• CFP for IEEE Computational Intelligence Magazine - Special Issue on Exp

    From Corrado Mencar@21:1/5 to All on Sat Jan 16 15:19:04 2021
    * Apologies for cross-postings *

    Dear colleagues,
    we are organizing a special issue on "Explainable and Trustworthy Artif icial Intelligence" to be published in the IEEE Computational Intelligence Magazine (CIM) by the second half of 2021. Deadline is approaching: 15 Feb
    2021 !

    Submission website: https://mc.manuscriptcentral.com/cim-ieee

    CIM publishes peer-reviewed articles that present emerging novel discoverie
    s, important insights, or tutorial surveys in all areas of computational in telligence design and applications, in keeping with the Field of Interest o
    f the IEEE Computational Intelligence Society (IEEE/CIS).

    - Impact Factor: 9.083
    - SJR: Q1 (Artificial Intelligence)
    - Website: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber207

    You are kindly invited to submit a paper for this special issue. In additio
    n, we highly appreciate if you can help us to disseminate this Call for Pap
    ers among your colleagues.

    ## Aims and Scope

    Computational Intelligence (CI) encompasses the theory, design, application
    , and development of biologically and linguistically motivated computationa
    l paradigms emphasizing fuzzy systems, neural networks, connectionist syste
    ms, genetic algorithms, evolutionary programming, and hybrid intelligent sy stems in which these paradigms are contained. These techniques and their hy bridizations work in a cooperative way, taking profit from the main advanta
    ges of each individual technique, in order to solve lots of complex real-wo
    rld problems for which other techniques are not well suited. CI enables Art ificial Intelligence (AI) through simulating natural intelligence in all it
    s forms.

    In the era of the Internet of Things and Big Data, data scientists are requ ired to extract valuable knowledge from the given data. They first analyze,
    cure and pre-process data. Then, they apply AI techniques to automatically
    extract knowledge from data. AI is identified as a strategic technology an
    d it is already part of our everyday life. The European Commission states t
    hat “EU must therefore ensure that AI is developed and applied in
    an appropriate framework which promotes innovation and respects the Union'
    s values and fundamental rights as well as ethical principles such as acco untability and transparency”1. It emphasizes the importance of Expl
    ainable AI (XAI in short), in order to develop an AI coherent with European
    values: “to further strengthen trust, people also need to underst
    and how the technology works, hence the importance of research into the exp lainability of AI systems”. Moreover, as remarked in the XAI challe
    nge stated by the USA Defense Advanced Research Projects Agency (DARPA), “even though current AI systems offer many benefits in many applic
    ations, their effectiveness is limited by a lack of explanation ability wh
    en interacting with humans”2. Accordingly, users require a new gen
    eration of XAI systems. They are expected to naturally interact with humans
    , thus providing comprehensible explanations of decisions automatically mad

    XAI is an endeavor to evolve AI methodologies and technology by focusing on
    the development of agents capable of both generating decisions that a huma
    n could understand in each context, and explicitly explaining such decision
    s. This way, it is possible to scrutinize the intelligent models and verify
    if automated decisions are made on the basis of accepted rules and princip les, so that decisions can be trusted, and their impact justified.

    This Special Issue is supported by the IEEE CIS Task Force on Explainable F uzzy Systems ([TF-EXFS](https://sites.google.com/view/tf-explainable-fuzzy- systems/)). The mission of the TF-EXFS is to lead the development of a new
    generation of Explainable Fuzzy Systems, with a holistic view of fundamen tals and current research trends in the XAI field, paying special attentio
    n to fuzzy-grounded knowledge representation and reasoning but also regard
    ing how to enhance human-machine interaction through multi-modal (e.g., gr aphical or textual modalities) effective explanations.

    The scope of this special issue is not limited to the community of research
    ers in Fuzzy Logic, but it is open to contributions by researchers, from bo
    th academy and industry, working in the multidisciplinary field of XAI.

    ## Topics

    This special issue is targeted on general readership articles about design
    and application of XAI technologies.
    Topics of interest include, but are not limited to:
    - Theoretical Aspects of Explainability, Fairness, Accountability and Trans parency
    - Relations between Explainability and other Quality Criteria (such as Inte rpretability, Accuracy, Stability, Relevance, etc.)
    - Dimensions of Interpretability: Readability versus Understandability
    - Explainability Evaluation and Improvements
    - Learning Methods and Design Issues for Explainable Systems and Models
    - Interpretable Machine Learning
    - Explaining Black-box Models
    - Hybrid Approaches (e.g., Neuro-Fuzzy systems) for XAI
    - Model-specific and Model-agnostic Approaches for XAI
    - Models for Explainable Recommendations
    - Explainable Conversational Agents
    - Self-explanatory Decision-Support Systems
    - Factual and Counterfactual Explanations
    - Causal Thinking, Reasoning and Modeling
    - Cognitive Science and XAI
    - Argumentation Theory for XAI
    - Natural Language Technology for XAI
    - Human-Machine Interaction for XAI
    - Ethics and Legal Issues for XAI
    - XAI-based Data Analysis and Bias Mitigation
    - Safe and Trustworthy AI
    - Applications of XAI-based Systems
    - Open Source Software for XAI

    ## Submission

    The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed high-quality articles. All manuscripts must be submitted electronically in
    PDF format. Manuscripts must be in standard IEEE two-column/single space fo rmat and adhere to a length of 10-12 pages (including figures and reference
    s) for regular papers. A mandatory page charge is imposed on all papers ex ceeding 12 pages in length.

    More information on manuscript details and submission guidelines can be fou
    nd at the following websites:
    - Special Issue website: https://sites.google.com/view/special-issue-on-xai -ieee-cim
    - IEEE CIM website: https://cis.ieee.org/publications/ci-magazine/cim-infor mation-for-authors

    ## Important Dates

    - Manuscript Due: **15th February, 2021**
    - First Notification: 15th April, 2021
    - Revision Due: 15th May, 2021
    - Final Notification: 1st July, 2021
    - Publication Date: November 2021

    ## Guest Editors

    - José María Alonso, Research Centre in Intelligent Technologies
    (CiTIUS), University of Santiago de Compostela, Spain
    - Corrado Mencar, Department of Informatics, University of Bari “Al
    do Moro”, Bari, Italy
    - Hisao Ishibuchi, Department of Computer Science and Engineering, Southern
    University of Science and Technology, Shenzhen, China

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