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* Use: **Sporadically**, **intermittently**, or **now and then**
Okay, now let's talk about *governance*. In the context of *distributed AI*, *governance* refers to the policies, processes, and structures that guide the development, deployment, and use of these systems. The goal is to ensure that *AI systems* are developed and used responsibly, ethically, and in a way that aligns with organizational goals and societal values. The implementation of a strong *governance* framework is essential for several reasons, and there are many challenges. Because AI is evolving rapidly, the legal and regulatory landscape is still catching up. This means that organizations often have to navigate a complex and evolving set of rules. Also, *accountability and responsibility* can be a challenge. In *distributed AI systems*, it can be difficult to determine who is responsible for the decisions made by the AI. You also have to deal with *bias and fairness*. AI systems can perpetuate existing biases in the data they are trained on, leading to unfair outcomes.
* **Unsupervised Learning:** Clustering (k-means), dimensionality reduction (PCA).
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