[44] Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.
[45] Hubert K. F., Awa K. N., & Zabelina D. L. (2024). The current state of artificial intelligence generative language models is more creative than humans on divergent thinking tasks. Scientific Reports, 14(1), 3440.
[46] Hwang, A. H. C. (2022). Too late to be creative? AI-empowered tools in creative processes. In CHI Conference on human factors in computing systems extended abstracts (pp. 1-9). Association for Computing Machinery.
[47] Jeong, J., & Jeong, I. (2024). Driving creativity in the AI-enhanced workplace: Roles of self-efficacy and transformational leadership. Current Psychology, 44, 8001-8014.
[48] Jia N., Luo X., Fang Z., & Liao C. (2024). When and how artificial intelligence augments employee creativity. Academy of Management Journal, 67(1), 5-32.
[49] Kantosalo, A., & Riihiaho, S. (2019). Quantifying co-creative writing experiences. Digital Creativity, 30(1), 23-38.
[50] Karimi P., Rezwana J., Siddiqui S., Maher M. L., & Dehbozorgi N. (2020). Creative sketching partner: An analysis of human-AI co-creativity. Proceedings of the 25th international conference on intelligent user interfaces. Cagliari.
[51] Kaufman, J. C., & Beghetto, R. A. (2009). Beyond big and little: The four c model of creativity. Review of General Psychology, 13(1), 1-12.
[52] Kim, J., & Maher, M. L. (2023). The effect of AI-based inspiration on human design ideation. International Journal of Design Creativity and Innovation, 11(2), 81-98.
[53] Kim, S., & Oh, D. (2025). Evaluating creativity: Can LLMs be good evaluators in creative writing tasks? Applied Sciences, 15(6), 2971.
[54] Köbis, N., & Mossink, L. D. (2021). Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry. Computers in Human Behavior, 114, 106553.
[55] Koivisto, M., & Grassini, S. (2023). Best humans still outperform artificial intelligence in a creative divergent thinking task. Scientific Reports, 13(1), 13601.
[56] Kong H., Yin Z., Chon K., Yuan Y., & Yu J. (2024). How does artificial intelligence (AI) enhance hospitality employee innovation? The roles of exploration, AI trust, and proactive personality. Journal of Hospitality Marketing and Management, 33(3), 261-287.
[57] Lee, B. C., & Chung, J. Y. (2024). An empirical investigation of the impact of ChatGPT on creativity. Nature Human Behaviour, 8(10), 1906-1914.
[58] Lee, H. K. (2022). Rethinking creativity: Creative industries, AI and everyday creativity. Media, Culture and Society, 44(3), 601-612.
[59] Li N., Yan Y., Yang Y., & Gu A. (2022). Artificial intelligence capability and organizational creativity: The role of knowledge sharing and organizational cohesion. Frontiers in Psychology, 13, 845277.
[60] Li X. M., Cheng M. T., & Xu J. C. (2022). Leaders' innovation expectation and nurses' innovation behaviour in conjunction with artificial intelligence: The chain mediation of job control and creative self-efficacy. Journal of Nursing Management, 30(8), 3806-3816.
[61] Liang X., Guo G., Shu L., Gong Q., & Luo P. (2022). Investigating the double-edged sword effect of AI awareness on employee's service innovative behavior. Tourism Management, 92, 104564.
[62] Liu X., Zhang W., Tong X., Zhong F., Li Z., Xiong Z., Xiong J., Wu X., Fu Z., & Tan X. (2023). MolFilterGAN: A progressively augmented generative adversarial network for triaging AI-designed molecules. Journal of Cheminformatics, 15(1), 42.
[63] Long D., Liu L., Gujrania S., Naomi C., & Magerko B. (2020). Visualizing improvisation in luminai, an ai partner for co-creative dance. Proceedings of the 7th International Conference on Movement and Computing, Association for Computing Machinery.
[64] Ma, X., & Huo, Y. (2024). Drawing a satisfying picture: An exploratory study of human-AI interaction in AI Painting through breakdown-repair communication strategies. Information Processing and Management, 61(4), 103755.
[65] Magni F., Park J., & Chao M. M. (2023). Humans as creativity gatekeepers: Are we biased against AI creativity? Journal of Business and Psychology, 39(3), 643-656.
[66] Maher, M. L. (2012). Computational and collective creativity: Who's being creative? In M. L. Maher, K. J. Hammond, A. Pease, R. P. Y. Pérez, D. Ventura, & G. A. Wiggins (Eds.), Proceedings of the third international conference on computational creativity (pp. 67-71). Association for Computational Creativity.
