Artificial Authenticity: The Transparency Paradox in SME Marketing

Engineering notes

Key topics: autonomous driving. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

This study examines how disclosure of Generative AI usage in SME marketing creates a "Transparency Paradox" that simultaneously demands and undermines consumer trust. An integrative literature review synthesizes empirical studies on AI disclosure effects with Signaling Theory and the Integrative Model of Organizational Trust, focusing on customer-facing communications where source authenticity underpins SMEs’ competitive advantage. The analysis identifies a core tension: while customers demand transparency, explicit AI labeling triggers a "Word-of-Machine" effect and a Personalization Paradox, reducing perceived value and emotional connection in hedonic contexts; conversely, concealing AI usage constitutes "AI-washing," risking reputational damage upon exposure. For SMEs relying on relational proximity as a core asset, this paradox is damaging. Given limited longitudinal evidence, findings draw on case studies and cross-contextual inference. The research demonstrates that technical transparency is insufficient; SMEs require 'Artificial Authenticity' strategies emphasizing human-in-the-loop oversight, linking ethics washing to psychological rejection of automated agency in SME marketing.

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