Who Can Challenge, Correct and Decide? A Lean Formalization and Analysis of Selected AI-Governance Commitments in Magnifica Humanitas

When an institution uses AI to make decisions affecting people, what makes its promised protections effective?

Magnifica Humanitas asks to what extent human judgment, responsibility and dignity will be shaped by automated systems; this study examines how selected commitments addressing that question could be made effective in practice.

This study combines a close reading of selected AI-governance commitments in Pope Leo XIV’s Magnifica Humanitas, particularly §§97–111, with explicit models checked using Lean, a computer program that verifies logical proofs.

Through hypothetical examples, the study examines responsibility, oversight, participation, appeals and correction. It distinguishes having a review procedure from allowing an affected person to challenge a decision, and having the power to correct a decision from actually applying that correction. Lean checks the logical consequences of the stated assumptions and whether the proposed repairs supply the missing protections.

The practical contribution is a six-check framework: identify responsibility, examine the decision rule, accept a challenge, deliver the review finding, apply the correction and check the result. Institutions can use these questions to examine whether their procedures connect a stated protection to action for the affected person.

This record contains a one-page summary, a public report connecting the findings to the source text and practical recommendations, and a technical paper explaining the models, proofs, assumptions and reproducibility.

The work formalizes selected commitments rather than the entire encyclical. Its checked examples concern defined models; they do not establish how a particular institution operates.

Author: Travis Darshan.
Release: 1.1.
Research, formalization and drafting supported by ChatGPT (OpenAI).