Openness, knowledge and the discipline of unlearning

The lesson gives you a repeatable method for picking up unfamiliar tools. This page explains why openness is treated as a trainable competence, and why expertise is both the asset and the obstacle.

Being open as a competence

Goller and Bessant list being open among the four individual competences for creativity, alongside exploring problems, building willpower and self-awareness. Placing openness in that list is a claim: it is not a personality type you either have or lack, but a set of behaviours that can be identified, practised and measured.

Their broader argument applies here with force. We have known the success factors for innovation for decades, and organisations keep failing to apply them — because a factor only changes anything once it is translated into behaviours people can actually perform. "Be more open to new technology" is a factor. "Each member learns one tool in two hours and teaches it to the others" is a behaviour.

The discovery skills are learning behaviours

Return to Christensen's five discovery skills from Lesson 1: associating, questioning, observing, experimenting, networking. Four of the five are, in effect, ways of learning. Questioning is how you find out what you do not know. Observing is how you notice what documentation does not say. Experimenting is how you find a system's boundaries. Networking is how you reach knowledge that is not in your head or your files.

Associating — the most powerful driver in their study — depends on all four, because you cannot connect things you have not encountered.

Adair's input chapters are the same argument in older language. Curiosity he calls the appetite of the intellect and the mind on tiptoe, developed by the simple practice of asking more questions of others and of yourself. Observation he treats explicitly as a trainable skill, noting that our interests programme us to notice some things and not others. Listening requires humility and the control of one's critical urges, with comprehension preceding evaluation. Reading for ideas means skipping, skimming and digesting rather than plodding — being a speed understander rather than a speed reader.

His most useful line for someone teaching a tool to five people next week: a person is judged not by their answers but by the questions they ask.

Knowledge is not automatically an advantage

Dawson and colleagues devote a section of their chapter on the individual to knowledge, and ask a question most textbooks avoid: is knowledge always conducive to creativity, innovation and change?

They distinguish formal or explicit knowledge — codified, written down, transferable — from informal or tacit knowledge, which is held in practice and experience and is difficult to articulate. Both matter, and tacit knowledge is typically the harder to transfer and the more valuable to a team.

The answer to their question is: not always. Deep knowledge of a domain builds strong patterns, and strong patterns constrain what you can imagine. Goller and Bessant name the same double edge through Dorothy Leonard's deep smarts: expertise lets you see patterns and variations others miss, and simultaneously narrows the range of alternatives you consider. They add the concept of domain specificity — someone highly creative in one field may not be in another.

Adair states the consequence most bluntly, in his chapter on widening the span of relevance: too much knowledge may be a disadvantage — we must learn to unlearn.

This has an immediate implication for teams. The most experienced member is the one whose assumptions are least visible to themselves. The newest member's naive question is not a gap in their preparation; it is a diagnostic instrument. Someone senior claiming a topic they know nothing about, and being visibly bad at it in front of younger colleagues, is not a morale gesture — it is unlearning performed in public.

Why concentrating knowledge in one person is a structural risk

Two research threads converge on the practical lesson's central instruction.

First, social loafing. Dawson and colleagues identify loss of personal accountability and coordination loss among its causes — people disengage when their contribution becomes unidentifiable or when they feel dispensable. A team in which one person handles all technical work has manufactured both conditions for everyone else.

Second, self-efficacy. Clapham and Meyer identify it as one of the four mechanisms through which leadership affects creativity: the belief that one can accomplish a task, which operates most strongly where people believe their work is valued. Every time the technical person does the task instead of teaching it, everyone else's self-efficacy for that task stays at zero — and self-efficacy is a cognitive force for creativity, not a nice feeling.

Their finding on autonomy reinforces this. Leadership that gives people room to pursue their own approaches promotes creativity; authoritarian arrangements that minimise autonomy in decision-making are associated with less of it. A team where all technical decisions route through one person has centralised decision-making without anyone intending to.

Learning to work with AI systems

Because much of what anyone must learn now involves generative tools, it is worth noting that this too is being studied as a skill rather than a shortcut.

Oppenlaender, Linder and Silvennoinen investigate prompt engineering as a creative skill in AI art — framing the ability to direct a generative system as learnable and unevenly distributed. Pranandari and Aoyama examine AI competence and innovation in the creative industries and find individual creativity moderating the relationship: what someone gets out of an AI system depends on the creativity they bring to it. El Saddik and colleagues survey the broader landscape of generative AI and multimodal content.

The practical consequence is the test in the lesson. If you cannot explain what you just did, you produced something rather than learned something — and someone who cannot explain their own process cannot repeat it next year without the same help.

Teaching as the completion of learning

The final step of the protocol — teach someone else — has support from several directions at once. Goller and Bessant's emphasis on translating factors into observable behaviours; Adair's rule that observation is not complete until you have recorded what you saw, and his instruction to develop curiosity by asking questions aloud; and the finding across the team literature that shared knowledge is what makes a team robust to any individual's absence.

A guide written by someone who was confused four days ago is also, for straightforward reasons, better than one written by an expert who has forgotten what was hard.