Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
34th (2020)
Session ID : 3N5-OS-11b-02
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Categorization based on the Ambiguity and Amount of Information Associated with a Named Entity of Privacy Policy
A Study on Transparency in Privacy Policies
*Sachiko KANAMORIHirotsune SATONaoya TABATARyo NOJIMA
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Abstract

Service providers that collect personal data from users are required to provide a privacy policy and obtain user consent in advance. However, researchers have identified that users generally do not read privacy policies or such policies are difficult to understand. We are developing a support tool to assist users to understand privacy policies using a machine learning method. In this paper, we report the categorization results of website privacy policies that are currently provided by domestic and international companies. The categorization is based on the ambiguity and amount of information in privacy policies. Based on the results, we discuss the types of privacy policies that are appropriate for our support tool as well as transparency in privacy policies.

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© 2020 The Japanese Society for Artificial Intelligence
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