Turn insights into solutions

Understanding human behaviour has always been the hardest analytical problem — not because people are irrational, but because the forces shaping what they do, feel, and choose operate largely below the threshold of conscious awareness.

 

Bourdieu's logic of practice describes this precisely: human actions stem from dispositions acquired through socialisation that feel like instinct, common sense, the obvious way to do things. They are not. They are historically produced, socially maintained, and largely invisible to the people performing them.

 

The analyst who takes what people say at face value is engaging with the surface of a much deeper structure. The analyst who reaches that structure does so not by asking better questions alone, but by developing the kind of trained attention — cross-cultural, cross-disciplinary, genuinely curious — that makes the invisible visible.

 

This is the context in which generative AI enters analytical practice — and it is a context that defines both what AI can do and what it cannot. AI tools are genuinely useful: they accelerate pattern recognition across large bodies of material, support inspiration and translation, and extend the range of what can be explored in a given time.

 

The limitations are equally real. The veracity of AI-generated statements remains uncertain — errors, whether factual or inferential, are becoming harder to detect as outputs become more fluent. More structurally, AI systems optimise for what they have been trained to optimise for which shapes every output in ways that are not transparent. Algorithms optimising for efficiency and predictability tend to strip away precisely the richness and contradiction that genuine understanding requires.

 

Human analysts do something different — and the difference is not simply that they are more careful or more experienced, though both matter. It is that they bring to the work a capacity for the kind of reflexive, lateral thinking: the ability to make the familiar strange, to hold multiple frameworks simultaneously, to recognise when the available categories are producing a false picture rather than revealing a true one.

 

Research on insight shows that the most significant analytical breakthroughs come not from processing more information within existing frameworks but from the moments when a contradiction, a coincidence, or a connection across domains produces a genuine reorientation of understanding. That capacity cannot be just prompted into existence. It is cultivated — through genuine engagement with diverse fields, through the kind of “trained intuition.”

 

The analyst is not a prompt engineer. They are someone who knows where to look, how to dig deeper, when to trust a finding and when to interrogate it, and how to translate what is discovered into something that connects to the real complexity of human experience rather than a simplified version of it that fits the available tools.

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"It ain't what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so."

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This quote is commonly attributed to Mark Twain, including in the opening of The Big Short. However, its authenticity is disputed, and there is no definitive source linking Twain to this phrasing. Regardless of its origin, the idea can be traced back to Plato’s Sophist, albeit in a less punchy form (here in Benjamin Jowett’s translation).

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STRANGER: I do seem to myself to see one very large and bad sort of ignorance which is quite separate, and may be weighed in the scale against all other sorts of ignorance put together.

THEAETETUS: What is it?

STRANGER: When a person supposes that he knows, and does not know; this appears to be the great source of all the errors of the intellect.

THEAETETUS: True.

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