Justiça Algorítmica: Instrumentalização, Limites Conceituais e Desafios na Engenharia de Software
May 11, 2025 · Declared Dead · + Add venue
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Lucas Rodrigues Valença, Ronnie de Souza Santos
arXiv ID
2505.07132
Category
cs.SE: Software Engineering
Citations
0
Last Checked
5 months ago
Abstract
This article describes ongoing research with the aim of understanding the concept of justice in the field of software engineering, the factors that underlie the creation and instrumentalization of these concepts, and the limitations faced by software engineering when applying them. The expansion of the field of study called ``algorithmic justice'' fundamentally consists in the creation of mechanisms and procedures based on mathematical and formal procedures to conceptualize, evaluate and reduce biases and discrimination caused by algorithms. We conducted a systematic mapping in the context of justice in software engineering, comprising the metrics and definitions of algorithmic justice, as well as the procedures and techniques for fairer decision-making systems. We propose a discussion about the limitations that arise due to the understanding of justice as an attribute of software and the result of decision-making, as well as the influence that the field suffers from the construction of computational thinking, which is constantly developed around abstractions. Finally, we reflect on potential paths that could help us move beyond the limits of algorithmic justice.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
📜 Similar Papers
In the same crypt — Software Engineering
R.I.P.
👻
Ghosted
R.I.P.
👻
Ghosted
Microservices: yesterday, today, and tomorrow
📚
📚
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
👻
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
👻
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
👻
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way — 👻 Ghosted
R.I.P.
👻
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
👻
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
👻
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
👻
Ghosted