State of play and future directions in industrial computer vision AI standards
Artemis Stefanidou, Panagiotis Radoglou-Grammatikis, Vasileios Argyriou, Panagiotis Sarigiannidis, Iraklis Varlamis, Georgios Th. Papadopoulos
TL;DR
The paper surveys rapid advances in AI/DL and CV, highlighting the urgent need for industrial standards addressing reliability, transparency, trust, security, safety, and robustness; it focuses on interpretability, data quality, and regulatory compliance and outlines a systematic analysis of current CV standards from major bodies. It analyzes the current landscape of standards from ISO/IEC, IEEE, DIN and other bodies, with emphasis on how standards relate to interpretability, data quality, and regulatory compliance. It discusses challenges including fragmentation across organizations, bias, security/privacy, evaluation, risk assessment, and balancing innovation with regulation. It provides a roadmap toward harmonization, governance, and lifecycle-wide risk management for industrial CV AI systems.
Abstract
The recent tremendous advancements in the areas of Artificial Intelligence (AI) and Deep Learning (DL) have also resulted into corresponding remarkable progress in the field of Computer Vision (CV), showcasing robust technological solutions in a wide range of application sectors of high industrial interest (e.g., healthcare, autonomous driving, automation, etc.). Despite the outstanding performance of CV systems in specific domains, their development and exploitation at industrial-scale necessitates, among other, the addressing of requirements related to the reliability, transparency, trustworthiness, security, safety, and robustness of the developed AI models. The latter raises the imperative need for the development of efficient, comprehensive and widely-adopted industrial standards. In this context, this study investigates the current state of play regarding the development of industrial computer vision AI standards, emphasizing on critical aspects, like model interpretability, data quality, and regulatory compliance. In particular, a systematic analysis of launched and currently developing CV standards, proposed by the main international standardization bodies (e.g. ISO/IEC, IEEE, DIN, etc.) is performed. The latter is complemented by a comprehensive discussion on the current challenges and future directions observed in this regularization endeavor.