I will describe our research showing how even very young human children engage in effective causal inference - discovering new causal relationships through observation and intervention. This includes not only inferring specific causal relationships but the discovery of abstract causal “over-hypotheses” , variable discovery, analogical reasoning and active learning through exploration. I will discuss implications for causal learning in AI systems and for designing machine common sense.