A group of largely education-focused colleagues have been meeting on Sunday evenings for 45 minutes of thought generation and leadership support. As we struggle with how to restructure an education operating system alongside rapidly-evolving AI, one colleague posed this theorem as the overriding mission of education:
“The only way to know that AI is not taking us for a ride is mastery… and the (most effective?) path to mastery is purpose.”
This prompted me to think about the intersection of AI, human skills, and education in a slightly different way than the excellent framework set out by Joy Case in her article Education in the Age of Artificial Intelligence, which I have embraced and shared with my edu-leader colleagues.
We probably have a relatively strong set of agreements about what “mastery” is as an end result. We know what mastery looks like in art, athletics, science, business, leadership, and probably in less quantifiable areas of human endeavor like marriage, child-rearing, and community service. We won’t agree on every element of mastery, but probably on the big strokes.
I focused on what skills, traits and characteristics that lead to mastery as an outcome are those that humans will continue to excel at more than AI, and which should we, or inevitably will we, learn to off-load or partner with AI on.
I came up with this prompt:
What skills or traits help us toward attaining mastery in ways that humans excel at better than AI? I am in the process of crowd-sourcing 1-2-word responses from thoughtful humans I know or encounter, and I will share those results. This will probably take a long time to gather in any reasonable numbers.
In the meantime, I directed ChatGPT to “Conduct a deep search of articles on AI and human cognition and performance. Create a list of the traits and skills that humans will most likely continue to excel at more than AI in the foreseeable future?”
The AI used four primary sources, which appear to be reasonably authoritative:
Stanford AI Index 2025 — Technical Performance
OECD AI Capability Indicators
Microsoft Research — Generative AI and Critical Thinking
World Economic Forum — Future of Jobs 2025
The top skills or traits on this response list are:
1. Purpose, or “What should I devote my life to?”, tied to values, morality, relationships, identity, meaning and personal experience.
2. Wisdom: The AI found that, “…AI’s major limitations increasingly involve novelty, ambiguity, uncertainty, cooperation, safety and context—what the authors characterize as a lack of wisdom.” Where AI will excel at, “Can you solve the problem?”, wisdom requires us to answer questions like, “Should we solve this problem?”; “Whose interests matter?”; “When should we act or not act?”; “What are we missing?”
3. Moral or ethical judgement, which in the human/real world involves consequences, responsibility, competing values and legitimate disagreement, for which there are not necessarily data-driven answers.
4. Lived experience. AI can describe emotions and experiences like grief, falling in love, raising a child, losing a parent, and physical pain, but it does not live those events. The actual embodiment of those life experiences suggests that AI can write an essay, but it cannot rival humans as an authentic storyteller with the authority of “This actually happened to me.”
5. Empathy and Compassion: AI is getting quite good at producing responses that humans perceive as empathetic. But as we learn to partner with AI, we should realize the distinction between artificial empathy and a human who can actually understand because something similar happened to them, which never happened to an AI.
6. Passion and intrinsic motivation, which may include joy, and dogged determination, the traits that highlight many people who we perceive to have achieved mastery. AI optimizes our pursuit of a goal but it does not care about the goal. Everyone I know who has achieved mastery, has cared deeply about their goal.
7. Courage involves fear, uncertainty, and consequence. AI can recommend a courageous course of action, but the human has to actually take the risk, and mastery always requires risk-taking in one or many forms.
Seemingly extrapolating beyond the primary resources it digested and cited, the AI added one overarching capability which really ties together all of the other human-centric superpowers…
Knowing what matters.
This is worth pondering. Does “knowing what matters” lie at the heart of cognition and metacognition in the era of AI? How might we amplify teaching discernment as a critical human-centered skill? Is this the one skill humans should never yield to AI, no matter how much the AI tells us that it is good at it? Does discernment lie at the root of our fear that HAL 9000 will not open the pod bay door on demand?
Does this become, an extremely critical pillar, if not the core, of all education missions around which subject, curriculum and skill building revolves, now and in the AI-partnered future?
What do you think? Share!
Thank you Grant! As iron sharpens iron, you have brought this Most Important Conversation to the forefront. It will be interesting to see what "Mastery" looks like in the coming years. Stay Human!
The list that AI came up with, and the final item ("Knowing what matters."). It seems to me they all represent or require an embodiment that AI cannnot (yet?) achieve.