Akaike’s Information Criterion (AIC) is a very useful model selection tool, but it is not as well understood as it should be. I frequently read papers, or hear talks, which demonstrate misunderstandings or misuse of this important tool. The following points should clarify some aspects of the AIC, and hopefully reduce its misuse. The AIC is a penalized likelihood, and so it requires the likelihood to be maximized before it can be …