User-based algorithmic auditing

Uri Y. Hacohen

doi:10.1515/til-2025-0012

Article

User-based algorithmic auditing

Uri Y. Hacohen

Published/Copyright: July 23, 2025

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From the journal Theoretical Inquiries in Law Volume 26 Issue 1

Abstract

In the artificial intelligence and cloud computing age, digital platforms like Meta, Google, and Amazon wield immense social, economic, and political power, shaping users’ daily lives. As these platforms gather vast amounts of user data and utilize sophisticated algorithms to personalize services, they also expose users to risks of bias and manipulation. Policymakers are seeking ways to hold platforms accountable, and algorithmic auditing is emerging as a key approach. However, existing regulations often rely on self-audits by the platforms themselves, leading to conflicts of interest. The shift towards third-party auditing is promising, but still falls short of resolving these conflicts. To address this challenge, this article introduces, typologizes, and explores a unique and underutilized approach to regulatory algorithmic oversight: “user-based algorithmic auditing.” According to this auditing approach, the platforms’ users lead the audit or assist external auditors in the process. User-based auditing is impartial and entirely independent of the audited platforms. User-based audits are also valuable for corroborating the information that the platforms provide in their self-auditing reports. The article explores regulatory frameworks, scrutinizes auditing approaches, and delves into the potential of user-based auditing to shape algorithmic oversight policies effectively.

^* Assistant Professor and Faculty Fellow at the Chief Justice Meir Shamgar Center for Digital Law and Innovation, The Buchmann Faculty of Law, Tel Aviv University. I would like to thank Professor Niva Elkin-Koren, Professor Anat Ben-David, Professor Michal Gal, and Professor Assaf Hamdani. I would also like to devote special thanks to the excellent team of the Theoretical Inquiries in Law (TIL) journal, and to Yonati Bonn Yavneh and Roni Berman for their wonderful research assistance and insightful conversations.

Published Online: 2025-07-23

Published in Print: 2025-06-26

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https://doi.org/10.1515/til-2025-0012