Computer Science as a term should simply capitulate and give way to AI

In French the term “informatique” feels slightly better, as a label to describe the field, than “Computer Science” feels in English. But this is a rare occurrence for French, because most of the other terms, like “technologie de l’information”, and “science des données”, feel awkward and far from their “real” cultural counterpart, the thing in itself that we do, when we do it.

The debate and problems with the term “AI” are on another whole level. What is it, what do we mean by it? How can the term retain its meaning if the goalpost is always shifting? Are we talking about AI in the general sense, which includes things like Google Search and Deep Blue, which were once genuine AI, but have now become more commonplace computer science stuff? Or are we rather talking about AI in the most radically recent sense, ChatGPT and LLMs?

A lot of people simply brush off these linguistic concerns: who cares really?

But some people do care! And for those, I propose the idea of starting the shift to a unification scheme: let’s start calling all things related to computers: AI, without any ambiguity. No more informatique and computer science! Yes, even hardware and systems stuff, programming, data structures, everything is now AI!

The beauty in that idea, I believe, is that a lot of the concepts at the foundations of classical AI (GOFAI) have simply evolved into classical computer science stuff: search algorithms, constraint programming, data structures, LISP-style functional programming, object-oriented programming, the list is very long. These things have NOT been subsumed into CS because of the goalpost moving phenomenon, but rather because they have simply become accepted as mainstream fundamental building blocks of the culture of creating things with computers. We have accepted them as “normal” CS stuff, and moved on.

So I think that the entire field of computer science should simply be bolder in its acceptance of this stronger term, that we’ve had all along: what we are doing is fundamentally Artificial Intelligence, the creation of an artificial mind in a non-biological substrate. But of course, this giant field can clearly be separated into two broad smaller sub-fields: classical AI, which gave us programming languages, data structures, modern IDEs, etc. And finally, machine learning, statistical learning, which is a fundamentally new way of thinking about computing, but is still implemented with classical AI ideas, in the end.

To pacify the language of computing, everything should simply become AI.