Comparing Privacy Policies of Government Agencies and Companies: A Study using Machine-learning-based Privacy Policy Analysis Tools

Razieh Zaeem, K. Barber

Abstract

Companies and government agencies are motivated by different missions when collecting and using Personally Identifiable Information (PII). Companies have strong incentives to monetize such information, whereas government agencies are generally not-for-profit. Besides this difference in missions, they are subject to distinct regulations that govern their collection and use of PII. Yet, do privacy policies of companies and government agencies reflect these differences and distinctions? In this paper, we take advantage of two of the most recent machine-learning-based privacy policy analysis tools, Polisis and PrivacyCheck, and five corpora of over 800 privacy policies to answer this question. We discover that government agencies are considerably better in protecting (or not collecting for that matter) sensitive financial information, Social Security Numbers, and user location. On the other hand, many of them fail to directly address children’s privacy or describe security measures taken to protect user data. Furthermore, we observe that E.U government agencies perform well, with respect to notifying users of policy change, giving users the right to edit/delete their data, and limiting data retention. Our work confirms the common-sense understanding that government agencies collect less personal information than companies, but discovers nuances, as listed above, along the way. Finally, we make our data publicly available, enhancing reproducibility and enabling future analyses.

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Paper Citation


in Harvard Style

Zaeem R. and Barber K. (2021). Comparing Privacy Policies of Government Agencies and Companies: A Study using Machine-learning-based Privacy Policy Analysis Tools.In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-484-8, pages 29-40. DOI: 10.5220/0010180700290040


in Bibtex Style

@conference{icaart21,
author={Razieh Zaeem and K. Barber},
title={Comparing Privacy Policies of Government Agencies and Companies: A Study using Machine-learning-based Privacy Policy Analysis Tools},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2021},
pages={29-40},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010180700290040},
isbn={978-989-758-484-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Comparing Privacy Policies of Government Agencies and Companies: A Study using Machine-learning-based Privacy Policy Analysis Tools
SN - 978-989-758-484-8
AU - Zaeem R.
AU - Barber K.
PY - 2021
SP - 29
EP - 40
DO - 10.5220/0010180700290040