What a person becomes when the machine takes the part of the work that used to prove they were good at it, and which human capacities grow more valuable, rather than less, the more execution is automated.
Competence was always demonstrated by execution, and execution was never competence. It was the proxy, welded to it only because the work could not be done without the faculty that did it. Automation is cutting that weld. This paper specifies what was always upstream of the visible work, and why it appreciates exactly as execution becomes abundant.
For all of working history, competence was demonstrated by execution: the person who could produce the document, the analysis, the coordinated result was judged competent by that visible fact. Execution was never competence. It was the proxy for it, welded to it only because the artefact could not be produced without the faculty that produced it. Automation is cutting the weld. This paper specifies what was always upstream of the visible work, judgement under uncertainty, calibration, sense making, the trained felt sense that something is wrong, and the origination of direction, and shows why these capacities appreciate as execution becomes abundant. It is equally honest about the mechanism, named in human factors research in 1983 and confirmed every decade since, by which the same automation erodes those capacities silently, because the confidence that masks the erosion does not fall with the competence. The deciding factor is not the model. It is whether a deliberate structure keeps the human inside the practice loop that builds judgement.
Competence was equated with execution only because, until now, the artefact could not be produced without the faculty that produced it. Automation cuts that weld, and a bright output no longer evidences anything at all about the human faculty that used to stand above it.
When a productive input becomes abundant, value moves to the adjacent thing that did not. Competent execution is the input becoming abundant. Judgement, calibration, sense making, the felt sense of wrongness, and direction are the adjacent things, and none of them is what the machine produces.
A capacity can decay completely while the feeling of possessing it stays at full strength, because the feeling was never reading the capacity. It was reading familiarity, and an automated environment stays familiar long after the competence in it has gone.
A tool that is right almost always trains attention away fastest, because there is almost no corrective experience to reset it. Better models do not retire the human checker. They disarm them, on a schedule set by how reliable the tool is.
Kahneman and Klein specified, for a different dispute, the two conditions under which skilled judgement is real: a learnable environment and feedback bearing practice. Automation acts directly on both, in either direction, depending only on how it is structured.
The practice loop is not preserved by giving the human what is left over. It is preserved by routing consequential, uncertain work to the human on purpose, because the point of the work is no longer only the output. It is the maintenance of the faculty needed when the output cannot be trusted.
This is the rare argument of its kind that terminates in something a person can build rather than only brace for. Whether the capacities emerge or quietly drain is not decided by the machine. It is decided by whoever maintains the layer that holds the practice loop open.
A person being hollowed by automation does not feel hollowed. They feel exactly as sure as they did before, and the output in front of them stays bright the entire time.
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