One Size Fits None: Effectiveness and Acceptability of Personalized Transparency and Privacy Assistance in the United States, the European Union, and China

This thesis asks whether personalization could fix one of privacy law’s biggest problems: disclosures are too long, too complex, and often give users little real control. It compares transparency mandates in California, the EU, and China, using TikTok’s privacy policy as a case study. The findings show that laws, company practices, and user expectations do not always align. It then tests personalized privacy policies that show users their most relevant section first. The results show that legally compliant personalization with reordering does not significantly improve engagement, understanding, or cognitive load. The thesis further explores personalized privacy assistants. Acceptance of these assistants depends on trust, habit, design, accountability, and regional context. The conclusion? Personalization is not a magic fix. It may help, but only when law, technology, and user-centered design create meaningful control.