This Special Issue aims at collecting contributions that focus on the
various dimensions of algorithmic fairness, both from foundational and
application perspectives. We therefore target works ranging from novel
theoretical frameworks to model fairness (and tackle unfairness) in the
general case, to the formalization of fairness issues in different
applications (from decision making, operations research, resource
allocation and policy making) using empirical approaches. Contributions
dealing with different data-types, e.g., tabular, sequential, textual and,
other complex data such as graphs, are particularly welcome.
Guest editors:
Prof. Miguel Couceiro, Université de Lorraine, CNRS, LORIA, F-54000 Nancy,
France. Email: miguel.couceiro@loria.fr
Luis Galárraga, Researcher, INRIA/IRISA, 263 Avenue du Général Leclerc,
Building 12 F, Campus de Beaulieu, 35042 Rennes, France. Email:
luis.galarraga@inria.fr
Special issue information:
Motivation
Algorithmic decisions are nowadays being employed on a daily basis. They
are carried out by mathematical models trained using machine learning
techniques on data collected from past experiences. Well-known examples
include decision support systems for loan grants, terrorism detection,
prediction of criminal recidivism, and many other activities with social
and economic impact on society. While ML-based decision systems generally
attain good performance, they can be complex and opaque, not to mention
that they are not infallible. This lack of transparency, together with the
increasing evidence of biases and unfair outcomes in those systems, has
raised several concerns within the scientific and legislative realms.
Most of the notions of fairness focus on the outcomes of the decision
process, and they are inspired by several anti-discrimination efforts that
aim to ensure that unprivileged groups (e.g. racial minorities) are treated
fairly. As such, the problem of improving algorithmic fairness can be
formulated as an optimisation one. However, certain dimensions of fairness
do not fit into this setting, e.g., fairness through unawareness and
counterfactuals. This raises a number of challenges for theorists,
researchers, and practitioners.
This brings us to the underlying motivation of this Special Issue that aims
at collecting contributions that focus on the various dimensions of
algorithmic fairness, both from foundational and application perspectives.
We therefore target works ranging from novel theoretical frameworks to
model fairness (and tackle unfairness) in the general case, to the
formalization of fairness issues in different applications (from decision
making, operations research, resource allocation and policy making) using
empirical approaches. Contributions dealing with different data-types,
e.g., tabular, sequential, textual and, other complex data such as graphs,
are particularly welcome.
Contents:
We welcome contributions (i) in the form of state-of-the-art original
research papers, (ii) in the form of position papers that establish bridges
between different frameworks, and (iii) discussion papers that highlight
emerging trends in the topics outlined above. New methodologies,
algorithmic tools, and implementations are also in the scope of this
Special Issue.
Manuscript submission information:
You are invited to submit your manuscript at any time before the submission
deadline of 1 March 2022. For any inquiries about the appropriateness of
contribution topics, please contact Miguel Couceiro, University of
Lorraine, CNRS, Loria, France (miguel.couceiro@loria.fr) or Luis Galárraga,
INRIA Rennes, France (luis.galarraga@inria.fr).
The journal's submission platform (Editorial Manager) is now available for
receiving submissions to this Special Issue. Please refer to the Guide for
Authors to prepare your manuscript, and select the article type of "VSI:
Fair decisions" when submitting your manuscript online. Both the Guide for
Authors and the submission portal could be found on the Journal Homepage
here:
https://www.journals.elsevier.com/euro-journal-on-decision-processes
Keywords:
Explainability, Fairness of decision, accountability of decisions, trust in
decision system
Why publish in this Special Issue?
Special Issue articles are published together on ScienceDirect, making it
incredibly easy for other researchers to discover your work.
Special content articles are downloaded on ScienceDirect twice as often
within the first 24 months than articles published in regular issues.
Special content articles attract 20% more citations in the first 24 months
than articles published in regular issues.
All articles in this special issue will be reviewed by no fewer than two
independent experts to ensure the quality, originality and novelty of the
work published.
Learn more about the benefits of publishing in a special issue:
https://www.elsevier.com/authors/submit-your-paper/special-issues
Interested in becoming a guest editor? Discover the benefits of guest
editing a special issue and the valuable contribution that you can make to
your field: https://www.elsevier.com/editors/role-of-an-editor/guest-editors
--
Dr Sarah Fores, FORS
Manager of EURO
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