… to assess the category and the level of unfairness of the clause. MANNs have been widely
… trained just like any other deep network. In the context of consumer contracts, we define the …

… The basic idea behind MANNs is to combine the successful learning strategies developed
in the machine learning literature for inference with a memory component that can be read …

… This is a standard procedure in machine learning, making it possible to assess our system’s
generalization capabilities. The results of the experiments show that CLAUDETTE correctly …

… the problem of explaining unfairness in consumer contracts and pave the way to …
machinelearning approaches in the consumer law domain, and the state of the art of …

… consumers of their contractual rights and obligations. To showcase the opportunities and
challenges of using language models to read consumer contracts, … biases in machine learning. …

… of ToS unfairness. In support of such a definition, we also define a novel unfairness measure,
… 3 of the Directive 93/13 on Unfair Terms in Consumer Contracts, a contractual term is unfair …

… This article focuses on on the components that use machine learning … Although their degrees
of unfairness vary, the risk of … consumer contracts among the set of documents harvested. …

… Credit discrimination undermines consumer financial autonomy and distorts market … Al
discrimination are traceable to indirect, proxy discrimination stemming from the machine learning …

… concerns about contractual bias and discrimination. And even … on the new Restatement of
Consumer Contracts. One central issue … Smart readers are built on machine learning language …

… corpus and a machine learning classifier for English, we … corpus and training a novel machine
learning system for each … rationales as explanations for the unfairness of a clause, also in …