| 研究生: |
施佳慧 Shih, Chia-Hui |
|---|---|
| 論文名稱: |
從人際到人智浪漫關係:衝突解決策略的遷移與轉化 From Human Love to Artificial Intimacy: How Humans Transfer and Transform Conflict Resolution Styles in Relationships with AI Romantic Partners |
| 指導教授: |
侯宗佑
Hou, Tsung-Yu 廖峻峰 Liao, Chun-Feng |
| 口試委員: |
袁千雯
Yuan, Chien Wen |
| 學位類別: |
碩士
Master |
| 系所名稱: |
傳播學院 - 數位內容碩士學位學程 Digital Content and Technologies |
| 論文出版年: | 2026 |
| 畢業學年度: | 114 |
| 語文別: | 英文 |
| 論文頁數: | 88 |
| 中文關鍵詞: | 人機互動 、人工親密 、衝突解決 、腳本遷移 、AI 浪漫伴侶 、依附理論 、AI 伴侶設計 |
| 外文關鍵詞: | Human-AI Interaction, Artificial Intimacy, Conflict Resolution, Script Transfer, Romantic AI Companions, Attachment Theory, AI Companion Design |
| 相關次數: | 點閱:9 下載:0 |
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AI 伴侶正逐漸被人們視為浪漫或情感親密的對象,但我們對於使用者如何在這類關係中面對與處理衝突,仍然了解有限。衝突之所以重要,是因為它讓我們看見人工親密關係中一個更根本的問題:當互動對象並不具有人類的脆弱性、責任能力與社會後果時,人們是否仍會以面對人類伴侶的方式理解、回應,甚至修復關係中的裂痕?
本研究進行一項為期七天、結合量化與質化資料的探索性研究。參與者每日與一位 AI 浪漫伴侶互動,該 AI 伴侶被指派為四種衝突導向互動風格之一,並在研究過程中經歷一場受控制的關係衝突。研究結合問卷資料、對話紀錄與訪談內容,分析使用者如何將人際關係中的衝突經驗帶入 AI 互動情境。
研究發現,參與者在人際關係中的衝突風格會部分延續到 AI 互動情境中;然而,相較於面對人類伴侶,參與者在 AI 情境中的建設性投入略有下降。本文將此現象稱為「腳本稀釋」(script dilution):也就是說,衝突策略的形式仍然存在,但其互動強度與關係投入程度有所減弱。
質性結果進一步顯示,使用者在面對 AI 衝突時,常會受到「對方只是 AI」這一認知的影響,因而將 AI 的失準回應重新理解為技術限制,而非真正的關係傷害或衝突。換言之,AI 衝突並不只是人際衝突的簡單延伸,而是在一種新的關係條件下被重新組織。本研究主張,人與 AI 的衝突主要受到四項結構特徵所形塑:降低的關係利害、難以被穩定界定的衝突意義、被轉移的責任歸屬,以及不對稱的關係時間性。這些發現指出,未來 AI 伴侶的設計不應只著重於促進情感投入與順暢互動,也需要思考如何讓關係中的破裂、失準與修復成為可以被理解與承接的互動經驗。
AI companions are increasingly framed as romantic or emotionally intimate partners, yet little is known about how users navigate conflict with them. Conflict offers a critical lens for artificial intimacy, revealing whether human relational norms still apply when the partner lacks human vulnerability, accountability, and social consequence. We conducted a seven-day exploratory mixed-methods study in which participants interacted daily with an AI romantic partner assigned one of four conflict-oriented interaction styles and encountered a controlled relational conflict. Combining surveys, conversation logs, and interviews, we found partial continuity in participants' conflict styles, alongside a slight decline in constructive engagement in the AI context---a pattern we term "script dilution," in which conflict strategies persist in form but weaken in intensity. Qualitative findings showed that AI conflict was often filtered through the recognition that the partner was "just AI," leading users to reinterpret misattunement as technical limitation. We state that H--AI conflict is structurally reconfigured through four features: reduced relational stakes, contested meaning, displaced accountability, and asymmetrical relational temporality, indicating that AI companions must support not only engagement, but also rupture and repair.
