posted by organizer: ryera || 531 views || tracked by 1 users: [display]

ExpFair4DSS@IDEAL 2024 : Special Session on Explainability and Fairness in Decision Support, at IDEAL 2024. Hybrid conference.


When Nov 20, 2024 - Nov 22, 2024
Where Valencia, Spain; and online
Submission Deadline Jul 26, 2024
Categories    explainability   fairness   decision support   machine learning

Call For Papers

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.


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, especially those from historically marginalized communities. 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 Tematic Network of Recommender Systems Research (ELIGE-IA) (

Templates and Submission method

Submission Site:

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

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.

Luis Martínez
University of Jaén

Bapi Dutta
University of Jaén

Raciel Yera
University of Jaén

Related Resources

ICMLA 2024   23rd International Conference on Machine Learning and Applications
IEEE-EMBS BHI 2024   IEEE-EMBS International Conference on Biomedical and Health Informatics
Ei/Scopus-AACIP 2024   2024 2nd Asia Conference on Algorithms, Computing and Image Processing (AACIP 2024)-EI Compendex
IUKM 2025   11th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making
AAAI 2025   The 39th Annual AAAI Conference on Artificial Intelligence
PPMSA@IDEAL 2024   Special Session on Predictive and Prescriptive Models for Smart Cities’ Applications at the 25th International Conference on Intelligent Data Engineering and Automated Learning
IEEE-Ei/Scopus-SGGEA 2024   2024 Asia Conference on Smart Grid, Green Energy and Applications (SGGEA 2024) -EI Compendex
DEF-AI-MIA 2024   Workshop on Domain adaptation, Explainability, Fairness in AI for Medical Image Analysis & 4th COV19D Competition @ IEEE CVPR 2024
KDD 2025   31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining
IJIS Special Issue 2024   Reinforcing Cyber Security of Critical Infrastructures through Digital Twins