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CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service

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arxiv 1805.01217 v2 pith:6DZMIBNA submitted 2018-05-03 cs.AI cs.CY

Marco Lippi , Przemyslaw Palka , Giuseppe Contissa , Francesca Lagioia , Hans-Wolfgang Micklitz , Giovanni Sartor , Paolo Torroni This is my paper · ORCID
classification cs.AIcs.CY
keywords clausespotentiallyunfairservicetermsalikeautomatedautomatically
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Terms of service of on-line platforms too often contain clauses that are potentially unfair to the consumer. We present an experimental study where machine learning is employed to automatically detect such potentially unfair clauses. Results show that the proposed system could provide a valuable tool for lawyers and consumers alike.

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Cited by 1 Pith paper

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  1. Predicting potentially abusive clauses in Chilean terms of services with natural language processing

    cs.CL 2025-02 conditional novelty 7.0 of 10

    The authors create the first Spanish-language multi-label dataset of potentially abusive clauses in Chilean terms of service and benchmark fine-tuned and few-shot language models on it.

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