Website privacy policies often contain ambiguous language that undermines the purpose and value of privacy notices for site users. This paper compares the impact of different regulatory models on the ambiguity of privacy policies in multiple online sectors. First, the paper develops a theory of vague and ambiguous terms. Next, the paper develops a scoring method to compare the relative vagueness of different privacy policies. Then the theory and scoring are applied using natural language processing to rate a set of policies. The ratings are compared against two benchmarks to show whether government-mandated privacy disclosures result in notices that are less ambiguous than those emerging from the market. The methodology and technical tools can provide companies with mechanisms to improve drafting, enable regulators to easily identify poor privacy policies, and empower regulators to more effectively target enforcement actions.