Ignorance is normally described as an absence of knowledge. From this idea follows an almost self-evident conviction: those who know much understand more than those who know little.
A significant part of the organisation of modern society follows from this. We study to reduce ignorance, train specialists to improve decisions, and reward expertise because we regard it as protection against error.
Often, it is. No one wants to be operated on by an inexperienced surgeon or entrust a bridge to an engineer who struggled in exams. Yet there is a form of error that lies beyond expertise and is therefore difficult to recognise: it arises when someone accumulates knowledge without questioning the framework that gives that knowledge meaning.
All knowledge, in fact, operates within a structure of relevance. Some questions are considered important, others marginal. Some data are ignored. Some variables are left out. And so on.
This selection is the condition that makes it possible to know anything. No discipline, and no mind, can work on the whole of reality at once.
No cognitive system, human or artificial, processes the world: it selects a small part of the world and makes it tractable. True intelligence, then, lies in being able to see what one’s own process of selection has excluded.
A manager may spend months discussing how to increase a product’s market share by five per cent. They may gather data, build sophisticated models, segment customers, analyse competitors, and so on. Yet perhaps the right question would have been whether that market would still exist the following year, and in what form. Or whether technological conditions already exist that could render the product category irrelevant.
Expertise allows us to answer a question precisely. Understanding requires us to question the question itself.
The same phenomenon appears in scientific research. An entire community may devote years to refining theoretical tools, methodologies and experimental procedures, while in the meantime the original problem may have lost its central importance. A discipline may continue to generate sophisticated results around an increasingly unimportant question. The quality of the work may improve while the relevance of the overall framework declines.
These examples reveal an often overlooked characteristic of expertise. Specialist knowledge increases our ability to operate within a frame of reference. It does not automatically guarantee the ability to observe that frame from the outside.
For this reason, the greatest risk lies in believing, on excellent grounds, in something epistemically impoverished.
From this perspective, some human expertise bears a surprising resemblance to what is often held against artificial intelligence. An AI model operates within a structure it did not build. It uses data, categories and objectives defined elsewhere. It produces well-crafted results but displays considerable difficulty when the problem requires it to question the framework that makes its own functioning possible.
Many professionals work in a similar way, since they operate within categories they have neither chosen, investigated nor understood. They use criteria of relevance they have inherited. They refine tools that presuppose particular definitions of the problem. The quality of their work may be high. Their dependence on this invisible schema may be equally great.
There is knowledge of content, and there is knowledge of the conditions that make that content meaningful.
The first allows us to solve problems. The second allows us to understand which problems deserve to be solved. The first produces an obsession with efficiency (which is efficiency’s debased form). The second produces judgement.
Organisations, universities and professions invest enormous resources in the first. Far less frequently do they cultivate the second.
Yet it is precisely in the second that one of the most sophisticated forms of intelligence manifests itself. The ability to see the box from within, to ask whether the current interpretative framework represents one possibility among many or really is the only one. Sometimes what appears natural is often the result of a forgotten selection.
This kind of awareness does not eliminate schemas. No one can think without schemas. It does, however, allow us to treat them as tools rather than as self-evident truths.
Traditional ignorance arises from a lack of knowledge. This new form of ignorance arises, even in the presence of knowledge, from the absence of the conditions and boundaries of knowledge itself.
Thus, according to this article’s thesis, the new ignorance consists in never having questioned the criteria by which we select what, in reality, we consider worthy of being known.