The difference between natural and computer languages is not merely one of degree, with natural languages’ involving vocabularies that are several orders of magnitude larger than those of computer languages. Natural languages aren’t just more complex versions of the algorithms with which we teach machines to do tasks; they are also the living embodiments of our essence as social animals . We express our love and our losses, explore beauty, justice and the meaning of our existence, and even come to know ourselves all through natural languages.

The irony is that few people appreciate the uniqueness of human language more than coders working in artificial intelligence, who wrestle with the difficulty of replicating our cognitive abilities. The computer scientist Alan Turing noted that the question of whether a machine can think is incredibly difficult to determine, not least because of the lack of a clear definition of “thinking”; he proposed investigating instead the more tractable question of whether a machine can convince a human interlocutor that it’s human — the so-called Turing test.

One of the important lessons of Turing’s test is the reminder that in our interactions with other people, we are fundamentally limited in how much we can know about another’s thoughts and feelings, and that this limitation and the desire to transcend it is essential to our humanity. In other words, for us humans, communication is about much more than getting information or following instructions; it’s about learning who we are by interacting with others.

The interpersonal essence of language learning extends to learning as a whole. We know that small-group, in-person instruction is more effective than traditional lectures. We ask questions, are asked in return, and we learn more, learn faster and retain more when we care about the people we are interacting with. It’s no accident that despite the initial enthusiasm generated by MOOCs, or massive online open courses, they have in fact been a major disappointment, with completion rates as low as 5 percent. By comparison, online courses with smaller groups of students and direct feedback from the professor show completion rates as high as 85 percent.

In an age of ever-rising inequality and student debt, it’s understandable that policymakers should seek to maximize the skills that seem the most marketable. And there is no doubt that computer programming is a valuable tool.