Algorithmic bias: an undergraduate thesis systematically maps the ethical challenges
Amanda Jeniffer Pereira Nobre and Ana Carolina Rodrigues Leite defended at FCTE/UnB an undergraduate thesis running a systematic literature mapping on the ethical challenges tied to bias in AI algorithms.
Brasília, July 21, 2025
When an algorithm decides who enters a hiring pipeline, whose credit gets approved, or who receives priority medical care, the bias woven into its training becomes a silent instrument of exclusion. The undergraduate thesis defended in July 2025 by Amanda Jeniffer Pereira Nobre and Ana Carolina Rodrigues Leite maps the world literature in search of the contours of this conversation — under the advising of Prof. André Luiz Peron Martins Lanna .
The work is a systematic literature mapping on ethical challenges tied to bias in AI systems. Instead of picking one case and drilling down, the duo does the opposite: it covers what the community has already discussed, organizes application areas (health, security, labor market), identifies recurring patterns, and highlights methodological gaps. It is a librarian’s work in the best sense — giving the reader a map to orient before entering the forest.
By tying AI and machine learning with ethical concerns, the thesis contributes to an agenda the Brazilian community must develop with urgency: how to identify bias, how to hold automated decisions accountable, and how to train professionals capable of recognizing risk before the machine runs.
The full text — written in Portuguese — is available at the UnB Undergraduate Theses Digital Library.
About CEDIS: The Center for Studies, Development, and Innovation in Software (CEDIS), linked to the University of Brasília, researches and develops innovative software solutions.