Getting schooled by AI, colleges must evolve

As we enter the age of AI, it becomes more important for knowledge workers to excel in their strengths, and aim big for some strikes instead of settling for a comfortable average all around.

How can colleges reform to endow graduates better?

Here are my opinions, for what they are worth.

Human skills for the AI era

In the age of AI, doing rather than knowing becomes more important. Shallow information is worthless, but mastery of principles, critical thinking, and synthesis is priceless.

Colleges should teach collaboration, entrepreneurship/innovation, communication/writing, and critical thinking and problem solving skills.

How can colleges reform to cultivate these skills?

First, they should transition from zero-sum mentality to the win-win mentality. This is not easy, because the system has been built on making students compete against each other and stack-ranking them. I don't know what kind of structural changes and scaffolding can help for this.

I have some practical advice for exercising these skills, though.

Flipped classes and discussion groups help a lot. Students can do the reading/learning before class, and the class time can be used for critical analysis, discussion, and debates as in the Harkness method.

A multi-year group project, with incremental delivery each semester, can help students cultivate entrepreneurship, teamwork, project management, and problem-solving skills. The students can change/rotate team members, grow their team, pivot their projects over the semesters. But they get to cut their teeth on ownership, dealing with customers, and learn accountability. The instructors should be following the progress of teams and individual development of team-members closely like Software Development Managers over time, and provide one-on-one coaching, and opportunities to improve themselves.

The instructors should challenge the students to learn from each other, and improve together, rather than compete against each other. They should encourage the students to take initiatives, run campaigns, and get things done.

Curriculum for CSE departments

CSE departments should revise their curricula by doing a cost-benefit analysis for all classes. Yes, there is benefit to teaching any old class, but what is the opportunity cost?

For the love of God, don't allow the students to take nothing but AI classes... Don't raise Tensorflow disk jockeys. They will be the first ones to get obsolete.

Teach databases dammit! That stuff is immensely useful in the real world, and involves both a deep theory and good amount of practice.

Teach compilers! Having a low-level and deep understanding of programming languages and programming is going to be very useful to the students. Generative AI models can do the shallow coding. The humans will be doing the critical analysis and design of the full-stack architecture.

Teach system design. Teach performance modeling of systems. Get the students to practice gluing components together without compromising the end to end performance and reliability.

And of course, teach TLA+. It gives students critical thinking and concurrent protocol design skills with rapid feedback.

To subdue deep learning, you have to learn deep, treat the AI as a tool, and master it.

As to methods, there may be a million and then some, but principles are few.
The man who grasps principles can successfully select his own methods.
The man who tries methods, ignoring principles, is sure to have trouble.
-- Ralph Waldo Emerson