Decision Justification Engineering: Evidence, Human Permission, and Continuing Authority

Decision Justification Engineering (DJE) explores what justifies delegating a defined task to an automated system—and what must remain true for that authority to continue. This release brings together a presentation, three-page executive summary, four conceptual companions, and an end-to-end case guide. A real-property valuation laboratory provides a concrete setting for examining evidence, quality control, repeated AI estimates, and the distinction between engineering sufficiency and human permission. The laboratory examines source-evidence representation, ten-qualifying-run ensembles, outcome-redacted retrospective predictions, one genuinely prospective prediction, and Leave-One-Out Cross-Validation characterization of two evidence states. The proposed governance architecture addresses continuing authority, its revocation, and controls on individual candidates. Measured findings are distinguished from illustrative standards and proposed deployment controls. The work does not demonstrate an end-to-end autonomous deployment. Start with the executive summary for orientation or the presentation for the full narrative. The website provides guided access to the material; the repository supplies supporting workbooks and experimental records. These linked resources are not all included in this seven-PDF deposit. Guided website: https://dje.truth-machine.org/ Supporting repository: https://github.com/truth-machine/decision-justification-engineering

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-02
DOI
https://doi.org/10.5281/zenodo.23890633
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Decision Justification Engineering: Evidence, Human Permission, and Continuing Authority

Sandy Fitzburgh
4 links
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Decision Justification Engineering: Evidence, Human Permission, and Continuing Authority

Sandy Fitzburgh
article en

Abstract

Decision Justification Engineering (DJE) explores what justifies delegating a defined task to an automated system—and what must remain true for that authority to continue. This release brings together a presentation, three-page executive summary, four conceptual companions, and an end-to-end case guide. A real-property valuation laboratory provides a concrete setting for examining evidence, quality control, repeated AI estimates, and the distinction between engineering sufficiency and human permission. The laboratory examines source-evidence representation, ten-qualifying-run ensembles, outcome-redacted retrospective predictions, one genuinely prospective prediction, and Leave-One-Out Cross-Validation characterization of two evidence states. The proposed governance architecture addresses continuing authority, its revocation, and controls on individual candidates. Measured findings are distinguished from illustrative standards and proposed deployment controls. The work does not demonstrate an end-to-end autonomous deployment. Start with the executive summary for orientation or the presentation for the full narrative. The website provides guided access to the material; the repository supplies supporting workbooks and experimental records. These linked resources are not all included in this seven-PDF deposit. Guided website: https://dje.truth-machine.org/ Supporting repository: https://github.com/truth-machine/decision-justification-engineering

Zenodo (CERN European Organization for Nuclear Research)
Peace, justice, and strong institutions
Openalex Percentile: Top 11%
Ethics and Social Impacts of AI
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Decision Justification Engineering: Evidence, Human Permission, and Continuing Authority — Sandy Fitzburgh · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS