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Regulatory models What might it mean to be a risk-based regulator? for regulators is "Model 1." This model produces prescriptive regulation typified by inspectors showing up with a tape measure to Finally, Model 4, is a variant of the previous model where the companies under regulation are too small Sparrow suggests that risk-based regulators will: Focus on the "Expert" rather than the "Legal" model

A DSM models system elements and their corresponding information exchange, interactions, and relationship Dependancy Structure Matrix An environmental program will include many aspects which can be modelled For example, the following pillars are sequential relationship in the Environmental Golden Thread model As such, the coupled relationships in the model show the critical areas of focus in the system. since it connects the main upper loop to the lower loop of the model (see dependency map below).

Our fish tank was a model of the real world, but not the world itself. As the British statistician George Box wrote, “All models are wrong, some are useful.” We need to use models to help us navigate the real world, not replace the real world by our models. Another way of saying this is that: we don’t live in our models, and neither do our businesses. Maintain Perspective- Use models as tools for understanding, not as blueprints for reality.

It provides context for how compliance fits into the overall business model. 2. into the operational business model. Evaluate Compliance Operability The final step is to assess how well the integrated compliance model One area where capability maturity models have been successfully employed is in software development, by Carnegie Mellon University, continues to develop and publish maturity models.

While this is necessary, it is based on an old model where meeting obligations (the act of compliance you start with an integrative, holistic, and proactive approach to meeting obligations, a different model

Continuous Change : Models may be retrained over time, either manually or automatically, as new data Engineering for robustness means testing models under various scenarios, stress conditions, and edge Explainability tools and techniques help uncover what’s driving the model’s decisions, which is essential Engineering includes versioning models, tracking data changes, managing retraining pipelines, and ensuring models continue to meet performance and compliance requirements over time.

Promise Theory, the framework Mark Burgess developed to model autonomous commitment, sits at the heart His observation was that the command-and-control model of managing devices was itself producing vulnerabilities His response was to model a different design principle: devices that govern themselves from within by develops this as a formal proposal: **Promise Agents** — security equipment with embedded, fine-tuned AI models

Rasumussen's model and others since represent a growing trend away from "root causes" or you might say Nancy's Leveson [2] provides an example of how this can be used to model safety control: Nancy Leveson - Hierarchical Model of Safety Control Framework Predictions Rasmussen's Risk Management Framework makes of pressure toward cost-effectiveness in an aggressive, competing environment Rasmussen's Migration Model - Transport Canada - Jim McMenemy, Safety Intelligence Project Rasmussen's migration model represents

and foundation models. However, organizations are developing their own specialized models for specific use cases. These custom models require their own risk assessment and safety measures tailored to their particular This means organizations cannot simply rely on foundation model providers to solve all safety problems If you're fine-tuning models, creating retrieval-augmented generation systems, or deploying AI agents

This will look different across industry sectors, but each will have an operational model that must be following maps are helpful to identify where these places are: Total Value Chain Map Organizational Model The Operating Model Canvas book is a good place to start understanding operating models from which you

One is tearing down the model we’ve relied on for decades. Think about what that means for the platform model. The existing model has exhausted its goodwill. The SaaS model — the dominant business model in technology for the past two decades — starts to look Bespoke, AI-generated solutions invert that model.

concept of operations (CONOPS) for these management system standards varies but each follows a similar model illustrated below: Operational Compliance Model - Concept of Operation Successfully implementing these Download our Lean Operational Compliance Model: (Version 4) – Operational Compliance is a state of operability This operational compliance model will help you achieve and sustain operational readiness so that you This model now includes the 5 immutable principles of program success: