INTERNATIONAL JOURNAL OF TOURISM, TRAVEL AND HOSPITALITY LAW 1. ITALIAN MODELS FOR REGULATING THE USE OF ALGORITHMS IN SCHEDULED AIR TRANSPORT In 2022 and in the first half of 2023, strong tensions arose in the air transport market, with significant price increases and marked fluctuations, with no comprehensible reasons. Although the exact determination of the reasons for such behaviour on the part of the airlines has remained unsubstantiated, there is a widespread belief that they were caused by the systematic use of highly sophisticated mathematical tools for calculating the charge, with algorithms2. Well - known in the economic literature3, the subject had no reflection on the legal debate, at least in Italy, until August 2023, whereas there have been analyses in other areas, for instance in labour relations4. To tell the truth, as has been objected to in some public speeches by airline executives, the legislator was moved by suspicion, but not by the demonstration of the distorting influence of these models on the calculation of fares and, above all, by the unproven conviction that automated intervention could establish in advance the economic capacity and willingness to spend of the traveller, thus conditioning the selection of the requested compensation to his detriment. On the legal side, the first question posed by algorithms is their knowability5, as pointed out in the Italian debate6, since, it has been said, "it 2 See: L. M. Lopucki, Algorithmic entities, in Washington University law review, 2018, 887 ff. 3 V.: K. Koelker - K. Lutjens, Using genetic algorithms to solve large - scale airline network planning problems, in Transp. Research procedia, 2015, 900 ff.; J. Betancourt - A. Hortacsu - A. Oery - K. Willliams, Dynamic price competition: theory and evidence from airline markets, in Nber working papers, 2022, no. 30347, 5 ff.; A. Karbassi Yazdi - M. Amin Kaviani - T. - Hanne - A. Ramos, A binary differential evolution algorithm for airline revenue management: a case study, in Soft computing, 2020, 24, 5 ff. 4 See: J. Prassl, Humans a service. The promise and the perils of work in the gig economy, Oxford University press, Oxford, 2017, 65 ff.; A. Rosenblat, Uberland: how algorithms are rewriting the rules of work, Los Angeles, 2018, 37 ff.; C. Salazar, Rights and algorithms: the gig economy and the “Foodora case”, between judges and legislators, in Liber amicorum per Pasquale Costanzo, 2019, 179 ff. 5 See: J. Gorelli Hernandez, Algoritmos y transparencia: pueden mentir los numeros? Los derechos de informaciòn, in Trabajo y derecho, 2002, 1 ff. (from the abstract); A. Höchling - M. C. Wehener - Lyth, Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision making in the context of human resources recruitment and human resources development, in Bus. res., 2020, 13, 795 ff. 6 See: E. Gragnoli, The employment relationship, automatic decisions and their limits. The regulation of non - understandable phenomena, report to the International Conference in Logrono Ethicomp
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