This paper explores how the rise of algorithms, particularly machine learning, is profoundly changing the field of economics, going beyond just impacting the economy itself. It argues that unlike previous technological innovations, algorithms represent a fundamental shift in how decisions are made, which is the core of economics. The author highlights that traditional econometric tools are designed for estimating parameters, whereas machine learning excels at predicting outcomes. This distinction leads to new areas of research, such as "prediction policy problems", where decisions hinge on predictive inferences rather than causal ones. The text further discusses how algorithms can aid in scientific discovery by generating hypotheses and identifying anomalies that challenge existing economic theories. Finally, it emphasizes that as algorithms become increasingly integrated into economic decisions, they will become a necessity for economic modeling and policy design.