XAIR: A Systematic Metareview of Explainable AI (XAI) Aligned to the Software Development Process

Clement T, Kemmerzell N, Abdelaal M, Amberg M (2023)

Publication Type: Journal article, Review article

Publication year: 2023

Journal

Machine Learning and Knowledge Extraction MDPI

Book Volume: 5

Pages Range: 78-108

Journal Issue: 1

DOI: 10.3390/make5010006

Abstract

Currently, explainability represents a major barrier that Artificial Intelligence (AI) is facing in regard to its practical implementation in various application domains. To combat the lack of understanding of AI-based systems, Explainable AI (XAI) aims to make black-box AI models more transparent and comprehensible for humans. Fortunately, plenty of XAI methods have been introduced to tackle the explainability problem from different perspectives. However, due to the vast search space, it is challenging for ML practitioners and data scientists to start with the development of XAI software and to optimally select the most suitable XAI methods. To tackle this challenge, we introduce XAIR, a novel systematic metareview of the most promising XAI methods and tools. XAIR differentiates itself from existing reviews by aligning its results to the five steps of the software development process, including requirement analysis, design, implementation, evaluation, and deployment. Through this mapping, we aim to create a better understanding of the individual steps of developing XAI software and to foster the creation of real-world AI applications that incorporate explainability. Finally, we conclude with highlighting new directions for future research.

Authors with CRIS profile

Tobias Clement Lehrstuhl für Wirtschaftsinformatik, insbesondere IT-Management Nils Kemmerzell Lehrstuhl für Wirtschaftsinformatik, insbesondere IT-Management Michael Amberg Lehrstuhl für Wirtschaftsinformatik, insbesondere IT-Management

Related research project(s)

Towards a Better Understanding of Explainable Artificial Intelligence (XAI): Insights Gained from Selected Studies (XAI) Software Campus 2.0 April 1, 2022 - March 31, 2024

Involved external institutions

Software AG DE Germany (DE)

How to cite

APA:

Clement, T., Kemmerzell, N., Abdelaal, M., & Amberg, M. (2023). XAIR: A Systematic Metareview of Explainable AI (XAI) Aligned to the Software Development Process. Machine Learning and Knowledge Extraction, 5(1), 78-108. https://dx.doi.org/10.3390/make5010006

MLA:

Clement, Tobias, et al. "XAIR: A Systematic Metareview of Explainable AI (XAI) Aligned to the Software Development Process." Machine Learning and Knowledge Extraction 5.1 (2023): 78-108.

BibTeX: Download