[67] Maier T., Soria Zurita N. F., Starkey E., Spillane D., McComb C., & Menold J. (2022). Comparing human and cognitive assistant facilitated brainstorming sessions. Journal of Engineering Design, 33(4), 259-283.
[68] Maksic, S., & Josic, S. (2021). Scaffolding the development of creativity from the students' perspective. Thinking Skills and Creativity, 41, 100835.
[69] Marrone R., Cropley D., & Medeiros K. (2024). How does narrow AI impact human creativity? Creativity Research Journal, 36, 1-11.
[70] Mazzone, M., & Elgammal, A. (2019). Art, creativity, and the potential of artificial intelligence. Arts, 8(1), 26.
[71] McGuire J., De Cremer D., & van de Cruys, T. (2024). Establishing the importance of co-creation and self-efficacy in creative collaboration with artificial intelligence. Scientific Reports, 14(1), 18525.
[72] Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information and Management, 58(3), 103434.
[73] Millet K., Buehler F., Du G., & Kokkoris M. D. (2023). Defending humankind: Anthropocentric bias in the appreciation of AI art. Computers in Human Behavior, 143, 107707.
[74] Nguyen, H., & Nguyen, A. (2024). Reflective practices and self-regulated learning in designing with generative artificial intelligence: An ordered network analysis. Journal of Science Education and Technology, 33, 1-15.
[75] Niloy A. C., Akter S., Sultana N., Sultana J., & Rahman, S. I. U. (2024). Is Chatgpt a menace for creative writing ability? An experiment. Journal of Computer Assisted Learning, 40(2), 919-930.
[76] Organisciak P., Acar S., Dumas D., & Berthiaume K. (2023). Beyond semantic distance: Automated scoring of divergent thinking greatly improves with large language models. Thinking Skills and Creativity, 49, 101356.
[77] Orwig W., Bellaiche L., Spooner S., Vo A., Baig Z., Ragnhildstveit A., Schacter D. L., Barr N., & Seli P. (2024). Using AI to generate visual art: Do individual differences in creativity predict AI-assisted art quality? Creativity Research Journal, 36, 1-12.
[78] Park H. W., Rosenberg-Kima R., Rosenberg M., Gordon G., & Breazeal C. (2017). Growing growth mindset with a social robot peer.Proceedings of the 2017 12th ACM/IEEE International Conference on Human-Robot Interaction, Association for Computing Machinery.
[79] Porto W. F., Irazazabal L., Alves E. S., Ribeiro S. M., Matos C. O., Pires Á. S., Fensterseifer I. C., Miranda V. J., Haney E. F., & Humblot V. (2018). In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design. Nature Communications, 9(1), 1490.
[80] Puranam, P. (2021). Human-AI collaborative decision-making as an organization design problem. Journal of Organization Design, 10(2), 75-80.
[81] Rafner J., Beaty R. E., Kaufman J. C., Lubart T., & Sherson J. (2023). Creativity in the age of generative AI. Nature Human Behaviour, 7(11), 1836-1838.
[82] Rezwana, J., & Maher, M. L. (2023). Designing creative AI partners with COFI: A framework for modeling interaction in human-AI co-creative systems. ACM Transactions on Computer-Human Interaction, 30(5), 1-28.
[83] Rong Q. M., Lian Q., & Tang T. R. (2022). Research on the influence of AI and VR technology for students' concentration and creativity. Frontiers in Psychology, 13, 767689.
[84] Runco, M. A. (2023). AI can only produce artificial creativity. Journal of Creativity, 33(3), 100063.
[85] Runco, M. A. (2025). Updating the standard definition of creativity to account for the artificial creativity of AI. Creativity Research Journal, 37(1), 1-5.
[86] Seeber I., Bittner E., Briggs R. O., De Vreede T., De Vreede G. J., Elkins A., Maier R., Merz A. B., Oeste-Reiß S., & Randrup N. (2020). Machines as teammates: A research agenda on AI in team collaboration. Information and Management, 57(2), 103174.
[87] Senior A. W., Evans R., Jumper J., Kirkpatrick J., Sifre L., Green T., Qin C., Žídek A., Nelson A. W., & Bridgland A. (2020). Improved protein structure prediction using potentials from deep learning. Nature, 577(7792), 706-710.
[88] Shaer O., Cooper A., Mokryn O., Kun A. L., & Ben Shoshan H. (2024). AI-Augmented Brainwriting: Investigating the use of LLMs in group ideation. Proceedings of the CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery.
