A Hate Speech Moderated Chat Application: Use Case for GDPR and DSA Compliance
Jan Fillies, Theodoros Mitsikas, Ralph Sch\"afermeier, Adrian Paschke

TL;DR
This paper introduces a GDPR-compliant chat application that uses AI and legal reasoning to improve hate speech detection and moderation, ensuring privacy and ethical considerations are integrated.
Contribution
It presents a novel approach combining legal and ethical reasoning with AI technologies like GPT-3.5 and Prova for explainable and compliant hate speech moderation.
Findings
Demonstrates a platform protecting minors from harmful content.
Provides counter hate speech tailored to user attributes.
Lays groundwork for future DSA compliance in online moderation.
Abstract
The detection of hate speech or toxic content online is a complex and sensitive issue. While the identification itself is highly dependent on the context of the situation, sensitive personal attributes such as age, language, and nationality are rarely available due to privacy concerns. Additionally, platforms struggle with a wide range of local jurisdictions regarding online hate speech and the evaluation of content based on their internal ethical norms. This research presents a novel approach that demonstrates a GDPR-compliant application capable of implementing legal and ethical reasoning into the content moderation process. The application increases the explainability of moderation decisions by utilizing user information. Two use cases fundamental to online communication are presented and implemented using technologies such as GPT-3.5, Solid Pods, and the rule language Prova. The…
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Taxonomy
TopicsHate Speech and Cyberbullying Detection · Freedom of Expression and Defamation · Privacy, Security, and Data Protection
