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研究生: 李尤怡
ASALI, ELISA
論文名稱: 生成式人工智慧使用之內在機制與其雙面效應對設計師創意表現的影響:整合專業認同與意義追尋的觀點
Examination of The Two-Sword Effects of Intrinsic Mechanisms toward Generative AI Usage on Designers' Creativity Performances: Integrating the Perspectives of Professional Identity and Meaningfulness Pursuit
指導教授: 洪秀瑜
Hung, Hsiu-Yu
口試委員: 洪秀瑜
Hung, Hsiu-Yu
陳彥君
Chen, Yan Jun
蔡顯童
Cai, Xian Tong
口試日期: 2024/05/27
學位類別: 碩士
Master
系所名稱: 管理研究所
Graduate Institute of Management
論文出版年: 2024
畢業學年度: 112
語文別: 英文
論文頁數: 62
中文關鍵詞: 生成式人工智慧職業認同意義創造力職業藝術家
英文關鍵詞: Generative AI, Professional Identity, Meaningfulness, Creativity, Professional Artists
研究方法: 調查研究
DOI URL: http://doi.org/10.6345/NTNU202400528
論文種類: 學術論文
相關次數: 點閱:109下載:7
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  • 人工智慧的領域可能並不新穎,但仍可被視為處於萌芽階段。隨著創意產業爭相創建越來越先進的生成式人工智慧工具,並競相成為首批實施這些新技術的企業,它們往往未考慮這樣做的潛在影響。鑒於這個領域的崭新性以及之前關於其對創意產業影響的研究缺乏,本研究對於負責創意團隊的管理者來說,提供了一個警示,提醒他們關注人工智慧使用對專業身份感、意義感和創意產出等方面的影響,並為人工智慧使用對專業藝術家這一特定領域的影響提供了實證結果。本研究依賴於從 Prolific 平台收集的294名專業藝術家的回應,並經過多重篩選以確保準確性。本研究將專業藝術家定義為擁有藝術/設計相關領域的正式教育,或在該行業擁有工作經歷(或曾經擁有)的個體。利用部分最小二乘結構方程模型(PLS-SEM),本研究結果顯示專業藝術家使用人工智慧與其專業身份感、意義感和感知創意之間存在正向關係。這意味著在支持性環境中使用人工智慧可以增強藝術家的身份感、從創意工作中獲得的意義感以及展現的創意。相反,在非支持性環境中則會導致相反的結果。就警示因素而言,本研究建議管理者更好地考慮影響其下屬的因素,例如在本案例中是生成式人工智慧這一有爭議的新技術的實施

    The field of Artificial Intelligence might not be new, but it could still be considered to be in its nascent stages. As the creative industry races to create more and more sophisticated Generative AI tools, and compete to be the first to implement these new technologies, they often fail to take into consideration the potential impact of doing so. Given how new this field are and the lack of previous research regarding its impact on the creative industry, this research serves as a warning to managers in charge of a group of creatives on the impact of AI usage on their professional identity, perception of meaningfulness, and creativity output, as well as a contributor of empirical results on the field of AI usage impact on the specific domain of professional artists. This study relies on responses from 294 professional artists gathered from the platform Prolific, screened through several filters to ensure accuracy. Professional artists are defined by this study as those who possess a formal education in art/design related fields, or those who possess a job (or previously do so) in said industry. Using PLS-SEM, the results of this study explain how AI usage by professional artists has a positive relationship with their professional identity, perception of meaningfulness, and perceived creativity. This implies that AI usage in a supportive environment could enhance artistic identity, the meaning derived from creative work, and the creativity exuded. Within a non-supportive environment on the other hand would result in the opposite. In terms of the warning factor, this research suggests managers take better consideration of the things affecting those under their lead, such as in this case the implementation of controversial new technology, Generative AI.

    Acknowledgment 致謝辭 i English Abstract ii 中文摘要 iii Table of Contents iv Table of Tables vi Table of Figures vii Chapter I Introduction 1 1.1 Research Background and Motivation 1 1.2 Research Question and Significance of Research 3 1.3 Research Process 6 Chapter II Literature Review 8 2.1 Generative Art 8 2.2 Creativity Performance 9 2.2.1 Creativity Augmentation 11 2.2.2 Perceived Enhanced Creativity With AI 11 2.2.3 Perceived Declining Creativity With AI 12 2.4 Identity and Professional Identification 13 2.5 Antecedents of Professional Identity 14 2.5.1 Professional Self-Identification 14 2.5.2 Professional Socialization 14 2.6 The Outcome of Professional Identity 15 2.7 The Perception of Meaningfulness 16 2.8 Antecedents of Meaningfulness Perception 17 2.8.1 Sense of Purpose 17 2.8.2 Sense of Significance 17 2.8.3 Sense of Connectedness 18 2.9 The Outcome of Meaningfulness Perception 19 2.10 The Bidirectional Relationship Between Two Mediation Mechanisms: Professional Identity and Meaningfulness Perception 19 Chapter III Methodology 21 3.1 Conceptual Model 21 3.2 Sample Selection 22 3.3 Measures and Questionnaire Design 23 3.3.1 Questionnaire Design 23 3.3.2 Development of Measures 23 3.4 Data Collection Procedure 27 3.5 Research Tools 27 3.5.1 Structural Equation Modeling (SEM) 27 Chapter IV Results 29 4.1 Descriptive Statistics 29 4.1.1 Sample Profile analysis 29 4.1.2 Reliability and Validity Analysis 32 4.1.3 Structural Model Estimation and Hypothesis Testing 35 Chapter V Conclusion 43 5.1 General Discussion 43 5.2 Theoretical Contribution 43 5.3 Managerial Implications 45 5.4 Limitations and Future Research 46 References 48 Appendix 1 Questionnaire Items 58

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