---
_id: '62033'
abstract:
- lang: eng
text: AbstractThe literature addressing bias and
fairness in AI models (fair-AI) is growing at a fast
pace, making it difficult for novel researchers and practitioners to have a bird’s-eye
view picture of the field. In particular, many policy initiatives, standards,
and best practices in fair-AI have been proposed for setting principles, procedures,
and knowledge bases to guide and operationalize the management of bias and fairness.
The first objective of this paper is to concisely survey the state-of-the-art
of fair-AI methods and resources, and the main policies on bias in AI, with the
aim of providing such a bird’s-eye guidance for both researchers and practitioners.
The second objective of the paper is to contribute to the policy advice and best
practices state-of-the-art by leveraging from the results of the NoBIAS research
project. We present and discuss a few relevant topics organized around the NoBIAS
architecture, which is made up of a Legal Layer, focusing on the European Union
context, and a Bias Management Layer, focusing on understanding, mitigating, and
accounting for bias.
article_number: '31'
author:
- first_name: Jose M.
full_name: Alvarez, Jose M.
last_name: Alvarez
- first_name: Alejandra Bringas
full_name: Colmenarejo, Alejandra Bringas
last_name: Colmenarejo
- first_name: Alaa
full_name: Elobaid, Alaa
last_name: Elobaid
- first_name: Simone
full_name: Fabbrizzi, Simone
last_name: Fabbrizzi
- first_name: Miriam
full_name: Fahimi, Miriam
id: '118059'
last_name: Fahimi
orcid: 0000-0002-0619-3160
- first_name: Antonio
full_name: Ferrara, Antonio
last_name: Ferrara
- first_name: Siamak
full_name: Ghodsi, Siamak
last_name: Ghodsi
- first_name: Carlos
full_name: Mougan, Carlos
last_name: Mougan
- first_name: Ioanna
full_name: Papageorgiou, Ioanna
last_name: Papageorgiou
- first_name: Paula
full_name: Reyero, Paula
last_name: Reyero
- first_name: Mayra
full_name: Russo, Mayra
last_name: Russo
- first_name: Kristen M.
full_name: Scott, Kristen M.
last_name: Scott
- first_name: Laura
full_name: State, Laura
last_name: State
- first_name: Xuan
full_name: Zhao, Xuan
last_name: Zhao
- first_name: Salvatore
full_name: Ruggieri, Salvatore
last_name: Ruggieri
citation:
ama: Alvarez JM, Colmenarejo AB, Elobaid A, et al. Policy advice and best practices
on bias and fairness in AI. Ethics and Information Technology. 2024;26(2).
doi:10.1007/s10676-024-09746-w
apa: Alvarez, J. M., Colmenarejo, A. B., Elobaid, A., Fabbrizzi, S., Fahimi, M.,
Ferrara, A., Ghodsi, S., Mougan, C., Papageorgiou, I., Reyero, P., Russo, M.,
Scott, K. M., State, L., Zhao, X., & Ruggieri, S. (2024). Policy advice and
best practices on bias and fairness in AI. Ethics and Information Technology,
26(2), Article 31. https://doi.org/10.1007/s10676-024-09746-w
bibtex: '@article{Alvarez_Colmenarejo_Elobaid_Fabbrizzi_Fahimi_Ferrara_Ghodsi_Mougan_Papageorgiou_Reyero_et
al._2024, title={Policy advice and best practices on bias and fairness in AI},
volume={26}, DOI={10.1007/s10676-024-09746-w},
number={231}, journal={Ethics and Information Technology}, publisher={Springer
Science and Business Media LLC}, author={Alvarez, Jose M. and Colmenarejo, Alejandra
Bringas and Elobaid, Alaa and Fabbrizzi, Simone and Fahimi, Miriam and Ferrara,
Antonio and Ghodsi, Siamak and Mougan, Carlos and Papageorgiou, Ioanna and Reyero,
Paula and et al.}, year={2024} }'
chicago: Alvarez, Jose M., Alejandra Bringas Colmenarejo, Alaa Elobaid, Simone Fabbrizzi,
Miriam Fahimi, Antonio Ferrara, Siamak Ghodsi, et al. “Policy Advice and Best
Practices on Bias and Fairness in AI.” Ethics and Information Technology
26, no. 2 (2024). https://doi.org/10.1007/s10676-024-09746-w.
ieee: 'J. M. Alvarez et al., “Policy advice and best practices on bias and
fairness in AI,” Ethics and Information Technology, vol. 26, no. 2, Art.
no. 31, 2024, doi: 10.1007/s10676-024-09746-w.'
mla: Alvarez, Jose M., et al. “Policy Advice and Best Practices on Bias and Fairness
in AI.” Ethics and Information Technology, vol. 26, no. 2, 31, Springer
Science and Business Media LLC, 2024, doi:10.1007/s10676-024-09746-w.
short: J.M. Alvarez, A.B. Colmenarejo, A. Elobaid, S. Fabbrizzi, M. Fahimi, A. Ferrara,
S. Ghodsi, C. Mougan, I. Papageorgiou, P. Reyero, M. Russo, K.M. Scott, L. State,
X. Zhao, S. Ruggieri, Ethics and Information Technology 26 (2024).
date_created: 2025-10-31T15:17:11Z
date_updated: 2025-11-18T09:56:30Z
doi: 10.1007/s10676-024-09746-w
extern: '1'
intvolume: ' 26'
issue: '2'
language:
- iso: eng
publication: Ethics and Information Technology
publication_identifier:
issn:
- 1388-1957
- 1572-8439
publication_status: published
publisher: Springer Science and Business Media LLC
status: public
title: Policy advice and best practices on bias and fairness in AI
type: journal_article
user_id: '118059'
volume: 26
year: '2024'
...