I was sitting in my Real Analysis II lecture today when I started to listen to the words the professor was saying. “…the vector-valued function F has first order partial derivatives at x only if each F-sub-i have first order partials at x…” It’s completely unintelligible. I’ve been in this class for a semester plus a month, and I still have moments when I understand all the individual words that the professor is saying, but together they mean nothing to me. Take the course description. “Derivatives as linear maps, differentiable mappings, inverse and implicit function theorems. Further topics such as theory of the Riemann and Lebesgue integral, Hilbert spaces, and Fourier series.” The individual words make sense, but their combination is impenetrable.
The same is true in the computer science department. Even at a very basic level, there’s a whole slew of technologies, constructs, and ideas that lead to jargonized discussions. This means that to the casual observer, even low-level conversations are quickly obfuscated by the language used to describe the discipline.
The reasons for this excess of jargon stem from a couple of sources. First, both mathematics and computer science require a certain degree of precision. Particularly in math, it’s absolutely necessary that the theoretical object being described has an extremely precise definition, and this leads to strings of conditions and properties that it must satisfy—more words leads to more jargon. Both CS and math are continually growing fields. Newer technologies are developed, problem-solving techniques are created, theorems are proved, and every one of them needs a name.
This excess of lingo is absolutely necessary for the disciplines in question, but it has dangerous implications beyond the fields. Consider the freshmen who are interested in CS but don’t have any technical background. As they wander into Halligan, they encounter grad students working on AI research, Comp 40 students having urgent discussions about their latest projects, and professors chatting about the latest result in computational biology. Have I lost you yet? Halligan is the computer science building; AI is artificial intelligence; Comp 40 is a low-level programming class famous for students spending 40 hours per week in the lab (it’s an exaggeration, I promise), computational biology is the field devoted to using computational solutions to solve genetic problems.
The point is, it can be intimidating to walk into an environment where everyone seems to be speaking a different version of English. The best way to handle is to acknowledge that complete understanding won’t happen overnight. It’ll take a while to be fluent in CS, but the learning curve is steep, and two weeks of an introductory course will do wonders for the percentage of sentences understood. It’s like moving into a foreign country—sure, there’s a language barrier, but the are fantastic opportunities just beyond it make it absolutely worth crossing.