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D3.2 - List of requirements incorporated into the new standards produced by the TEF

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While other work packages (WP) of the project focus on physical and digital facilities for technical assessment of AI and Robotics solutions, mainly aiming at performance, quality and safety, WP 3 emphasizes aspects such as ethical, legal, societal, lifecycle, and cybersecurity assessments. These aspects are essential within the existing regulatory and standardization framework, particularly in the AI Act, the Machinery Regulation, the Data Act, and the Cybersecurity Act. The objective of WP 3 is to conduct a detailed analysis of the associated requirements and enable the project to offer a range of services that effectively address these aspects. Particularly as the agrifood sector faces significant challenges in achieving regulatory compliance for AI and robotics solutions due to the inherent complexity of agricultural environments and the evolving nature of AI technologies. This deliverable explores these challenges and provides a comprehensive analysis of regulatory frameworks and best practices to support TEF partners in navigating fields of application of AgrifoodTEF’s relevant standards and conformity assessment processes. The deliverable also delves into key regulatory frameworks such as the AI Act, Machine Regulation, and Cybersecurity Act and others from the New Legislative Framework, emphasizing their relevance to the agrifood sector. CE Marking is highlighted as a critical step for market readiness, offering competitive advantages and fostering trust among stakeholders. The analysis identifies gaps in existing standards and comments on strategies for harmonization and future development. AgrifoodTEF’s role is to provide comprehensive support to clients, offering tools, infrastructures, and expertise to streamline compliance efforts. This deliverable serves as a roadmap for achieving regulatory alignment and optimizing market adoption of AI and robotics solutions in the agrifood sector, with actionable recommendations for stakeholders to address identified challenges and gaps.

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Sujets associés

Smart Agriculture and AIAdversarial Robustness in Machine LearningPhysical Unclonable Functions (PUFs) and Hardware Security

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