Explainable AI for Entertainment: Issues on Video on Demand Platforms

With the proliferation of Artificial Intelligence-based systems, several questions arise involving ethical principles. In addition, the human-centered approach takes the focus on the user experience with these systems and studies user needs. A growing issue is the relationship between the transparency of these systems and the trust of users, since most systems are considered black-boxes. In this scenario, the Explainable Artificial Intelligence (XAI) emerges, with the proposal to explain the rationale of the decision making of the algorithms. XAI then starts to gain space in systems that involve high risk, such as health. Our research aims to discuss the importance of transparency to improve the user experience with recommendation mechanisms for entertainment, such as Video on Demand (VoD) platforms. In addition, we intent to raise the adjacent consequences of including XAI, such as improving the control and trust of VoD platforms. For this, we conducted an exploratory research method named Directed Storytelling. The study was conducted with thirty-one participants, all users of VoD platforms, regardless of time and frequency of use of this kind of systems. We note that people understand that there is an automated mechanism making recommendations for content in a personalized way for them, based on their browsing history, but the rules are not explicit. Thus, many users are suspicious of being manipulated by the system’s recommendations and resort to external recommendations, such as tips from third parties or Internet searches through specialized channels.