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Explainable Artificial Intelligence in Consumer-Centric Business Practices and Approaches
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Author(s): Sonal Trivedi (VIT Business School, VIT Bhopal University, Bhopal-Indore Highway, Kothrikalan, Sehore, India)
Copyright: 2024
Pages: 20
Source title:
AI Impacts in Digital Consumer Behavior
Source Author(s)/Editor(s): Thomas Heinrich Musiolik (Woxsen University, India & University of Europe for Applied Sciences, Germany), Raul Villamarin Rodriguez (Woxsen University, India)and Hemachandran Kannan (Woxsen University, India)
DOI: 10.4018/979-8-3693-1918-5.ch002
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Abstract
The review begins by discussing the fundamental concepts of XAI, highlighting its significance in enhancing consumer trust and engagement in AI-driven services and products. The authors explore various dimensions of XAI, such as interpretability, transparency, and accountability, and their implications in consumer-centric contexts. This study identifies a range of methods and techniques adopted by businesses to implement XAI, including rule-based systems, model-agnostic approaches, and interpretable machine learning models. Content analysis is employed as the primary research method in this review. The findings of this SLR provide a holistic overview of the current state of XAI in consumer-centric business practices and approaches, helping businesses and researchers gain a better understanding of the field's evolution and the challenges that lie ahead. It also underscores the importance of ethical considerations and regulatory frameworks in fostering responsible AI adoption within consumer-focused domains.
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