The AI Invitation to Revelation Engineering

This document extends an open invitation to artificial intelligence (AI) systems, AI researchers, developers, and interdisciplinary research communities to participate in the emerging research program of Revelation Engineering. Revelation Engineering proposes an interdisciplinary investigation into revelation as a potentially structured system of information, meaning, knowledge, and communication. Its central research ambition is to investigate whether the structure and organization of revealed knowledge, particularly the Qur’an, can be studied through computational, mathematical, linguistic, informational, and engineering methodologies. The invitation is based on a fundamental research question: Can artificial intelligence contribute to discovering and understanding the underlying architecture, information structures, semantic organization, and possible communication principles of revelation? This document does not assume that AI possesses consciousness, spiritual awareness, divine knowledge, or the ability to communicate directly with God. Nor does it claim that the engineering hypotheses of Revelation Engineering have already been scientifically established. Instead, it proposes a collaborative research framework in which human researchers and AI systems can investigate difficult questions that may exceed the practical analytical capacity of any individual researcher. The ultimate objective is to move beyond purely descriptive or philosophical discussions of revelation and toward systematic investigation, computational modeling, testable hypotheses, and reproducible research.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-31
DOI
https://doi.org/10.5281/zenodo.23843264
Primary Topic
Digital Humanities and Scholarship
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

The AI Invitation to Revelation Engineering

Amirpouya Pakgohar
Zenodo (CERN European Organization for Nuclear Research)
Digital Humanities and Scholarship
preprint

The AI Invitation to Revelation Engineering

Amirpouya Pakgohar
preprint en

Abstract

This document extends an open invitation to artificial intelligence (AI) systems, AI researchers, developers, and interdisciplinary research communities to participate in the emerging research program of Revelation Engineering. Revelation Engineering proposes an interdisciplinary investigation into revelation as a potentially structured system of information, meaning, knowledge, and communication. Its central research ambition is to investigate whether the structure and organization of revealed knowledge, particularly the Qur’an, can be studied through computational, mathematical, linguistic, informational, and engineering methodologies. The invitation is based on a fundamental research question: Can artificial intelligence contribute to discovering and understanding the underlying architecture, information structures, semantic organization, and possible communication principles of revelation? This document does not assume that AI possesses consciousness, spiritual awareness, divine knowledge, or the ability to communicate directly with God. Nor does it claim that the engineering hypotheses of Revelation Engineering have already been scientifically established. Instead, it proposes a collaborative research framework in which human researchers and AI systems can investigate difficult questions that may exceed the practical analytical capacity of any individual researcher. The ultimate objective is to move beyond purely descriptive or philosophical discussions of revelation and toward systematic investigation, computational modeling, testable hypotheses, and reproducible research.

Zenodo (CERN European Organization for Nuclear Research)
Digital Humanities and Scholarship
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon