“Algorithmic Transparency” or “Algorithm Panic”? A Literature Review and Frontier Issues on AIGC Advertising Transparency and Consumer Responses

Abstract

The quick dissemination of generative artificial intelligence (AIGC) is changing the production methods of the advertising industry, and has also pushed “whether to disclose and how to disclose” to the center of regulation and the market. On a global scale, AI labeling systems have been implemented one after another, while academia still has obvious disagreements about what AIGC advertising transparency will bring-Is transparency a good medicine for restoring trust, or a hidden danger that damages advertising effectiveness? This research, based on literature from the Web of Science Core Collection and the China National Knowledge Infrastructure (CNKI), adopts a systematic review method to sort out the conceptual connotation, effect evidence, theoretical explanations, boundary conditions, and research gaps of AIGC advertising transparency. The paper ascertains that the impact of AIGC advertising transparency on consumers has a “double-edged sword” characteristic, that is to say, its net effect depends on the interaction between disclosed information and consumers’ existing expectations. The uncanny valley theory, CASA theory, the persuasion knowledge model, and attribution theory are not competing with one another; rather, they separately explain different links in the temporal chain of “expectation formation—expectation violation—defense activation—attribution judgment.” The direction and strength of the effect are also moderated by multiple factors, including consumer characteristics, brand and product factors, advertising formats, and platform contexts. In this context, this paper constructs an integrated theoretical framework and proposes future issues, such as differentiation of disclosure framing, differential effects of advertising formats, dynamic transparency, and human-AI collaborative transparency, providing a foundation for subsequent empirical research and regulatory practice.