Language and communication are considered as relevant to artificial intelligence. Linguists are not the only scientists wishing to test theories of language functioning: so do psychologists and neurophysiologists. This chapter briefly looks at samples of important and prescient early work, and shows two contrasting, slightly later, approaches to the extraction of content, evaluation, representation, and the role of knowledge. It considers a range of systems embodying natural language processing (NLP)/computational linguistics (CL) aspects since the early seventies, and divides them by their relationships to linguistic systems and in relation to concepts normally taken as central to AI, namely logic, knowledge, and semantics. Broadly, statistical methods imply the use of only numerical, quantitatively based, methods for NLP/CL, rather than methods based on representations, whether those are assigned by humans or by computers. The chapter discusses the role of annotations to texts and the interpretability of core AI representations.