AI Investor Forum: Gus Tai on AI in Education (Part 6)

Sramana Mitra: we just discussed very thoroughly the K through 12, but in higher education, where we are dealing with much more complex topics and material, having the framework of a college or a university framework of teachers and professors, having a grading system or a degree system etc. and being part of that construct is actually helpful.

Then, you augment that with AI with this infinitely patient, infinitely knowledgeable AI teacher who can teach each of those subjects at a very deep, very complex, personalized level. I think that is still the best model to develop that kind of knowledge. Then, a much larger number of people will actually learn – not just the self-motivated ones; the self-motivated ones are already learning.

Gus Tai: Yes. So, your last point really resonates with me. Self-motivated people can learn however they want to learn.

Learning is metabolically taxing. We, as living organisms, learn so that we could engage and act, but learning is inefficient with respect to action, and we’re oriented more toward action. This is active inference neuroscience theory, which I buy into.

So, if you’re trying to learn something that doesn’t motivate us, community gives us energy; societal norms and culture gives us the framework and support to be able to develop new habits and use historic habits with respect to culture and apply them to have the activation energy to engage in this metabolically fatiguing activity. I just think the social construct, whatever it may be, is really beneficial to help people who aren’t self-motivated in all contexts.

Sramana Mitra: Right. So, on the education topic, there is one other discussion I want to have, and then we are going to close off this segment and switch to the mentoring session. We’re getting to a world where AI is automating vast amounts of human activity through robotics, through software automation AI agents, etc. At the moment, coding is also on the block – coding could become 40% automated. These are very big societal fields.

What do we educate people for in a world where there is such a huge amount of automation? I’ve been thinking about this for a long time actually.

AI is augmenting the human’s capacity to teach. So I think there’s, there could be a much larger number of teachers who are AI augmented and can take on a lot more and teach a lot more effectively.

I think teaching could and should become a much more active profession with a much larger number of jobs. What do you think, Gus?

Gus Tai: That is a possibility. The dilemma is that with this introduction of a new technology, just like the introduction of the smartphone, has really caused the fragmentation of attention of individuals. Given that massive corporations monetize people as part of the product, not as a customer, by monetizing attention, AI as it rolls out, may wind up causing most people to lose the practice of learning.

If learning is metabolically fatiguing and there are shortcuts to learning things superficially versus this deliberative intentional practice, then it may weaken the muscle for the customer base to want to learn the way you want.

I think that for your vision to manifest, it requires a cultural development and movement in that way. Societies have had waves towards these types of social norms. I think the direction we’re in right now is maybe too tactical of how do we get a skill that allows us to vocationally do something and in the act of engaging, finding pseudo meaning. However, once that job is automated away, like many jobs in financial organizations within a company where it’s around manipulating numbers, what am I left with?

I would love to see your vision happen. A lot of stuff has to develop for the culture to have that mindset. I believe we’re not heading in that direction right now.

Sramana Mitra: We’re not heading in that direction. Yes, I think that is correct. One of the concrete examples of what you’re saying is that in American colleges and universities, the most popular major for undergraduates is psychology. When people cannot come up with a major, they identify themselves as a Psychology major. Psychology doesn’t warrant having that many majors. Number one, it doesn’t have that many jobs. It’s kind of like a cop out. It takes a lot of work to be a Physics major or a Computer Science major, or a Biology major or a pre-med; and psychology is a cop out.

So, your point is very well taken in that the desire to learn complex difficult stuff is already dwindling. This is a good segue into the other possibility where jobs could be created in large numbers is healthcare.

We will dive into healthcare next time. Healthcare is developing very well, and there is a very real future possibility where AI augmented healthcare is going to be far superior than where we are today. Many more people can provide healthcare augmented by AI.  So that’s another class of jobs, but it’ll require studying Biology, it’ll require understanding. You can take the shortcuts and the AI augmentation, but you still have to understand Biology. You have to still understand some of the basics of how things work in the human body to be able to provide healthcare.

Well, we are going to wrap up there, Gus. That’s great as I expected. We’ll continue next week.

Gus Tai: Thank you, Sramana. Bye.

This segment is part 6 in the series : AI Investor Forum: Gus Tai on AI in Education
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