This paper discusses whether the law is up to regulate machine learning (”ML”) model-based decision-making in the context of the railways. We especially deal with the fairness and accountability of these models when exploited in the context of train traffic management (”TTM”). Railway sector-specific regulation, in their quality as network industry, hereby serves as a pilot. We show that, even where technological solutions are available, the law needs to keep up to support and accurately regulate the use of the technological solutions and we identify stumble points in this regard.

Fairness and accountability of machine learning models in railway market: Are applicable railway laws up to regulate them?

Oneto L.;
2019

Abstract

This paper discusses whether the law is up to regulate machine learning (”ML”) model-based decision-making in the context of the railways. We especially deal with the fairness and accountability of these models when exploited in the context of train traffic management (”TTM”). Railway sector-specific regulation, in their quality as network industry, hereby serves as a pilot. We show that, even where technological solutions are available, the law needs to keep up to support and accurately regulate the use of the technological solutions and we identify stumble points in this regard.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11567/1086656
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