Astrology and Machine Learning: Can Algorithms Better Predict What Will Happen to People

Abstract

Machine learning has grown very quickly, which has changed predictive models in many areas. However, some people are not sure if it can beat belief-based systems like astrology at predicting what will happen in people's lives. Astrological systems use astronomical patterns and symbolic interpretation to make predictions. This study compares the prediction skills of algorithmic models created in Machine Learning and astrological systems. Our study's goal is to look into how machine learning models use very large datasets, statistical patterns, and computer-based methods to make predictions about people's behavior, decisions, and the results of their lives. Astrology, on the other hand, is based on broad correlations between the positions of the planets and human traits. As a result, its statements are not backed up by evidence and can not be made over and over again. By showing the differences between data-driven forecasts and interpretive belief systems, the study shows how the two approaches are different in how they work. Despite the fact that machine learning models have been shown to be correct, the study also looks into the psychological appeal of astrology. There are a number of reasons why astrology is still useful, even in places with a lot of technology. Cognitive biases, emotional demands, and cultural affects are some of these factors.