  Artificial Intelligence is not a new subject, and business, industry and
public sectors have used it in different ways and contexts and considering
multiple concerns. This work reviewed research papers published in ACM Digital
Library and IEEE Xplore conference proceedings in the last two years supported
by fundamental concepts of Natural Language Processing (NLP) and Text Mining
(TM). The objective was to capture insights regarding data privacy, ethics,
interpretability, explainability, trustworthiness, and fairness in the public
sector. The methodology has saved analysis time and could retrieve papers
containing relevant information. The results showed that fairness was the most
frequent concern. The least prominent topic was data privacy (although embedded
in most articles), while the most prominent was trustworthiness. Finally,
gathering helpful insights about those concerns regarding A.I. applications in
the public sector was also possible.
