Today’s Tuesday Reading is from Dr. Szymon Machajewski, Associate Director of Academic Technology and Learning Innovation at the University of Illinois Chicago and a MOR participant. Szymon is also the author of The Learn-It-All Educator: A Guidebook for Training Brains, Not Replacing Them. He may be reached at [email protected] and via LinkedIn.
In early 2023, my team and a handful of early-adopter faculty were among the first to explore generative AI tools for teaching and learning. We were deep in it: working directly with vendors like Microsoft, presenting at conferences, delivering keynotes. We saw the potential before most of campus did: AI-generated rubrics, automated quiz questions, entire course modules assembled from a prompt. It felt like the future. And almost nobody else wanted it.
The early-adopters were enthusiastic; it is their nature, and nothing will stop them. But the broader faculty population did not follow. Instructors were not excited about AI-generated rubrics because many of them had never used rubrics and did not see why they should start now. They already loved their familiar exams and trusted assignments. AI-assembled course content felt synthetic and foreign, something to be rejected rather than adopted.
I spent weeks trying to understand the resistance and building better arguments: you will save time, you can redirect energy toward more meaningful student interactions, and you can lead during this transformation. None of it landed. And then it hit me: these were not their problems. They were ours. Our team wanted to be the heroes for the ones we saw as technically challenged, and we were so invested in being the ones with the answer that we never paused to ask whether we were solving the right problem.
That experience taught me something I have been thinking about ever since, something my participation in MOR has sharpened considerably: the biggest barrier to learning is not ignorance. It is the need to feel like you already know.
The Ego Trap and the Question of Presence
In that early adoption work, I witnessed two ego barriers operating at the same time. Faculty could not hear our solutions because acknowledging a problem meant admitting their familiar practices might be insufficient. And our technical team could not hear faculty because admitting our solutions were unwanted meant confronting the possibility that our expertise was pointed in the wrong direction. Both sides were protecting what they knew rather than learning what they did not.
MOR’s framework for leadership presence asks us to consider how we enter a situation, what energy we bring, how we engage, and how others assess the ethos of our character. The ego trap corrodes all four. I entered those conversations ready to solve, radiating certainty, engaging by persuading rather than inquiring. I was not showing up as a leader. I was showing up as an expert defending my territory.
Where in your own leadership are you still trying to be the person who already knows, when your organization most needs you to be the person who is visibly learning?
Permission to Not Know
MOR’s founder, Brian McDonald, put it simply: the proof you have learned something is in your ability to do something at an increased capability. The outcome is that you cannot increase capability without first confronting what you do not yet understand. That means giving yourself permission to be a beginner, deliberately, privately, and without apology.
After that early adoption experience, I started using AI differently. Not to generate solutions for others, but to process my own ignorance safely. When I encountered a technology or a pedagogical argument I did not fully grasp, I would type the basic questions into an AI tool, the questions that felt too elementary to ask in a meeting of peers. I started thinking of this as a judgment-free zone: a private space where the cost of asking a naive question is zero.
This is not a replacement for the human connections that MOR’s 4 I’s, initiate, inquire, invest, influence, are designed to strengthen. The goal is to show up to those connections better prepared. When I finally understood a concept well enough in private, I could engage with colleagues about it in public without the ego barrier distorting the conversation.
The Immediate Versus the Important
None of this learning happens if your calendar is consumed by operational noise. MOR participants will recognize this as the tension between the immediate and the important: the crisis of the day versus strategic priorities, developing talent, and building relationships. Your calendar is a strategic asset.
A useful shorthand from my own work: some tasks are what I call FLUFF, Formatting, Layouts, Under-the-hood logistics, Filing, Filtering. They have capped payoffs. Others are SPARK, Specific, Persuasive, Authentic, Rigorous, Keen-Insight. They have uncapped returns. Looking back at that early AI push, I was spending my time on SPARK-level strategic work but treating it with a FLUFF mindset, rushing to deliver features instead of pausing to understand the human problem underneath.
Can AI compress two hours of FLUFF so you can get off the dance floor and onto the balcony for SPARK? Leaders who have practiced defensive calendaring know the discipline of protecting time. AI is a new tool for that same habit. But the lesson I learned the hard way is that reclaiming time is only half the shift. What you do with that time matters more: learning, questioning, listening, not just solving faster.
The Learn-MOR Habit
MOR holds that sustainable behavior change happens when individuals adopt new practices and develop new habits. The shift from know-it-all to learn-it-all is not a one-time declaration. It is a practice, built one week at a time. The question is not whether your organization needs AI literacy. It is whether you, as the leader, are willing to go first.
Pick one practice and try it this Tuesday. Say “I don’t know yet” in a meeting and notice what it does to your presence. Label each calendar block as FLUFF or SPARK and use AI to reclaim one block for strategic work. Before launching your next technology initiative, consider whose problem you are solving and bring that to the room. Or publicly share something you learned this month that changed your thinking, so your team sees that learning is the expectation, not the exception.
I wish I had done this in 2023. I wish I had walked into those early conversations and said, “I think we are building the wrong thing, and I want to understand why before we build more.” That would have required a kind of courage I did not yet have. MOR has helped me name it and practice it. The technology will keep changing. The question is whether you will keep learning, and whether you will do it visibly enough that your organization learns to do the same.
Where in your own leadership are you most trying to be the person who already knows, when your organization most needs you to be the person who is visibly learning?
Last week, we asked which helps you most when you’re trying to keep momentum strong:
- 30% said habits or routines
- 26% said someone to hold you accountable
- 26% said a deadline
- 18% said someone to work with on the goal
Collectively, we need structures to keep momentum going. Forms of structure include habits, routines, accountability, and deadlines. This is true for any area of life. When you specifically think about your own continued development as a leader, what is one way you could increase your momentum?