The Four Pillars for an AI Education: How It Started, How It’s Going.

A few months ago, I let you in on what I thought were the main pillars of a well-rounded AI education.

Currently, the focus is solely on one pillar: engineering. So courses abound on the latest models and deployment techniques. This is not what the world needs at the moment. Standing on that one pillar creates a difficult equilibrium. When it finally collapses, the fallout won’t be pleasant.

As I mentioned in The Building Blocks for an AI Education — and the Courses That Built Mine, that one pillar was my entry point into AI. Five years ago there were already many talks about AI, and something that always propels me to learn, is to know what “the heck” I am talking about. Something I wish was a recurrent propeller to other people as well. ;)

Fast forward a few years, and particularly since the launch of ChatGPT last year, AI conversations have become more frequent. It’s safe to say AI has been one of the most discussed topics in business and society for several months now.

However, the gaps I identified in my educational journey — specifically, the other pillars required for a balanced AI education — continue to be absent from the conversation or are disproportionately represented compared to engineering.