Causality is the relationship between cause and effect, describing how a particular event or action leads to a specific outcome. It refers to the way in which prior events can play a role in creating behavior or outcomes of future events. Causality is used to explain why certain things happen and can help us understand underlying patterns or trends in our data. Causality is distinguished from correlation, which suggests that two variables are related, but does not make causal claims. Understanding the subtle difference between causation and correlation is key to building correct models to predict future behavior, create better interventions, and make informed decisions.

See also: evolution, emergence, agent-based modeling, free will