大陆成人直播

Designing Detection Algorithms for AI-Generated Content:Consumer Inference, Creator Incentives, and Platform Strategy

时间：2025年9月26日10：00

地点：承泽园229教室

Speaker: Jieteng Chen

Abstract:

Generative AI has transformed content creation, enhancing efficiency and scalability across media platforms. However, it also introduces substantial risks, particularly the spread of misinformation that can undermine consumer trust and platform credibility. In response, platforms deploy detection algorithms to distinguish AI-generated from human-created content, but these systems face inherent trade-offs: aggressive detection lowers false negatives (failing to detect AI-generated content) but raises false positives (misclassifying human-created content), discouraging truthful creators. Conversely, conservative detection protects creators but weakens the informational value of labels, eroding consumer trust. We develop a model in which a platform sets the detection threshold, consumers form beliefs from content labels and decide whether to engage, and creators choose whether to adopt AI and how much effort to exert to create content. We find that as the detection threshold varies, the equilibrium structure undergoes a regime shift. At low thresholds, consumers trust human labels and partially engage with AI-labeled content, disciplining AI misuse and boosting engagement. But when the detection threshold becomes higher, this inference breaks down, AI adoption rises, and both trust and engagement collapse. Thus, the platform’s optimal detection strategy balances these risks, influencing content creation incentives, consumer beliefs, and overall welfare.

Introduction of Speaker

Jieteng Chen is a PhD candidate in Marketing from the Chinese University of Hong Kong. His research explores the economics of AI, digital platforms, and industrial organization, with a particular focus on algorithmic design by online platforms and the business implications of emerging technologies. His work has been published in Journal of Marketing Research, and he has an ongoing project at an advanced stage in Management Science. His research is supported by NSFC Research Grant for PhD Students.