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139 results found for "Model"
- Crossing The Ethical Chasm of Data Mining
This will help in updating our system models and processes to make them more efficient. In a fashion, we construct a "model" for how we understand the world and then validate that model using Management systems are based on models for how things get done. How true a model is depends on several factors that include: resolution, fidelity, and effectiveness. This is why we need to apply the scientific method to update our models so that they become "truer" in
- Developing an Environmental Golden Thread - Part 1 (Using a DSM)
A DSM models system elements and their corresponding information exchange, interactions, and relationship An environmental program will include many aspects which can be modelled using a DSM. We have used it here to model the 12 environmental pillars which need to be advanced simultaneously towards
- Paper Policies are Not Enough
This is a fundamental principle of cybernetic models (i.e., the Good Regulatory Theorem).
- AI Risks Document-Centric Compliance
To bring the risks into focus, let’s consider the use of Large Language Models (LLMs) used in applications What do LLM's model? They do not model your compliance program, your cybersecurity framework, or any other aspect of your LLMs model language to predict words, that's all. behaviours, and interactions necessary to achieve the outcome of compliance which is something that's not modelled
- Reverse Engineering Success: The Inversion Approach to Compliance
However, there is a lesser-known, yet profoundly effective mental model that turns this logic on its The inversion mental model asks you to work backward from an undesirable outcome, rather than from a Inversion in Action: How to Apply it to Compliance Success Let’s explore how the inversion mental model The power of the inversion mental model is that it forces organizations to consider these blind spots The inversion mental model offers a valuable approach by shifting focus to failure prevention.
- Navigating Modern Risk: Embracing Uncertainty as the Key to Success
The old model of risk assessment, primarily focused on mitigating the consequences, no longer serves Model Uncertainty : Often, risks are assessed using models that may not accurately reflect reality. Model uncertainty recognizes the limitations of these models and their potential deviations from actual
- Moving Compliance to the Performance Zone
This is a very useful model not only to understand how companies can best prioritize their efforts but with compliance added in RED : Performance Zone – The focus of this zone is to execute the business model Transformation Zone – this is where a disruptive business model scales and is introduced to the performance
- What is Operational Compliance?
However, this defines “Procedural Compliance” which is based on a traditional and reactive model for Instead, “Operational Compliance”, which is based on a holistic and proactive model, defines a state
- AI Engineering: The Last Discipline Standing
discussions I have had over the last year, IT product companies appear to be moving towards an AI first model The traditional model—where product managers coordinate with software engineers, UI designers, data analysts Companies like Vercel, Replit, and dozens of Y Combinator startups demonstrate this model in action daily AI reliability and maintenance - AI systems need monitoring, debugging, and optimization Develop AI model customization expertise - Fine-tuning, prompt optimization, and model selection Master AI-human collaboration
- Engineering Through AI Uncertainty
Known-Unknowns (Complicated Domain) Here we have moderate visibility. Traditional models struggle to provide explanations for what occurs in this domain. State of AI Uncertainty Current AI technologies, particularly advanced systems that use large language models What aspects of AI should receive attention: the technology itself, the models, the companies developing we can't predict specific outputs with perfect accuracy We understand enough about potential failure modes
- AI, AI, Oh!
For example, engineering has traditionally relied on algorithms, statistical analysis, models, and prediction
- Leading Health Systems Innovation
Current models are based on a reactive and transactional approach to how health care is delivered. focused on the future of health care, what it might look like, and how it can change from a reactive model We have the wrong model Reactive Transactional Funding the wrong things Regulation that constrains My thoughts Health care systems are based on a model that is not sustainable and it has been this way











