Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
We build a model of online behavioral manipulation driven by AI advances. A platform dynamically offers one of n products to a user who slowly learns product quality. User learning depends on a product's "glossiness," which captures attributes that make products appear more attractive than they are. AI tools enable platforms to learn glossiness and engage in behavioral manipulation. We establish that AI benefits consumers when glossiness is short-lived. In contrast, when glossiness is long-lived, behavioral manipulation reduces user welfare. Finally, as the number of products increases, the platform can intensify behavioral manipulation by presenting more low-quality, glossy products.