Fairness and accountability of ML in railway market: are applicable railway laws up to regulate them?

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 tra c management (" TTM"). Railway sector-speci c regulation, in their quality as network industry, hereby serves as a pilot. We show that, even where techno-logical 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.