Special Session

Advances on eXplainable Artificial Intelligence

Officially approved (http://sites.ieee.org/fuzzieee-2019/special-sessions/)

Organized by: Jose M. Alonso, Ciro Castiello, Corrado Mencar

NOTE: The paper submission deadline for fuzzieee19 has been extended 2 weeks. The new submission deadline is January 25.

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In the era of the Internet of Things and Big Data, data scientists are required to extract valuable knowledge from the given data. They first analyze, cure and pre-process data. Then, they apply Artificial Intelligence (AI) techniques to automatically extract knowledge from data.

Our focus is on knowledge representation and how to enhance human-machine interaction. As remarked in the last challenge stated by the USA Defense Advanced Research Projects Agency (DARPA), "even though current AI systems offer many benefits in many applications, their effectiveness is limited by a lack of explanation ability when interacting with humans". Accordingly, users without a strong background on AI, require a new generation of explainable AI systems. They are expected to naturally interact with humans, thus providing comprehensible explanations of decisions automatically made. This is also aligned with the European vision for AI (CLAIRE) which remarks the need of building trustworthy AI that is beneficial to people through fairness, transparency and explainability. Thus, the goal of this special session is to discuss and disseminate the most recent advancements focused on explainable artificial intelligence. The session goes a step ahead with respect to the previous events we organized (which were mainly focused on interpretable fuzzy systems) in some other conferences: joint IFSA-EUSFLAT 2009, ISDA 2009, WCCI 2010, WILF 2011, ESTYLF 2012, WCCI 2012, EUSFLAT 2013, IFSA-EUSFLAT2015, FUZZ-IEEE2017, and IPMU2018.

The aim of this session is to provide a forum to disseminate and discuss XAI, with special attention to Interpretable Fuzzy Systems. Notice that about 30% of publications in Scopus (20 October 2017) regarding XAI came from authors well recognized in the field of Fuzzy Logic, as described in the following publication:

Jose M. Alonso, C. Castiello, C. Mencar, "A Bibliometric Analysis of the Explainable Artificial Intelligence Research Field", 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), Cádiz, Spain, Springer, CCIS 853:2-15, 2018.

Scope and topics

Explainable Computational Intelligence
Theoretical Aspects of Interpretability
Dimensions of Interpretability: Readability versus Understandability
Learning Methods for Interpretable Systems and Models
Interpretability Evaluation and Improvements
Models for Explainable Recommendations
Design Issues
Successful Applications of Interpretable AI Systems

Interpretable Machine Learning
Interpretable Fuzzy Systems
Relations between Interpretability and other Criteria (such as Accuracy, Stability, Relevance, etc.)
Explainable Agents
Self-explanatory Decision-Support Systems
Argumentation Theory for Explainable AI
Natural Language Generation for Explainable AI
Interpretable Human-Machine Interaction

Notes

Papers submitted for special sessions are to be peer-reviewed with the same criteria used for the rest of contributed papers. As a result, all papers submitted to this special session (if accepted and presented) will be published as part of the regular FUZZ-IEEE proceedings. If you are interested in taking part in this special session, please submit your paper directly through the FUZZ-IEEE web site selecting the option "Main research topic": SS - Advances on eXplainable Artificial Intelligence.

The session will end with an Open Discussion (20 min) where the chair will lead wider discussion around XAI in the context of the papers presented and their alignment with the mid-term strategic goals of the DARPA XAI program as well as the CLAIRE initiative on AI. The aim is to offer an opportunity for researchers and practitioners to identify new promising research directions in this area.