Ethics is a field of study that analyses practices, their principles, customs, and habits. The Grand Research Challenges in Human-Computer Interaction in Brazil (GranDIHC-BR) between 2012 and 2022 highlighted the relevance of the topic Ethics in the context of Human Values. Aligned with that, we claim that computational techniques are not neutral and, therefore, ethical analysis is essential to the design of applications as well as theoretical or conceptual research. The goal of this work is to provide an understanding on how researchers have addressed the ethical aspects by analyzing the publications of the IHC-BR: the Brazilian Symposium on Human Factors in Computing Systems, the leading conference dedicated to HCI in Brazil. Thus, we conducted a Systematic Literature Review guided by the main research question: how does ethics permeate research published between 2006 and 2021? As a result, although less than 5% of the papers discussed ethical content, we observed a significant growth in ethical aspects over the years, both associated with the meta-research and its application.

A sociedade é influenciada por novas tecnologias, culminando em questões éticas inéditas. Como habilitar a proteção de dados em uma época de algoritmos que utilizam os mesmos sabe-se lá para quê? O governo brasileiro, motivado por esta questão, sancionou uma legislação abrangente para proteção de dados. Na sua redação fica nítida a preocupação com a transparência. Em vista disso, quais serão as questões tecnológicas associadas com a transparência em uma lei dedicada à privacidade?

Scientific environments are known for being highly dynamic, subject to rapid evolution and demanding constant renewal and update. Additionally, science is a highly social arena. However, interpersonal collaboration and knowledge flow in scientific environments are usually more restricted. Collaboration is intense among small groups of people working on specific problems within a domain, but low between groups. As user profiling has been extensively used as a basis for recommendation, personalization and matchmaking systems, a better profile identification can improve interaction levels among researchers belonging to the same domain but working in different laboratories. Profiles may be constructed in two ways: either through explicit declaration by the user or through the observation of users’ actions. Many systems employ one approach to the exclusion of the other. We contend that a combined approach will yield better results, especially on scientific scenario, providing a mix of declared and inferred information. In this article, we present inference-based profiles in scientific environments (i-ProSE), an integrated system that dynamically creates and maintains scientific user profiles based both on declared information and on observed behaviour. The i-ProSE can be used to locate experts, deliver content, build communities, find collaborators for long-term projects or detect instantaneous opportunities for informal collaboration, which is presented with a short study case.