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Among the seven key requirements to achieve trustworthy AI proposed by the High-Level Expert Group on Artificial Intelligence (AI-HLEG) established by the European Commission, the fifth requirement (“Diversity, non-discrimination and fairness”) declares: “In order to achieve Trustworthy AI, we must enable inclusion and diversity throughout the entire AI system’s life cycle. [...] This requirement is closely linked with the principle of fairness”. In this paper, we try to shed light on how closely these two distinct concepts, diversity and fairness, may be treated by focusing on information access systems and ranking literature. © 2023 Copyright for this paper by its authors.

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Abstract
This paper analyses the causal relationship between external events and sports content TV audiences. To accomplish this, we explored external data related to sports TV audience behaviour within a specific time frame and applied a Granger causality analysis to evaluate the effect of external events on both TV clients' volume and viewing times. Compared to regression studies, Granger causality analysis is essential in this research as it provides a more comprehensive and accurate understanding of the causal relationship between external events and sports TV viewership. The study results demonstrate a significant impact of external events on the TV clients' volume and viewing times. External events such as the type of tournament, match popularity, interest and home team effect proved to be the most informative about the audiences. The findings of this study can assist TV distributors in making informed decisions about promoting sports broadcasts.

Abstract