Introducing the cutting-edge SAFE AI methodology, a framework crafted to meet the highest standards of safety and reliability in AI systems. Drawing upon internationally recognized guidelines such as ISO 26262, ISO 21448, and ISO PAS 8800, as well as the stringent requirements outlined in the EU AI Act for high-risk systems, this methodology sets a new benchmark for AI safety protocols.
At its core, SAFE AI prioritizes the traceability of causal relationships between any functional shortcomings within AI systems and the corresponding mitigation measures, aligning seamlessly with ISO 21448 and ISO PAS 8800 standards. By systematically managing uncertainties inherent in AI development, including processes, tools, and design choices, SAFE AI instills confidence in the system's performance and reliability.
One of its standout features lies in its evaluation of confidence levels in assurance arguments, bolstered by a comprehensive analysis of evidence strength, ensuring that every safety claim is backed by indisputable support. Moreover, SAFE AI seamlessly integrates with DevOps practices, facilitating continuous safety assurance as required by ISO PAS 8800.
In addition to its technical prowess, SAFE AI also supports stakeholders across the AI value chain, offering invaluable assistance in requirement elicitation, validation, and verification of safety-relevant quality attributes. Utilizing a contract-based approach, it ensures that the diverse needs of stakeholders are met, further cementing its position as a cornerstone of AI safety in today's rapidly evolving landscape.