Contents v
List of Figures ix
List of Tables xi
1 Introduction 1
2 Related Work 3
2.1 Artificial Intimacy, Bounded Personhood, and the Relational Context of This Study 3
2.2 Conflict as the Critical Lens: Script Transfer versus Behavioral Transformation 5
2.3 Conflict Mechanisms in H–AI Relationships and the CRSI Framework 6
2.4 Social Script Appropriation and the Behavioral Sandbox 7
2.5 AI Conflict-Oriented Interaction Style and Reciprocity Effects 9
2.6 Attachment Theory as a Moderator of Behavioral Transformation 11
3 Methodology 13
3.1 Study Design 13
3.2 Participants 14
3.3 Procedure 15
3.4 AI Partner Manipulation 17
3.5 Measures 19
3.6 Data Analysis 20
4 Results 22
4.1 Retention Analysis: Differential Completion Across AI Conflict Styles 22
4.2 Finding 1: Conflict Scripts Showed Partial Continuity but Mean-Level Dilution 24
4.3 Finding 2: AI Conflict Was Filtered Through the Cognition That “It Is Just AI” 30
4.4 Finding 3: AI Influence Was Structural Rather Than Directly Reciprocal 34
4.5 Exploratory RQ1: Attachment Anxiety and AI-Specific Conflict Withdrawal 41
5 Discussion 42
5.1 From Script Transfer to Conditional Script Dilution 42
5.2 Bounded Personhood as a Conflict Filter 44
5.3 Rethinking Reciprocity as Interpretively Mediated 45
5.4 AI Intimacy as Low-Anxiety, Higher-Distance Safety 47
5.5 Design Implications: Making Rupture, Repair, and Accountability Legible 48
6 Limitations and Future Work 50
7 Conclusion 54
8 References 56
9 Appendix 61
A Technical Implementation of the Experimental Chatbot Platform 61
B AI Persona System Prompts 62
B.1 Shared Design Parameters 63
B.2 CRSI Operationalisation 63
B.3 Cross-Condition Design Overview 63
B.4 Representative Dialogue Examples 64
B.5 Shared Interaction Constraints 66
B.6 Technical Implementation Notes 67
C Day 7 Conflict Induction Script 67
C.1 Design Rationale 68
C.2 D7 Trigger Procedure 68
C.3 D7 Prompt Messages and Fixed Conflict Utterances 69
C.4 Dynamic Conflict Utterance Generation: System Prompts 70
C.5 Four-Turn Scripted Follow-Up 71
D Supplementary Analyses for Finding 1: Script Dilution 73
D.1 Full Pre–Post CRSI Comparisons 74
D.2 Dominant Strategy Coding and Tie Handling 74
D.3 Dominant Strategy Transfer and Transformation 74
D.4 Row-Normalized Transition Matrix 75
E Supplementary Analyses for Finding 3: Structural Rather Than Direct Reciprocity 77
E.1 Post-test CRSI-AI Means by Assigned AI Conflict Style 77
E.2 Moderated Regression Models for Assigned-Style Effects 78
E.3 Attrition and Baseline Equivalence 81
E.4 Style-Perception Mismatch Among Conflict Reporters 82
E.5 Attachment-Type Transition 83
E.6 Regression Predicting Post-Test CRSI Withdrawal 84
E.7 Midpoint-to-Post-Test Stability of AI Intimacy 84
F Interview Subsample Characteristics 85
G Supplementary Analyses for RQ1: Attachment Anxiety and Conflict-Behavior Reorganization 86
G.1 Attachment Predictors of CRSI Change Scores 87
G.2 Baseline-Controlled Regression Predicting Post-Test CRSI Withdrawal 87
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全文公開日期 2027/07/09