近年來，在大型語言模型的成熟和擴散的推動下，人工智慧的快速發展導致了生成式人工智慧工具的出現。這些工具很快就成為提高知識工作者生產力的關鍵。透過大型語言模式帶來的發散性思維和認知能力，生成式人工智慧平台提供了有別於傳統資訊系統的生產力提升，培養了更廣泛的思維和創造力。生成式人工智慧的主動性和創造性屬性不僅增強了能力，也為知識工作者帶來了新的可能性。然而，專業知識工作者和生成人工智慧之間的合作仍然是一個不斷發展且研究不足的現象。
工作好奇心，即探索新經驗和知識的動力，深刻影響員工對人工智慧任務協作的態度。本研究借鑒自決理論 (SDT)，探討了專業工作者的好奇心如何影響他們對工作中 AIGC 的信任。遵循 SDT 的子理論—認知評估理論，我們研究了員工感知到的工作複雜性和任務多樣性如何影響好奇心-信任關係。實證資料收集自 302 名具有 AI 工具工作經驗的專業級員工，包括來自台灣各行業的研發人員、軟體產品/專案經理以及行銷和銷售專業人員。
研究結果表明，快樂驅動的工作好奇心會積極影響員工對 AIGC 的信任，而承受壓力的工作好奇心則與對 AIGC 的不信任呈正相關。有趣的是，我們發現高工作複雜性削弱了快樂驅動的好奇心對 AIGC 信任的正面影響，並放大了耐壓好奇心對 AIGC 不信任的負面影響。此外，當員工執行高度多樣化的任務時，快樂驅動的好奇心對 AIGC 信任的正面影響變得更加明顯。這些發現為人工智慧與人類協作提供了新的見解，並強調了人工智慧驅動的智力活動背景下組織心理學的未來研究途徑。這項研究強調了工作好奇心在決定個人對人工智慧協作的態度方面的關鍵作用，為應用心理學研究和人機互動文獻做出了貢獻。

The rapid development of AI in recent years, driven by the maturation and proliferation of large language models, has led to the emergence of generative AI tools. These tools have quickly become essential for enhancing the productivity of knowledge workers. Through the divergent thinking and cognitive capabilities enabled by large language models, generative AI platforms offer a productivity boost distinct from traditional information systems, fostering broader thinking and creativity. Generative AI’s proactive and creative attributes not only enhance capabilities but also enable new possibilities for knowledge workers. However, collaboration between professional knowledge workers and generative AI remains an evolving and under-researched phenomenon.
Work curiosity, the motivational drive to explore new experiences and knowledge, profoundly influences employees’ attitudes towards task collaboration with AI. Drawing on Self-Determination Theory (SDT), this study explores how professional workers’ curiosity affects their trust in AIGC at work. Following the SDT’s sub-theory, Cognitive Evaluation Theory, we investigate how the curiosity-trust connection is impacted by employees’ perceived job complexity and task variety. The empirical data was collected from 302 professional-level employees with AI tool experience for work purposes, including R&D personnel, software product/project managers, and marketing and sales professionals from various industries in Taiwan.
Findings indicate that joy-driven work curiosity positively affects employees’ trust in AIGC, whereas stress-tolerating work curiosity is positively associated with distrust in AIGC. Interestingly, we found that high job complexity attenuates the positive effect of joy-driven curiosity on trust in AIGC and amplifies the negative effect of stress-tolerant curiosity on distrust in AIGC. Moreover, when employees perform tasks with high variety, the positive influence of joy-driven curiosity on trust in AIGC becomes more pronounced. These findings provide new insights into AI-human collaboration and highlight avenues for future research on organizational psychology in the context of the AI-driven intellectual activities. This study contributes to applied psychology research and human-computer interaction literature by highlighting the critical role of work curiosity in determining individuals’ attitudes towards AI collaboration.

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