Unlocking Decision-Making: AI Bridges Theoretical Frameworks with Technological Advancements | by Stephanie Shen | Dec, 2023

A brief overview of how data science and AI help decision-making

Photo by Jake Melara on Unsplash

Our lives consist of constant decisions and choices. Because the consequences of our decisions can lead to considerable economic and social impacts, the research on decision-making was highly interdisciplinary from the beginning. Scientists from mathematics, sociology, psychology, economics, political science, and computer science have been actively studying how to make better decisions since the mid-20th century. Among the many achievements in these fields, the most well-known are the expected utility, prospect, and game theories. These theories are driven by mathematical models but often face challenges from empirical tests of real-world scenarios.

With the tremendous increase in computation power and the blooming of cloud technologies, decision support systems (DSS) have advanced in parallel with the decision theories to assist humans in making decisions, particularly in the business and organizational context. A typical DSS includes scalable knowledge databases to collect and store large amounts of information, statistical and analytical algorithms for forecasting and projection, and user interfaces (including charts and dashboards) for human decision-makers to visualize and interact with the decision-making process.

Most human decisions, however, have resulted from incremental learning of trial and error. The iterative approach is particularly effective in dealing with unknowns in a novel environment. It requires explorations for new information and assessments of errors to refine decision-making. Remarkably, deep reinforcement learning has emulated the trial-and-error nature of human decision-making and surpassed human players in specific games.

Reinforcement learning (RL) was one of those machine learning fields that have been around from the beginning. Its significant breakthrough happened after the deep neural network was applied to the model. The deep RL is just one of those examples of AI and deep learning revolutionizing the decision-making field. We now find ourselves in an era where AI provides the foundation to bring all decision-making disciplines together, fastens the…

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