Explainable Artificial Intelligence (XAI) for Big Data

Dear Colleagues,

This Special Issue aims to explore the intersection of Explainable Artificial Intelligence (XAI) and Big Data, addressing the challenges and opportunities in rendering complex AI models understandable and transparent. We invite researchers and practitioners to contribute to the advancement of XAI methodologies tailored for large-scale data applications.

As the reliance on AI algorithms grows in managing vast datasets, ensuring transparency and interpretability becomes imperative. This Special Issue focuses on the scientific background of XAI, emphasizing its role in overcoming the opacity of AI models. The significance of this research area lies in fostering trust, facilitating regulatory compliance, and enabling practical deployment of AI in Big Data contexts.

The aim is to provide a platform for cutting-edge research that enhances the explainability of AI systems dealing with extensive datasets. This aligns with the broader scope of Electronics, offering insights into the evolving landscape of AI applications.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• The importance of XAI in Big Data analytics;
• Impact of XAI on Big Data analytics;
• XAI techniques for Big Data analytics;
• Complexities of XAI and Big Data analytics;
• Challenges and opportunities in XAI for Big Data analytics;
• Interpretable Machine Learning Models for Big Data;
• Ethical Considerations in XAI for Large-scale Data;
• XAI and data privacy;
• XAI and bias in Big Data analytics;
• Human–AI Collaboration in Understanding Complex Data Models;
• XAI and decision-making;
• XAI and efficiency;
• XAI and transparency;
• XAI and interpretability;
• Regulatory Compliance and Transparency in AI for Big Data;
• XAI and trust.

Dr. Gangmin Li
Dr. Paul Sant
Dr. Kevin Yuen
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.

• explainable artificial intelligence (XAI)
• big data
• transparency
• interpretable machine learning
• ethical AI
• human-AI collaboration
• regulatory compliance
• trust in AI