[AISWorld] Special session on explainability and fairness in decision support, at IDEAL 2024

[Raciel Yera Toledo]

Special session on explainability and fairness in decision support
The 25th International Conference on Intelligent Data Engineering and
Automated Learning
Valencia, Spain. November 20-22, 2024. Hybrid conference.

The International Conference on Intelligent Data Engineering and Automated
Learning (IDEAL) is an annual international conference dedicated to
emerging and challenging topics in intelligent data analytics and
associated learning systems and paradigms. Following the recent successful
events: IDEAL2023 in Évora, IDEAL2022 in Manchester (hybrid), IDEAL2021
(virtual), IDEAL2020 in Guimarães (virtual), IDEAL2019 in Manchester, and
IDEAL 2018 in Madrid, the 25th edition, IDEAL2024 will be taking place in
Valencia (European Green Capital), Spain.

Scope
Explainability in decision support systems is essential for fostering trust
and transparency in algorithmic/AI-driven decision processes. By making
complex models understandable, users can see the rationale behind
decisions, ensuring accountability and facilitating better-informed
choices. This is particularly crucial in high-stakes areas like healthcare,
finance, and criminal justice, where the consequences of decisions can
significantly impact individuals and society. Explainability also aids in
identifying and mitigating biases within models, promoting fairness and
ethical AI use. Overall, enhancing explainability helps bridge the gap
between advanced technology and human users, ensuring that decision support
systems are both effective and reliable.
In a different direction, fairness in decision support systems ensures that
algorithmic/AI-driven decisions do not perpetuate or amplify biases,
promoting equality and justice. It involves developing and implementing
algorithms that treat all individuals and groups equitably. Ensuring
fairness is crucial in sectors like hiring, lending, and law enforcement,
where biased decisions can have severe social and economic consequences.
Addressing fairness involves continuous monitoring, bias detection, and
corrective measures, creating systems that not only perform well but also
uphold ethical standards and societal values, fostering trust and
legitimacy in automated decision-making processes.
The aim of the current session is to promote the exchange between different
researchers working on these topics, over the view of the intelligent data
engineering framework. Core themes or topics include, but are not limited
to:
-Innovative algorithms and techniques for boosting transparency and
explainability in decision support systems.
-New approaches for characterizing and improving fairness in decision
support.
-Human-in-the-loop approaches for explainability and fairness.
-Explainability and fairness in recommender systems.
-Real-world applications.
Research works focused on explainability and fairness under the umbrella of
the computational intelligence and intelligent data analysis practices, are
also welcome.
The session is supported by the Spanish Thematic Network of Recommender
Systems Research (ELIGE-IA) (https://www.esi.uclm.es/elige-ia/)

Important dates
Full Paper Submission: June 26th, 2024
Conference Date: November 20-22, 2024

Templates and Submission method
Submission Site:
https://cmt3.research.microsoft.com/IDEAL2024
On the option “Create new submission”, choose “Special Session:
Explainability and Fairness for Decision Support.
Authors are invited to submit their manuscripts (in pdf format) written in
English by the deadline via the conference online submission system (see
conference website). All submissions will be peer-reviewed by experts in
the field based on originality, significance, quality and clarity. All
contributions must be original, must not have been published elsewhere, and
must not have been submitted elsewhere during the review period. Papers
should normally be within 9 pages (including references) but must not
exceed 12 pages, and must comply with the format of Springer LNCS/LNAI
Proceedings (see www.springer.com/lncs).
To encourage emerging results and novel initial developments, especially
from PhD students and young researchers, we accept short papers (within 6
LNCS pages). Short papers can be submitted a week after the deadline. Such
papers will also go through our rigorous peer-review process for their
novelty and soundness with a quicker turn-around time. Although short
papers are mainly for the main track, they can be submitted to any relevant
Special Session too (information will be available). The submission system
will treat any paper within 6 pages as short papers and PC chairs will
ensure a speedy review of them.

Contact:
Luis Martínez
University of Jaén
martin at ujaen.es

Bapi Dutta
University of Jaén
bdutta at ujaen.es

Raciel Yera
University of Jaén
ryera at ujaen.es