Why am I seeing this: Democratizing End User Auditing for Online Content Recommendations

TL;DR

This paper introduces an interactive sandbox tool that enables users to test and understand how online recommendation algorithms respond to different user attributes, promoting transparency and accountability.

Contribution

It presents a novel interactive sandbox approach with synthetic personas to empower end users to audit personalized content recommendations.

Findings

User study shows high usability and usefulness

Effective in enabling end-user auditing

Improves understanding of recommendation systems

Abstract

Personalized recommendation systems tailor content based on user attributes, which are either provided or inferred from private data. Research suggests that users often hypothesize about reasons behind contents they encounter (e.g., "I see this jewelry ad because I am a woman"), but they lack the means to confirm these hypotheses due to the opaqueness of these systems. This hinders informed decision-making about privacy and system use and contributes to the lack of algorithmic accountability. To address these challenges, we introduce a new interactive sandbox approach. This approach creates sets of synthetic user personas and corresponding personal data that embody realistic variations in personal attributes, allowing users to test their hypotheses by observing how a website's algorithms respond to these personas. We tested the sandbox in the context of targeted advertisement. Our user study demonstrates its usability, usefulness, and effectiveness in empowering end-user auditing in a case study of targeting ads.