We keep saying judgment will matter more. I have been saying it too. But before we build careers, organizations and AI systems around that assumption, I think we need to understand what we're actually talking about.
An ongoing inquiry that narrows judgment, separates it from adjacent concepts, and asks how assessments are evaluated, learned from, formed and scaled across an organization.
Companies do not scale judgment by preserving it perfectly. They make parts of decision systems durable. The challenge is keeping rules, metrics and AI assessments valid and updatable once they gain operational force.
Experience does not automatically produce good judgment. What matters is whether it gives us useful signal, corrective feedback, and patterns that transfer.
Judgment is not one thing. It is an assessment, separate from reasoning, preference, creation, decision and authority. Making those distinctions visible makes consequential decisions easier to inspect.
We keep saying judgment will matter more. I have been saying it too. But before we build careers, organizations and AI systems around that assumption, I think we need to understand what we're actually talking about.
Someone read two pieces I had written months apart and named the connection I had never made explicit. That exchange stayed with me. The writing was the occasion. The question it surfaced was something else entirely: what it means to stand behind a contribution.
This week I made a design decision that bothered me.
A personal AI skill-readiness scanner I am experimenting with must never say the skill is safe. It took me a moment to understand why that bothered me.
That is not a tool. That is an alibi.