CLAUDETTE: an Automated Detector of Potentially Unfair Clauses in Online Terms of Service
Marco Lippi, Przemyslaw Palka, Giuseppe Contissa, Francesca Lagioia, Hans-Wolfgang Micklitz, Giovanni Sartor, Paolo Torroni
arXiv:1805.01217v2209 citations
Originality Synthesis-oriented
AI Analysis
This addresses the issue of unfair clauses in online terms of service for consumers and legal professionals, but it appears incremental as it applies existing ML methods to a new domain.
The paper tackled the problem of automatically detecting potentially unfair clauses in online terms of service using machine learning, with results indicating the system could serve as a valuable tool for lawyers and consumers.
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.