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Title: | 以情境危機溝通理論檢視AI危機策略與傳播效果:自駕車案例分析 Examining AI Crisis Strategies and Communication Effectiveness Through Situational Crisis Communication Theory (SCCT): An Analysis of Autonomous Vehicle Incidents |
Authors: | 吳湘雲 Wu, Hsiang-Yun |
Contributors: | 陳憶寧 Chen, Yi-Ning 吳湘雲 Wu, Hsiang-Yun |
Keywords: | 公關危機 危機溝通 情境危機溝通理論 危機框架 人工智慧失誤 Public relations crisis Crisis communication Situational Crisis Communication Theory Crisis framing AI failure |
Date: | 2025 |
Issue Date: | 2025-08-04 15:14:54 (UTC+8) |
Abstract: | 本研究基於情境危機傳播理論(Situational Crisis Communication Theory, SCCT),探討AI失誤(AI Failure)中的危機傳播與效果,本研究以AI自駕車事故為例,分析當媒體與企業將危機框定為「倫理問題」或「技術問題」時,如何影響公眾對企業危機責任的認知、情緒反應與行為意圖。本研究亦納入個體對AI自駕車議題的涉入程度作為調節變項,檢視其對危機訊息效果的影響。
本研究以2018年Uber自駕車撞擊行人致死事件為背景參考,模擬AI自駕車失誤所引發的危機情境,實驗採用2(媒體報導框架:倫理/技術)×2(企業回應策略:倫理/技術)×2(AI自駕車之議題涉入程度:高/低)之受試者設計,以文字控制媒體與企業如何描述事故原因,並透過問卷測量受試者對企業危機責任認知、所產生的情緒(包括道德義憤、憤怒與同情)以及抵制企業的行為意圖。共蒐集402份有效樣本,並透過結構方程模型(SEM)檢驗各主要變項之間的關係。
結果顯示,媒體與企業框架對危機責任的影響不顯著,可能反映AI危機情境下責任歸屬的模糊性,加上公眾對資訊來源的懷疑態度,認為難以透過簡短敘述評判責任,降低了外部敘事的影響力。而危機責任則對情緒反應具有顯著影響,即企業可控制危機的程度越高,越難喚起同情;危機所造成的損害程度越高,則越易激起憤怒與道德義憤,並進一步正向影響抵制意圖,顯示情緒為認知與行為間的重要中介。
本研究為AI危機情境中的危機管理與傳播策略提供新視角,補足SCCT於AI失誤議題上的應用限制,亦回應近年對AI技術信任與溝通倫理的關注。研究建議,在高模糊性與倫理敏感度高的AI議題中,單一的框架敘事未必能有效引導公眾認知,企業應優先採取透明與高互動性的溝通策略,不僅於危機發生後積極回應,更應於日常營運中逐步建立與利益關係人之間的對話機制與信任。 This study, based on Situational Crisis Communication Theory (SCCT), explores crisis communication in the context of AI failures. Using an AI self-driving car accident as an example, it analyzes how media and corporate framing—whether as an “ethical issue” or a “technical issue”—affects public perceptions of crisis responsibility, emotional responses, and boycott intentions. It also considers individuals’ involvement with the AI self-driving car issue as a moderating factor.
Using the 2018 Uber self-driving fatality as a reference, the study simulates an AI self-driving crisis scenario. A 2 (media framing: ethical/technical) × 2 (corporate response: ethical/technical) × 2 (issue involvement: high/low) between-subjects design was used. Written scenarios controlled how the cause was described, and participants completed a questionnaire measuring perceptions of responsibility, emotions (moral outrage, anger, sympathy), and boycott intentions. A total of 402 valid responses were analyzed using structural equation modeling (SEM).
Results show that media and corporate framing did not significantly affect perceptions of crisis responsibility. This may reflect the ambiguity of responsibility attribution in AI-related crises and the public’s skepticism toward information sources, which makes it difficult to judge responsibility based on brief statements. However, crisis responsibility perceptions significantly affected emotional responses: higher perceived controllability by the company reduced sympathy, while greater perceived damage severity increased anger and moral outrage, which in turn positively influenced boycott intentions. This highlights the role of emotion as a key mediator between cognition and behavior.
This study offers a new perspective on crisis management and communication strategies in AI contexts, addressing limitations in applying SCCT to AI failure scenarios and responding to concerns about trust in AI technology and communication ethics. The findings suggest that in highly ambiguous and ethically sensitive AI issues, a single framing narrative may not effectively shape public perceptions. Companies should prioritize transparent and interactive communication—not only responding actively after a crisis but also building dialogue and trust with stakeholders through ongoing engagement. |
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Description: | 碩士 國立政治大學 傳播學院傳播碩士學位學程 112464040 |
Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0112464040 |
Data Type: | thesis |
Appears in Collections: | [傳播學院傳播碩士學位學程] 學位論文
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