Is Computer Science Education Still Worth It? Let History Be Your Guide
Computer Science education has gone through boom-and-bust cycles before.
The best-known ones happened in the mid-1980s after the PC boom and in the early-2000s after the dot-com boom. There are reasons to believe that computing in general will recover from the current bust, but there might be a shift away from basic computer science to data science and artificial intelligence (two closely related fields).
One needs to remember, however, that in order to be an effective data scientist or AI engineer, a basic understanding of computer science is essential. The idea that programmers will not be needed anymore is a sentiment as old as computer science itself. When the first higher level programming languages were developed (COBOL, FORTRAN) their inventors believed that these languages were close enough to English so that "anybody" would be able to write programs. They were spectacularly wrong.
As in the stock market, the best time to buy is when others sell because of unfounded concerns. Even in a market that is less than bullish at the moment, NJIT computing grads are in demand. If the number of computing graduates shrinks nationally, those with a pedigree from NJIT and universities with strong computing programs will have an even greater abundance of opportunities to select from, and that will be an enviable position. Make no mistake, this is a long-term buying opportunity for the savvy educational investor.
Jim Geller is professor and chair of the Department of Data Science in the Ying Wu College of Computing at NJIT. He received his M.S. and Ph.D. degrees from the State University of New York at Buffalo in 1988 in Computer Science, with a focus on AI/Knowledge Representation. Professor Geller cofounded SABOC (the Structural Analysis of Biomedical Ontologies Center) at the Department of Computer Science at NJIT and has published over 200 journal papers, conference papers and book chapters in medical informatics, semantic web technology, object-oriented database modeling and knowledge representation.