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@inproceedings{Mendez.Kampik.Aler.Dignum-2024-SCAI,
    author = {Mendez, Julian Alfredo and Kampik, Timotheus and Aler Tubella, Andrea and Dignum, Virginia},
    title = { {A Clearer View on Fairness: Visual and Formal Representation for Comparative Analysis} },
    booktitle = {14th Scandinavian Conference on Artificial Intelligence, SCAI 2024},
    year = {2024},
    month = {June},
    pages = {112--120},
    editor = {Westphal, Florian and Peretz-Andersson, Einav and Riveiro, Maria and Bach, Kerstin and Heintz, Fredrik},
    organization = {Swedish Artificial Intelligence Society},
    doi = {10.3384/ecp208013},
    url = {https://ecp.ep.liu.se/index.php/sais/article/view/1005/913},
    note = { \url{https://doi.org/10.3384/ecp208013} },
    abstract = {
        The opaque nature of machine learning systems has raised concerns about whether these systems can guarantee fairness. Furthermore, ensuring fair decision making requires the consideration of multiple perspectives on fairness.
        At the moment, there is no agreement on the definitions of fairness, achieving shared interpretations is difficult, and there is no unified formal language to describe them. Current definitions are implicit in the operationalization of systems, making their comparison difficult.
        In this paper, we propose a framework for specifying formal representations of fairness that allows instantiating, visualizing, and comparing different interpretations of fairness. Our framework provides a meta-model for comparative analysis. We present several examples that consider different definitions of fairness, as well as an open-source implementation that uses the object-oriented functional language Soda.
    },
    keywords = {Responsible artificial intelligence, Ethics in artificial intelligence, Formal representation of fairness}
}