[89] Stokes J. M., Yang K., Swanson K., Jin W., Cubillos-Ruiz A., Donghia N. M., MacNair C. R., French S., Carfrae L. A., & Bloom-Ackermann Z. (2020). A deep learning approach to antibiotic discovery. Cell, 180(4), 688-702.
[90] Tang M., Hofreiter S., Werner C. H., Zielińska A., & Karwowski M. (2024). "Who" is the best creative thinking partner? An experimental investigation of human-human, human-internet, and human-AI co-creation. The Journal of Creative Behavior, 59(3), 1-22.
[91] Tigre Moura F., Castrucci C., & Hindley C. (2023). Artificial intelligence creates art? An experimental investigation of value and creativity perceptions. The Journal of Creative Behavior, 57(4), 534-549.
[92] Urban M., Děchtěrenko F., Lukavský J., Hrabalová V., Svacha F., Brom C., & Urban K. (2024). ChatGPT improves creative problem-solving performance in university students: An experimental study. Computers and Education, 215, 105031.
[93] Verma, S., & Singh, V. (2022). Impact of artificial intelligence-enabled job characteristics and perceived substitution crisis on innovative work behavior of employees from high-tech firms. Computers in Human Behavior, 131, 107215.
[94] Vinchon F., Lubart T., Bartolotta S., Gironnay V., Botella M., Bourgeois-Bougrine S., Burkhardt J. M., Bonnardel N., Corazza G. E., & Glăveanu V. (2023). Artificial intelligence & creativity: A manifesto for collaboration. The Journal of Creative Behavior, 57(4), 472-484.
[95] Wang H., Fu T., Du Y., Gao W., Huang K., Liu Z., Chandak P., Liu S., Van Katwyk P., & Deac A. (2023). Scientific discovery in the age of artificial intelligence. Nature, 620(7972), 47-60.
[96] Wang H., Zhang H., Chen Z., Zhu J., & Zhang Y. (2022). Influence of artificial intelligence and robotics awareness on employee creativity in the hotel industry. Frontiers in Psychology, 13, 834160.
[97] Wang S., Sun Z., & Chen Y. (2023). Effects of higher education institutes' artificial intelligence capability on students' self-efficacy, creativity and learning performance. Education and Information Technologies, 28(5), 4919-4939.
[98] Wang, Y., & Lau, D. C. (2022). How and why job crafting influences creative performance? A resource allocation explanation of the curvilinear moderated relations. Asia Pacific Journal of Management, 39(4), 1561-1587.
[99] Wingström R., Hautala J., & Lundman R. (2024). Redefining creativity in the era of AI? Perspectives of computer scientists and new media artists. Creativity Research Journal, 36(2), 177-193.
[100] Wu Z., Ji D., Yu K., Zeng X., Wu D., & Shidujaman M. (2021). AI creativity and the human-AI co-creation model. In M. Kurosu (Ed.), Human-computer interaction. Theory, methods and tools (pp. 171-190). Springer.
[101] Yilmaz, R. M., & Goktas, Y. (2017). Using augmented reality technology in storytelling activities: Examining elementary students' narrative skill and creativity. Virtual Reality, 21, 75-89.
[102] Yin M., Jiang S., & Niu X. (2024). Can AI really help? The double-edged sword effect of AI assistant on employees' innovation behavior. Computers in Human Behavior, 150, 107987.
[103] Yin Y., Jia N., & Wakslak C. J. (2024). AI can help people feel heard, but an AI label diminishes this impact. Proceedings of the National Academy of Sciences, 121(14), e2319112121.
[104] Zeijen M. E., Peeters M. C., & Hakanen J. J. (2018). Workaholism versus work engagement and job crafting: What is the role of self-management strategies? Human Resource Management Journal, 28(2), 357-373.
[105] Zeki, S. (2001). Artistic creativity and the brain. Science, 293(5527), 51-52.
[106] Zeng Z., Sun X., & Liao X. (2019). Artificial intelligence augments design creativity: A typeface family design experiment. In A. Marcus & W. Wang (Eds.), Design, user experience, and usability. User experience in advanced technological environments (pp. 400-411). Springer.
[107] Zhang Z., Wen F., Sun Z., Guo X., He T., & Lee C. (2022). Artificial intelligence-enabled sensing technologies in the 5G/internet of things era: From virtual reality/augmented reality to the digital twin. Advanced Intelligent Systems, 4(7), 2100228.
[108] Zhou, E., & Lee, D. (2024). Generative artificial intelligence, human creativity, and art. PNAS Nexus, 3(3), pgae052.