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Navigating agency tensions and governance in Generative Artificial Intelligence
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Lu-lu YAN1, Cong CHENG1, Chang-wei GUO2
Studies in Science of Science | 2026, 44(2) : 315 - 324
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Studies in Science of Science | 2026, 44(2): 315-324
• Theories and Methods •
Navigating agency tensions and governance in Generative Artificial Intelligence
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Lu-lu YAN1, Cong CHENG1, Chang-wei GUO2
Affiliations
  • 1 School of Management, Zhejiang University of Technology, Hangzhou 310023, China
  • 2 Science and Technology, School of Management, University of Science and Technology of China, Hefei 230026, China
Published: 2026-02-15
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Generative Artificial Intelligence (GAI) has become deeply embedded in the socio-economic fabric of human society, and its growing agency has emerged as a focal point of both theoretical debate and practical concern. On the one hand, GAI increasingly exhibits capabilities traditionally regarded as uniquely human, including interactive intelligence, cognitive flexibility, and creative expression. These characteristics not only enhance GAI’s functionality but also open new avenues for augmenting human cognition. On the other hand, the generative processes of GAI are frequently associated with factual inaccuracies, reasoning biases, and ethical dilemmas, leading to a fragile trust relationship between humans and machines. As a result, human reliance on GAI coexists with mounting skepticism, creating a fundamental tension between its empowering potential and the risks of technological unpredictability and moral ambiguity.

This paper investigates the question of what paradoxical tensions accompany the rise of GAI’s agency and how these tensions may be addressed. We first identify that GAI’s agency is characterized by three core features—interactivity, autonomy, and creativity—each of which is enabled by distinct forms of technological affordance. Interactivity is shaped by perceptual and communicative affordances, autonomy by operational and situational affordances, and creativity by the interplay of interactive and situational affordances. While these features empower GAI with remarkable generative capabilities, they simultaneously give rise to complex system-level risks and trust challenges. Specifically, the high degree of interactivity leads to a lack of transparency in generative logic, producing a “black-box” effect that impedes user understanding. The rise in autonomy undermines users’ sense of control, as GAI’s decision-making processes and behavioral evolution become increasingly opaque and less predictable. Meanwhile, its expanding creative potential complicates the attribution of accountability, creating asymmetries in responsibility where the more novel the output, the more ambiguous its moral and legal ownership.

These contradictions manifest in three interconnected paradoxes: the interaction-transparency paradox, wherein GAI’s interactive flexibility conflicts with the opacity of its generative mechanisms; the autonomy-controllability paradox, where heightened decision-making independence erodes human oversight; and the creativity-accountability paradox, in which increasing innovation introduces diffuse and deferred responsibility. Addressing these challenges requires a shift in governance strategies: enhancing interpretability through explainable AI and knowledge mediation, reinforcing human oversight via participatory design and feedback mechanisms, and clarifying ethical boundaries through shared responsibility and robust accountability frameworks. Only by navigating these tensions thoughtfully can we ensure that the technological advancements of GAI genuinely serve collective human interests and foster a synergistic development of both technological and societal values.

Generative Artificial Intelligence (GAI)  /  agency  /  affordance  /  trust  /  paradoxical tension
严璐璐, 程聪, 郭长伟. 生成式人工智能主体性的矛盾张力与治理研究. 科学学研究, 2026 , 44 (2) : 315 -324 .
Lu-lu YAN, Cong CHENG, Chang-wei GUO. Navigating agency tensions and governance in Generative Artificial Intelligence[J]. Studies in Science of Science, 2026 , 44 (2) : 315 -324 .
Year 2026 volume 44 Issue 2
68
34
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  • Receive Date:2024-12-10
  • Online Date:2026-10-09
  • Published:2026-02-15
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  • Received:2024-12-10
  • Revised:2025-06-16
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    1 School of Management, Zhejiang University of Technology, Hangzhou 310023, China
    2 Science and Technology, School of Management, University of Science and Technology of China, Hefei 230026, China
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