Treffer: FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency

Title:
FAT Forensics: A Python Toolbox for Algorithmic Fairness, Accountability and Transparency
Publication Year:
2019
Collection:
Computer Science
Statistics
Document Type:
Report Working Paper
DOI:
10.1016/j.simpa.2022.100406
Accession Number:
edsarx.1909.05167
Database:
arXiv

Weitere Informationen

Today, artificial intelligence systems driven by machine learning algorithms can be in a position to take important, and sometimes legally binding, decisions about our everyday lives. In many cases, however, these systems and their actions are neither regulated nor certified. To help counter the potential harm that such algorithms can cause we developed an open source toolbox that can analyse selected fairness, accountability and transparency aspects of the machine learning process: data (and their features), models and predictions, allowing to automatically and objectively report them to relevant stakeholders. In this paper we describe the design, scope, usage and impact of this Python package, which is published under the 3-Clause BSD open source licence.
Comment: Homepage: https://fat-forensics.org/ Source Code: https://github.com/fat-forensics/fat-forensics/