This complex model stimulates the trade-offs of AI by balancing the costs associated with AI resource usage, consisting of computational power, energy, and human resources, in comparison to the benefits which are gained through both increased efficiency and effectiveness of AI systems. Further, this model will increase one's understanding of trade-offs and optimal investment strategies in an effort to maximize AI performance.
Within this model, in order to understand the relationship between associated costs of AI, and efficiency and effectiveness of AI, the stocks are comprised of resource costs, AI efficiency, and AI effectiveness. Further, the inflows of the model, which are associated with AI costs consist of investment, hiring and training, efficiency improvement, and effectiveness improvement. In opposition, the outflows of the model, which are associated with AI efficiency and AI effectiveness are energy use and operational costs. It should be noted that AI efficiency and AI effectiveness directly enhance and influence each other. Further variables for each stock, inflow, and outflow can be visualized within the model, and the effect these have on the AI associated costs, AI efficiency, and AI effectiveness can be understood through simulations of the data.
Note: A key aspect of this model to understand is that it was informed by AI itself, in which AI searched were utilized to develop a complex, dynamic model that could adequately model the aspects listed above. Specifically, the AI search engine of Microsoft Copilot was used.
