Description: Elicitation-Based Generative Models are approaches that allow for the generation of data from information obtained directly from experts or stakeholders. These models are based on the idea that the knowledge and experience of individuals with a deep understanding of a specific domain can be used to create accurate and useful representations of data. Through elicitation techniques, opinions, judgments, and relevant data are collected and then integrated into a generative model. This type of model is especially valuable in contexts where historical data is scarce or where a deeper understanding of underlying dynamics is required. Key characteristics of these models include their ability to adapt to different contexts and their focus on collaboration between experts and analysts. Additionally, they allow for the incorporation of uncertainty and variability in the generated data, making them useful in decision-making and strategic planning. In summary, Elicitation-Based Generative Models represent an intersection between human intelligence and computational modeling, offering an innovative approach to data generation across various disciplines.
