Where are the learning loops in your career story?
If you’ve read Zen and the art of motorcycle maintenance, you’ll remember a section about a hypothetical student who enters a university where they teach but don’t have exams or grades.
The student turns up. Comes to some lectures. Finds partying more interesting. Skips a few. Finds the later material hard. Doesn’t put in the work to catch up.
As there are no exams or grades, there are no consequences. Eventually the student decides it’s not worth the trouble and drops out.
Now the student has to find something else to do. Perhaps a job to make money. Maybe as a mechanic. Finds that’s interesting. Works at it. Gets better. Wants to make some modifications. Realises that he or she doesn’t know enough. Maybe needs to learn more about mechanics and electrical. Joins a college or university.
This time the mindset is different. The student is driven to learn, because he or she really wants to know more about this subject. It’s intrinsic motivation rather than extrinsic recognition.
That’s a learning loop in action. And the interesting thing is that real learning often starts with practice – with taking action in a situation.
I did an MBA after around eight years of working. The theory I learned in the MBA helped explain the previous eight years. Following that, the continuing work and reflection informed my practice after that, which in turn led to more theory work as I tried to understand the previous experience.
I’m wondering how AI will improve these learning loops – and I think it may be at the level of theory.
It’s easier to work with AI to dissect and understand complex theoretical ideas. It can help us make sense of a large body of knowledge and connect and surface insights that it might take us years to do ourselves.
But the practice and reflection – that’s time we have to spend to apply and internalise the theory.
AI’s main promise, as far as I can see, is that it will help us become better learners.
Handcrafted insight 