The missing rung

Every knowledge-management deck arrives eventually at the same pyramid. Data at the base, information above it, knowledge above that, wisdom at the point, four tiers in a tidy triangle that nobody in the room questions because it looks like arithmetic. The picture is doing far more work than anyone notices, and a good deal of that work is wrong.

The popular version is already a corruption of its source. Russell Ackoff formalized the hierarchy in 1989 in From Data to Wisdom, and his own scheme carried five levels rather than four, with understanding sitting between knowledge and wisdom. Ackoff also offered a composition estimate for the human mind that survives as the most useful sentence in the paper: roughly forty percent data, thirty percent information, twenty percent knowledge, ten percent understanding, and virtually no wisdom. He was not being modest on our behalf. He was pointing out that the top of the pyramid is nearly empty in people too, which is a strange thing to expect a machine to fill by scaling.

The dropped rung is where machine systems stop, and they stop there cleanly. Statistical correlation carries a model from data to knowledge better than any human process ever has. What it does not produce is the grasp of why one thing bears on another that lets a person say this case is the earlier case wearing different clothes.

But the deeper trouble is the staircase itself. A ladder implies that every rung is made of the same material as the one below it, differing only in altitude, so that enough of the third rung eventually becomes the fourth. Watch what happens when an organization believes that. MD Anderson and IBM began building a cancer advisor on Watson in 2012, and by the time the collaboration ended in 2016 the project had consumed roughly sixty-two million dollars, thirty-nine to IBM and twenty-three in consulting support. The system was not in clinical use when it ended, and the agreement governing it stated plainly that it was not ready for clinical use and that using it to treat patients was prohibited. The oncology literature was never the obstacle. Watson held more of it than any physician in the building. What the workflow needed at its final step was the thing the ladder had promised would arrive on its own.

It does not arrive on its own, because the fourth rung is made of something the picture hides. Aristotle noticed the shape of this and it has aged well: a young person can be an expert geometer but cannot be practically wise, because practical wisdom needs a knowledge of particulars that experience alone supplies, and experience is the fruit of years. Read carelessly that sounds like a claim about elapsed time, and any system with a long training run would satisfy it. Read properly, the years are doing something specific. They are years of deciding, being wrong, and carrying the wrongness forward, which is only possible for something that can be harmed by the outcome of its own judgment. Call it the stake condition. A physician who misreads a chart carries the misreading. A model that misreads one cannot be harmed by it, will not remember it, and does not persist through the consequence in any form that changes what it does next.

So the ladder is retired and a question takes its place, and the question is short enough to ask in a meeting. What does this system have at stake in how the decision turns out? Where the honest answer is nothing, the top rung is not reachable from below by any amount of capability, and the decision belongs to someone who can be harmed by getting it wrong. That constraint is not a ceiling on what these systems are worth. It is the clearest map anyone has of where the humans go, and it holds no matter how good the models get.