At the core of many disciplines – including biomedicine, finance, and the social sciences – is the search for causes. To predict future events, understand the connection between phenomena, explain why things happen, and intervene to alter outcomes, researchers must determine the causal relationships governing the behavior of the systems they study. Automating this process has been a difficult pursuit for many reasons, from insufficient data and computing power to the more fundamental question of what causality is and how it can be inferred from observational data alone.
However, many of the previous barriers to inferring complex causal relationships are falling. Through technological advances enabling interrogation of the activities ...