The number of students who want to learn AI has risen 200%, and there are not enough teachers to go around

Today, with the comeback of neural networks and the boom in deep learning -- there are so many students wanting to study AI that there aren't enough teachers in universities to go around.

One report shows that the number of students majoring in computer science in the United States triples from 2011 to 2020, from 60,661 to 182,262. But the number of computer science teachers has only increased from 4,363 to 6,230, an increase of less than 50%.

In other words, where one teacher used to teach an average of 14 students, now one teacher has to teach almost 30 students. Not only are teachers more tired, but the quality of instruction that students receive is no better than before.

So, why is the number of teachers in computer science not keeping up?

Number of teachers x 1.5, number of students x 3

This report is from the Center for Security and Emerging Technologies (CSET), a U.S. think tank.

The survey collected data from more than 140 computer science departments at public and private universities. Although the survey did not specifically count machine learning courses, the data from computer science departments is enough to illustrate the trend, according to the director.

As mentioned at the beginning, there are already three times as many students in computer science departments in 2020 as there were nine years ago, with significant increases in both undergraduate, master's and doctoral students.

And while the number of teachers is increasing, it's not keeping up with the number of students.

This situation has teachers complaining that their workloads are increasing and that they have less time for research.

The quality of education for students has also suffered: many schools have responded by raising admissions thresholds or eliminating small classes.