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

Another important reason the report unveils here is that schools are actually not keeping up with the pace of hiring.

Look at the graph below to understand. From 2006 to 2020, the difficulty of recruiting teachers for college positions has remained basically flat, without much increase.

We can deduce that the most logical explanation for the relatively slow growth in the number of teachers is the lack of recruitment efforts.

So, are schools deliberately not hiring? They are fully aware of the shortage. The report states that the main reason is that there is not enough money.

In general, the cost of computer science is much higher than that of humanities, but government funding is growing slowly, and for many schools with more rigid budgets, they will have to bear the cost of recruiting additional teachers or reduce the subsidy to the original teachers after spending a lot of money to accept more students and offer more courses.

Both of these options face significant internal resistance to implementation. As a result, the number of teaching positions has not been able to keep up with the growth in students.

A few suggestions

If this shortage is not addressed, the consequences are also clear, with the most serious impact on doctoral students. Surveys show that doctoral enrollment has grown the slowest in recent years compared to undergraduate and master's students, and this is closely related to the growth in the number of tenure-track faculty.

Due to limited mentorship, many applicants who have not published in top journals are rejected, a requirement that is actually quite high. In turn, the slower pace of doctoral production can further limit the supply of qualified faculty at colleges and universities.

At a deeper level, this phenomenon is also detrimental to the long-term development of the AI field. The most intuitive manifestation of this is that teachers are consumed with teaching tasks, so how can they find time for research? After all, industry is more focused on profit and less likely to create fundamental advances.

So, what should be done?

This report also concludes with some recommendations.

(1) Academia: Keep it simple and brutal and increase funding.

(2) Industry: encourage employees to teach in schools at the same time.

(3) Government: provide more data and basic computing facilities for schools so that talented people do not go to industry because schools do not have enough resources.