Content Platform GenAI Regulation via Compensation
This addresses the issue of content distribution distortion and creator compensation for platforms using GenAI, but it is incremental as it proposes a specific economic scheme rather than a fundamental shift.
The paper tackles the problem of unregulated Generative AI (GenAI) usage on content platforms, which can distort content distribution and reduce consumer engagement and platform profits, and shows that a simple creator compensation scheme can incentivize more high-value human-generated content, improving engagement and profits while reducing data pollution for future GenAI training.
The use of Generative AI (GenAI) for creative content generation has gained popularity in recent years. GenAI allows creators to generate contents that are increasingly becoming indistinguishable to the human--generated counter--part at a much lower cost. While GenAI reshapes the competitive landscape of the contents market, the original creators were typically not compensated for their works that were used in the GenAI training. On the other hands, the wide--spread adoption of GenAI threatens to replace the human--generated shares of contents on content platforms, contaminating training data source for future GenAI models. In this paper, we argue that an unregulated usage of GenAI can also be harmful to the platform by causing a contents distribution distortion which can lower the consumers' engagement and the platform's profit. We show that a simple economically--driven creator compensation scheme, can incentivize more creation of high--value human--generated contents, without the need for an AI--detector. This reduces the data pollution for future GenAI training, while improves the consumer engagement and the platform's profit.