Recommendation systems and trust on adult media platforms
By many accounts, recommendation systems on adult media platforms are neutral engines that merely reflect user preferences. We challenge that misconception because these algorithms do more than mirror tastes: they shape discovery, normalize certain content, and influence boundaries of consent and safety. As platform designers, researchers, and consumers, we examine how opaque ranking, feedback loops,…
