As Artificial Intelligent systems become more widely used in our daily lives, it is crucial to ensure not only their accuracy, but also their fairness. In this study, I focused on assessing fairness and the possible presence of bias in systems that address the task of Speech Emotion Recognition (SER). Speech Emotion Recognition is the process of automatically detecting and understanding the emotional content conveyed through spoken language. It relies on analyzing acoustic features of the speech signal, independently of the actual linguistic content. The experiments were conducted using the only two datasets available in Italian for this task, Emozionalmente and EMOVO.