Explainable Artificial Intelligence: Efficiency and Sustainability
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 8185
Special Issue Editors
Interests: artificial intelligence; machine learning; deep learning; complex systems; computational intelligence
Interests: artificial intelligence; artificial neural networks; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the last few years, with the rapid growth in generating data and increasing demand for computing power, Artificial Intelligence (AI) has been employed to enhance the performance of systems over a wide variety of tasks and applications in our private and professional lives. However, despite this considerable performance, the internal mechanisms of the machine learning or deep learning techniques are ambiguous as their inner architectures are non-linear and complex to understand. This complexity may lead to difficulty in understanding these models. Many powerful techniques have been used as “black boxes” and they have not provided any information about how and why certain methods of estimation, classification, and prediction are chosen. Although experts can interpret the structure of these models, in many daily applications, such a shortage of transparency may affect users’ ability to utilize the software or devices equipped by these models. This is best understood when it comes to medical applications since there is a meaningful connection between the success of a diagnosis or treatment of disease and the acceptability of the used method.
In this regard, the development of methods for interpreting, explaining, and visualizing AI-based models has recently attracted great attention. This field of research, referred to as explainable artificial intelligence (XAI), tries to shed light on existing AI methods and design new AI techniques whose learning processes and decisions can be understandable for users.
In this Special Issue, we are particularly interested in showcasing recent advancements in the area of explainable artificial intelligence, as well as in presenting recent results, reviews, and case studies to illustrate and analyze the impacts of such techniques on the future of AI applications. Prospective authors are invited to submit original manuscripts on topics including, but not limited to, the following:
- Impacts of transparency and accountability of ai in the smart banking system;
- explainable artificial intelligence and healthcare systems;
- Acceptability and interpretability of XAI in sustainable development;
- explainable artificial intelligence and sustainable AI;
- XAI perspectives in designing hardware or software;
- Effects of XAI in developing and acceptability metaverse;
- explainable artificial intelligence and gaming;
- explainable artificial intelligence and blockchain, cryptocurrency and cyber security;
- Sustainable robotics and explainable artificial intelligence
Dr. Mohammad (Behdad) Jamshidi
Dr. Sobhan Roshani
Dr. Fatemeh Daneshfar
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. Electronics 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
- robotics and XAI
- gaming and XAI
- blockchain and XAI
- AI sustainability
- AI trustworthy
- AI acceptability
- AI interpretability
- cryptocurrency and XAI
- healthcare and XAI
- cyber security and XAI
- metaverse and XAI
