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companies are viewing customers as a means to an end – fuel for their AI engines, shiny generative models (to name a few) have already scraped much (if not all) of the internet to train their generative AI models

Transparency in AI algorithms, data privacy protection, and addressing bias in machine learning models XAI emphasizes transparency and interpretability in AI systems, ensuring that decisions made by AI models

organizations the essential concepts and principles that underlie management programs based on an operational model This model incorporates the science of governing, systems, risk, and promise theories, along with Lean

recent years, standards and regulations have specified the need for companies to adopt improvement models The need for maturing systems is not new and there are many: methods, frameworks, and models that can

These programs are based on reactive models characterized by: lagging indicators, audit-fix cycles, and Unfortunately, GRC appears to be preoccupied with this same reactive model correcting things after they The reactive model on which GRC is based is not enough to achieve the desired outcomes for GRC never A proactive model would function as a regulated system (in the technical sense) focused on outcomes,

The PLUS Decision Making model developed by The Ethics Resource Center can help organization’s make generations to meet their own needs.” - United Nations This is another test we could add to the PLUS model

AI algorithms within digital twins enable predictive modeling and optimization, but they may also amplify Additionally, complex AI models may lack interpretability, hindering decision-makers' ability to trust

This requires a more thorough discussion on the nature of uncertainty, cause/effect models, and working tools and practices (probabilities, likelihoods, Monte Carlo, estimation techniques, aggregation, modelling

technology has evolved through decades of research and experimentation to reach today's transformer models Machine Learning : The creation of knowledge models stored in neural networks, where most current AI Uncertainty about AI Models: Laqua pointed out that "all models are wrong, although some are useful. Uncertainty about Intelligence : The DIKW model (Data, Information, Knowledge, Wisdom) suggests that that humans introduce a top-down aspect related to morality, imagination, and agency that current AI models

Rasumussen's model and others since represent a growing trend away from "root causes" or you might say

There are many reasons why this is the case, that include the nature of how knowledge models work, the

I knew that information about Lean Compliance used in current foundation models was not up-to-date and