ACROCPoLis: A Descriptive Framework for Making Sense of Fairness

Andrea Aler Tubella, Dimitri Coelho Mollo, Adam Dahlgren Lindström, Hannah Devinney, Virginia Dignum, Petter Ericson, Anna Jonsson, Timotheus Kampik, Tom Lenaerts, Julian Alfredo Mendez, Juan Carlos Nieves

Research output: Chapter in Book/Report/Conference proceedingConference paper


Fairness is central to the ethical and responsible development and use of AI systems, with a large number of frameworks and formal notions of algorithmic fairness being available. However, many of the fairness solutions proposed revolve around technical considerations and not the needs of and consequences for the most impacted communities. We therefore want to take the focus away from definitions and allow for the inclusion of societal and relational aspects to represent how the effects of AI systems impact and are experienced by individuals and social groups. In this paper, we do this by means of proposing the ACROCPoLis framework to represent allocation processes with a modeling emphasis on fairness aspects. The framework provides a shared vocabulary in which the factors relevant to fairness assessments for different situations and procedures are made explicit, as well as their interrelationships. This enables us to compare analogous situations, to highlight the differences in dissimilar situations, and to capture differing interpretations of the same situation by different stakeholders.

Original languageEnglish
Title of host publicationProceedings of the 6th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023
PublisherAssociation for Computing Machinery
Number of pages12
ISBN (Electronic)9781450372527
Publication statusPublished - 12 Jun 2023
Event6th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023 - Chicago, United States
Duration: 12 Jun 202315 Jun 2023

Publication series

NameACM International Conference Proceeding Series


Conference6th ACM Conference on Fairness, Accountability, and Transparency, FAccT 2023
Country/TerritoryUnited States

Bibliographical note

Funding Information:
We would like to thank the anonymous reviewers for their thoughtful feedback, which has led us to substantially expand the discussion of ACROCPoLis in this paper.

Publisher Copyright:
© 2023 Owner/Author.

Copyright 2023 Elsevier B.V., All rights reserved.


  • Algorithmic fairness
  • responsible AI
  • social impact of AI
  • socio-technical processes

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