I mean, let's look at the silver lining here: it might be good to stop climate change...

unless the machines are hell bent on expansionist mass production of other machines without regard for the environment. Maybe it would be worse.

But if they have sentience, and view us as a threat, or simply a lesser life form and a plague to this planet, then maybe they have enough insight to want to preserve the natural state of the world, sans Homo Sapien.

So far my experience in university, aside from a few smaller classes, is that a professor giving a lecture in a big hall is not a lot different from this. The delivery in a large lecture leaves a lot to be desired. I actually prefer watching videos of lectures, and only going to office hours to get more insight if that's necessary. Even office hours are rushed though!

It would great to have general artificial intelligence professors, like a super advanced futuristic version of Knewton. I think there's potential in this technology IMHO.

The author explains that we will be able to use what we learned from this chapter to develop a framework for decision making about use of technology and teaching in a digital age with a set of criteria and values.

Canadian researcher Donald Hebb was a pioneer in the area of brain plasticity...researcher Frank Rosenblatt in the US used Hebb's researched to base his work on the "perception" algorithm which is the basic elementary form of modern neural networks in artificial intelligence.

I never realized that "retrieval practice" was required for the most effective kind of learning. Nobody ever taught me that, even in university until a few years in. I learned the concept from a book called "Mind For Numbers" by Dr. Barbera Oakley. This is truly the best kind of learning. Practice testing!