  Online Automated Privacy Policy Generators (APPGs) are tools used by app
developers to quickly create app privacy policies which are required by privacy
regulations to be incorporated to each mobile app. The creation of these tools
brings convenience to app developers; however, the quality of these tools puts
developers and stakeholders at legal risk. In this paper, we conduct an
empirical study to assess the quality of online APPGs. We analyze the
completeness of privacy policies, determine what categories and items should be
covered in a complete privacy policy, and conduct APPG assessment with
boilerplate apps. The results of assessment show that due to the lack of static
or dynamic analysis of app's behavior, developers may encounter two types of
issues caused by APPGs. First, the generated policies could be incomplete
because they do not cover all the essential items required by a privacy policy.
Second, some generated privacy policies contain unnecessary personal
information collection or arbitrary commitments inconsistent with user input.
Ultimately, the defects of APPGs may potentially lead to serious legal issues.
We hope that the results and insights developed in this paper can motivate the
healthy and ethical development of APPGs towards generating a more complete,
accurate, and robust privacy policy.
