Inteligência artificial e decisões: percepção dos usuários sobre os sistemas de recomendação

Abstract

This dissertation aims to investigate whether technology users understand that recommender systems can influence their decisions. The advancement of science and the development of technology have changed the habits of society and revolutionized communication, relationships, consumption and obtaining information. Digital platforms like Netflix and Youtube, for example, use algorithms, which collect user data to recommend fully personalized content. However, even if the recommendations are intended to help the user to locate services or products that are of interest to them and to avoid overloading the selection process, they can be considered nudges or “pushes”. Furthermore, subtle changes in the information that people are exposed to can transform their behaviors and, consequently, choices can become just a series of reactions to invisible nudges and nudges. Considering that recommender systems are present on all websites, digital platforms and applications, the challenge is to present people, in a transparent and understandable way, the influence of these systems on the choices made daily. In addition to elucidating data security, privacy and information mediation. Given the fact that each choice made represents the exclusion of so many others and that recommender systems are present on all websites, platforms and applications, it becomes important to promote the user with the possibility of understanding the impact that personalized recommendations can have. This is because the problem is not in the recommendations, but in the absence of clear and understandable information intended for the user