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However, compliance for the most has lagged behind and still functions using the old factory model using

Model-based Risk Assessmen t: This method uses computer models and simulations to predict the likelihood It involves creating a mathematical model of the system being assessed and running simulations to test

The scientific method aims to develop theoretical models and explanations for natural phenomena, while

This requires thinking in engineering terms such as: Design Thinking, Systems Engineering, Model Based

A trained model's decision-making process often remains opaque, making it difficult to predict behaviour requirements that conflate technical capabilities with user needs, no systematic analysis of failure modes Each unaddressed bias, unanticipated failure mode, or unhandled edge case represents a choice about acceptable This means asking harder questions about requirements, spending more time analyzing potential failure modes

During that time we learned all about business modeling, re-engineering, and the like.

The combined system was modeled after ISO 9001 and ISO 45001 and supported regulatory obligations for All of this was accomplished over the course of 12 months utilizing the Lean Compliance Startup Model

The tension between value production and compliance is a false dichotomy based on an old-factory model

apply to evaluate the risks associated with their AI systems, including aspects such as data quality, model

Modeling, simulation, and experimentation are essential to developing options.

Unfortunately, many of these same companies use a reactive compliance model that was developed only to

Performance models (and this includes compliance) based on the reactive audit-fix cycle have not been