Marketing^AI

Advertising in AI Systems: Society Must Be Vigilant


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This paper examines how AI systems are likely to incorporate advertising, similar to web search and social media, but with new complexities due to their dynamic, personalized nature. The authors discuss potential methods for delivering commercial content, differentiating between static ads and "generative advertisements" seamlessly integrated into AI responses through product recommendations, placements, or paid visibility. The paper outlines key considerations for designing commercially-influenced AI systems, emphasizing faithfulness to sponsor information, maintaining core utility, respecting user privacy, and ensuring provenance of content. It also explores strategies users might employ to identify and mitigate commercial biases, including direct debiasing and multi-sampling, while acknowledging limitations and open questions regarding regulation, transparency, user autonomy, and the long-term impact on model quality.

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Marketing^AIBy Enoch H. Kang