Use the Decision Map to decide where AI should strengthen human work, where the work should be redesigned, and where a human capacity should remain protected.
This is not another AI policy checklist. It starts with the human purpose of the work, then tests what AI strengthens, bypasses, or replaces.
Use it in about 10–15 minutes
The practical question is: what should the person be able to do because of this activity? Then ask whether AI helps them practice that ability, lets them skip the practice, or does the work for them.
Name the capability, judgment, responsibility, or relationship the work is supposed to develop or preserve.
Identify the AI use and classify its effect: strengthen, bypass, or replace.
Require evidence, then test Personhood, Answerability, Presence, and governance constraints.
Record the boundary, why it is defensible, and what would cause the decision to be reopened.
Worked example
This example shows why the Map does not collapse into “allow” or “ban.” The assignment is redesigned around the human capacity the course is actually trying to form.
A faculty member is considering allowing students to use generative AI during a first-year writing assignment. The question is not whether AI may appear somewhere in the process. The question is what parts of the writing process must remain meaningful human exercise.
The assignment is intended to develop students' ability to formulate a claim, organize reasoning, evaluate sources, draft in their own voice, revise in response to critique, and explain why the final argument is theirs.
Possible uses are separated instead of treated as one undifferentiated category.
Brainstorming or critique may strengthen the exercise if the student still evaluates, chooses, explains, and revises.
AI-generated first drafting may bypass the intended exercise when the student skips the work of forming the argument in language.
Full substitution would replace the core formative task if the system performs the reasoning and drafting the student is supposed to learn.
Provisional direction: REDESIGNA polished final paper is not enough evidence that the intended capability was exercised.
Personhood: the student retains agency over the claim, can contest AI suggestions, and has recourse when a tool introduces error or distortion.
Answerability: the student can explain and defend the choices in the final work; responsibility cannot be outsourced to the system.
Presence: faculty feedback, peer critique, and live intellectual encounter remain where they contribute to formation.
The formation judgment does not replace institutional governance. The redesigned assignment still needs to fit applicable:
AI is permitted in defined supporting roles, but the assignment preserves meaningful student exercise of thesis formation, source judgment, first-pass reasoning, revision explanation, and accountable defense.
Try your own case
This quick builder does not replace the full Decision Map. It helps you frame the case well enough to know what deserves a closer review.
Where ReHuman fits
ReHuman does not compete with cybersecurity, compliance, responsible-use training, or governance. It addresses the layer those functions do not answer by themselves: what human capability, judgment, responsibility, and presence should remain meaningful as AI enters the work.
Bring one live case
Bring one assignment, workflow, service, or AI use case. In a short review, we can identify the human purpose, test the proposed AI role, and clarify what should be preserved, redesigned, released, or governed differently.
ReHuman Decision Map · Formation Before Permission · James R. Andrews, J.D., M.Div., D.Min. · james@innershift360.com
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