Interpretable and Explainable AI Applications
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Engineering and Science".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 715
Special Issue Editors
Interests: deep learning; XAI; human-centric AI; case-based reasoning; data mining; fuzzy logic and other machine learning and machine intelligence approaches for analytics—especially in big data
Special Issues, Collections and Topics in MDPI journals
Interests: use-inspired textual agents; explainable agency; case-based reasoning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The sub-fields of interpretable machine learning (IML) and explainable artificial intelligence (XAI) have substantial overlap. Both are concerned with the broader goal that AI systems, those that include AI methods, need to be interpretable to users and designers. AI is a much broader field than ML, so these fields have a great deal of synergy and must consider one another’s contributions. This Special Issue will target contributions that consider the broader view of the field that aims to investigate how AI systems explain themselves, either via interpretability or a combination of interpretability and explainability. IML/XAI will also play a vital role in sustainability issues with the sustainable development of AI applications as humans/society can trust AI.
The aim of this Special Issue is to provide a leading forum for the timely, in-depth presentation of recent advances in the research and development of interpretability and explainability techniques for AI applications.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- How artificial intelligence methods and systems explain their decisions;
- Interpretability of AI models and methods;
- Validation of explainability or interpretability approaches for AI;
- Robustness of methods for interpretability and explainability;
- Applications adopting AI methods with explainability or interpretability methods;
- Applications benefiting from different types of explanation contents, e.g., counterfactuals, feature attribution, instance attribution;
- Social aspects of explainability and interpretability in AI;
- Accountability of AI systems.
Please include in your submission a statement of whether your manuscript’s contribution is in computing and engineering or in social aspects. In case of including contributions in both aspects, please indicate which author(s) are contributing to each.
We look forward to receiving your contributions.
You may choose our Joint Special Issue in AI.
Prof. Dr. Mobyen Uddin Ahmed
Prof. Dr. Rosina O. Weber
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- explainability
- interpretability
- artificial intelligence applications
- validation
- accountability
