Balancing Safety, Engagement, and Compliance: Evaluating the Impact of NSFW Governance on AI-Generated Content

Abstract

Generative AI platforms face unique governance challenges as they lower barriers to creating Not Safe for Work content. Unlike traditional platforms that moderate after publication, AI systems must govern during the creative process, fundamentally altering the user experience by reshaping perceived affordances. This shift in governance model remains critically understudied despite its growing importance. Collaborating with a leading text-to-image AI provider, we examine how implementing stricter NSFW content moderation affects user behavior. Our natural experiment with 88,427 users reveals that stricter governance led to a significant relative decline in subscription rates among users with NSFW intentions, reflecting affordance contraction obstructing user goals, while retained users adapted by complying with policies without reducing prompt diversity. The findings advance our understanding of affordance in responsible AI implementation by demonstrating how governance mechanisms can effectively redirect user behavior while preserving creativity, contributing to both platform safety and sustainable innovation.

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