Industrial Explainable Artificial Intelligence Insights

This whitepaper presents insights into the role of explainable artificial intelligence (XAI) within industrial applications, particularly in manufacturing. It is designed for decision makers, product managers, and AI developers. The document outlines the increasing necessity of explainability throughout the AI life cycle, emphasizing its importance for compliance with the upcoming EU AI Act, which mandates transparency for high-risk AI systems. The whitepaper details the research approach, which involved interviews with 36 experts to gather perspectives on the relevance of XAI. Key findings indicate that explainability enhances trust and transparency in AI systems, impacting all stages of the AI life cycle, from data preparation to model evaluation and deployment. The document also discusses the challenges faced in implementing XAI in manufacturing, highlighting the need for collaboration between data scientists and domain experts to ensure effective AI model development and testing. Overall, it underscores the critical role of explainability in fostering user trust and meeting regulatory requirements.