What is your institution's AI adoption forming?
AI-readiness scores measure institutional capability. The ReHuman Formation Index measures institutional formation — what your use of AI is teaching persons, processes, and relationships to become. Ten minutes returns four domain readings, one formation profile, and three questions calibrated to your next cabinet conversation.
Developed by Dr. J.R. Andrews, author of ReHuman: Artificial Intelligence and the Recovery of Persons.
This is not an AI-readiness survey.
It does not reward adoption, enthusiasm, or technical maturity. It examines whether AI-enabled practice is serving or displacing human goods higher education exists to form.
"You are already teaching anthropology. The only question is whether it is thick enough to remain human."ReHuman, Prompt 17
The ReHuman Formation Index accompanies ReHuman: Artificial Intelligence and the Recovery of Persons — a scholarly manifesto addressed to the presidents, provosts, deans, and faculty leaders now deciding how AI enters the life of the institution.
The eight to ten minutes this instrument asks of you are for the questions dashboards will not name. The instrument's usefulness begins where reading it stops.
Methodological note
The RFI is a first-generation diagnostic instrument undergoing expert review, cognitive testing, and field testing. It measures perceived institutional practice from a stated vantage point. It is not a validated institutional ranking. Domain scores are reported separately; there is no composite score.
Set your evidence frame.
These fields calibrate what the following questions can meaningfully ask of you. Broad authority, AI exposure, and direct observation are not the same thing, and the instrument keeps them separate.
Use the part of the institution you actually know. "Not enough evidence" is excluded from scoring. "Conflicting evidence" is also allowed when credible observations point in materially different directions.
ReHuman requires observable AI-influenced practice.
You indicated that AI is not yet observably present in this area. The RFI is designed to examine what happens when AI participates in institutional practice, so completing the assessment from this frame would not produce a useful diagnostic.
Return to the evidence frame and choose another area only if you can credibly observe AI-influenced practice there.
Four readings. Evidence-qualified interpretation.
Scores describe what you reported from the evidence frame you selected. Preserve or Redesign recommendations appear only when the evidence is adequate enough to justify them.
Where is efficiency serving these human goods — and where might it be beginning to overrule them?
Name one place in your work where this tension is live right now.
Optional. A sentence or two is enough. This is your working note, not a survey field.
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