This past week, I was delighted to join Dr. Vera Kamtukule - former Minister of Tourism in Malawi, as a guest on her new podcast: The Leadership Lab with Dr VK.
We got into conversation about entrepreneurship, about innovation, and about whether Africa is truthfully prepared and ready to partake in the fourth industrial revolution.
This is part 1 of a 3-part conversation. Have a listen, and please subscribe to her channel, so you do not miss the next episodes.
Two Questions
I recently finished reading two books: I Am Not a Robot, by Joanna Stern and Co-Intelligence by Prof. Ethan Mollick. I found the pairing useful because the two books approach AI from different but complementary directions.
Mollick’s Co-Intelligence is primarily concerned with how people can work with AI. His framing is I find extremely practical: how to collaborate with AI, how to remain the human in the loop, how to use AI as a co-worker, tutor, coach, or creative partner, and how to adapt to tools that are still improving rapidly.
Stern’s I Am Not a Robot approaches the question from the side of lived experience. Her work is less about AI as an abstract technical system and more about what happens when AI enters daily life: work, learning, intimacy, decision-making, productivity, attachment, automation, and the uneasy boundary between assistance and replacement.
What I found interesting is that very little in these books felt completely new to me - this was a delight. I do not say this in any way to criticise these books. It is likely just [great!] evidence that I have become an extreme AI user over the past two years.
Business school did that to me. The workload required reading, analysis, writing, presentations, strategy, modelling, research, and constant synthesis across different subjects. AI became part of how I managed that pace.
This is what I think both books do well: they give language to patterns many heavy AI users already experience but may not have fully named. Mollick helps explain how to work with AI deliberately. Stern helps explain what that work may be doing to us.
Ladder of Learning
In I am Not a Robot, Stern discusses the Bloom’s Taxonomy. First developed in 1956, the taxonomy organized learning objectives in the cognitive domain into levels: knowledge, comprehension, application, analysis, synthesis, and evaluation. It became one of the most widely used frameworks in education because it helped teachers and institutions think about different depths of learning.
In 2001, the taxonomy was revised by scholars including Lorin Anderson and David Krathwohl. The revised version shifted the categories from nouns to verbs and reordered the upper levels. The familiar revised sequence is: remember, understand, apply, analyze, evaluate, and create. This revision matters because it reframed learning as active performance rather than static possession of knowledge. A learner is not simply expected to have knowledge, but to do something with it.
Four Rules
Mollick’s Co-Intelligence is useful because it frames AI not merely as a tool to be used occasionally, but as a collaborator that must be managed deliberately. The four rules he offers are quite practical in my opinion: always invite AI to the table; be the human in the loop; treat AI like a person, but specify what kind of person it should be; and assume this is the worst AI you will ever use.
This is the balance I keep returning to. AI is powerful enough to help people learn. It is also powerful enough to help people avoid learning. It can accelerate mastery. It can also simulate mastery.
Have a listen wherever you get your podcasts, or read the full article via my blog: Mastery.
