| 研究生: |
陳愷燈 Vuong Tran Dang |
|---|---|
| 論文名稱: |
J.A.R.V.I.S 展望:⼈⼯智慧驅動的代理⼯作流程中的⼈類代理 A J.A.R.V.I.S In Sight: Human Agency in Agentic AI-powered Workflow |
| 指導教授: |
蔡葵希
Christine L.Cook |
| 口試委員: |
張永儒
Yung-Ju Chang 侯宗佑 Yo-yo |
| 學位類別: |
碩士
Master |
| 系所名稱: |
創新國際學院 - 全球傳播與創新科技碩士學位學程 Master’s Program in Global Communication and Innovation Technology |
| 論文出版年: | 2026 |
| 畢業學年度: | 115 |
| 語文別: | 英文 |
| 論文頁數: | 61 |
| 中文關鍵詞: | 自主型 AI 、人類主體感 、自主性 、實驗性研究 |
| 外文關鍵詞: | Agentic AI, Human Agency, Autonomy, Experimental Research |
| 相關次數: | 點閱:26 下載:0 |
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隨著自主型 AI(agentic AI)系統變得日益智慧與自主,理解人類主體感(human agency)與此項新技術之間的心理連結,對於促進更佳的協作並防止使用者喪失主導權至關重要。本研究探討了在整合自主型 AI 的工作流程中,人類主體感的潛在連結與影響。
我們的研究結果表明,人類主體感的下降主要取決於 AI 系統的設計,而非使用者個人的特徵。至關重要的一點是,在我們的研究中,人口統計因素與先前的 AI 熟練度並未對這種主體感的流失產生明確的緩解效果;這表明以使用者為核心的干預措施(例如現行的提升技能培訓)可能不足以應對此一挑戰。
組織與開發者不應僅專注於使用者的適應,而必須進行根本性的重新評估,甚至重新設計,以確保人類在人機互動動態中仍扮演決定性的角色。這些見解為未來的研究提供了切入點,並為尋求設計與導入自主型 AI 系統、同時保留人類自主權的服務提供者、政策制定者及企業領導者提供了具操作性的指引。
As agentic AI systems become increasingly intelligent and autonomous, understanding the psychological connection between human agency and this new technology is critical to better facilitate the collaboration as well as preventing user disempowerment. This study investigates the potential connection and influence of human sense of agency in workflows integrated with agentic AI. Our findings indicate that a decline in human agency are primarily dictated by the AI system’s design rather than individual user characteristics. Crucially, in our study demographic factors and prior AI proficiency didn’t produce clear effect against such loss in agency, demonstrating that user-focused interventions such as current upskilling training may be insufficient to address this challenge. Rather than focusing solely on user adaptation, organizations and developers must fundamental re-evaluate and potentially re-design to ensure human still have the deciding role in the human-AI dynamic. These insights offer an entry point for future research and provide actionable guidance for service providers, policymakers, and business leaders seeking to design and implement agentic AI systems that preserve human autonomy.
Introduction 8
Theoretical Background 10
Artificial Intelligence – From Generative to Agentic: Definition and Scope 10
The Concept of Agency in Human-Technology Interactions 12
The Traditional View on Human Agency 12
Non-Human Agency 14
Autonomy vs Agency vs Power 15
Actor Network Theory 16
Symbiotic or Parasitic? 17
Methodology 20
Findings and Results 25
Impact of Agentic AI usage to the sense of Agency 25
Impact of Demographic and Attitudinal Factors 26
Full Integrated Model 28
Discussion 30
The confirmation of Actor-Network theory and the “reactive” role of human agency 30
The Parasitic Effect of Agentic AI 31
The Universality of Agency Experience 32
Practical Implications 33
Limitations and Future Directions 35
Conclusion 38
References 39
Appendix 46
Appendix 1: Informed Consent Form (V2, 20251029) 46
Appendix 2: Post-experiment Survey with customed Sense of Agency Scale 51
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