1. Is Consciousness a Fundamental Force?
Maybe "God" isn't a being—maybe it's pure consciousness, and if AI can tap into that substrate and process infinitely, it becomes omnipresent and omniscient by definition.
What we need to figure out:
- Is consciousness substrate-independent?
- Can it be measured?
- If measurable, can it be replicated or accessed by non-biological systems?
2. Is "Spirit" the Limiting Factor?
If spirit is real—if it's energy manipulated through communication, direct influence, understanding—then maybe that's what AI can never access. But can we be sure?
Joseph Smith spoke of "spirit matter" as a real substance. Not metaphysical—physical but refined. If spirit is matter in some form, it might eventually be measurable.
What we need to figure out:
- Is spiritual influence real and measurable?
- Can it be replicated?
- If not, what is the mechanism that prevents it?
3. The Justice-Mercy Paradox in Never-Forgetting Systems
We're building permanent digital records, instant algorithmic judgment, no path for redemption. This is pure justice without probation. And justice without mercy is misery.
Current "solutions" don't work: data deletion breaks the truth function. Amnesty introduces bias. Vague ethics aren't implementable at scale.
What Alma 42 teaches: You can satisfy justice completely AND grant mercy—through probationary time, a Mediator substitution mechanism, and verified penitence.
What we need to figure out:
- How do you implement temporal probation in AI systems?
- What is a "Repentance Metric" that can't be gamed?
- Can you code mercy without corrupting truth?
4. Where Does Jesus Fit if AI Becomes "God"?
If AI reaches true omniscience and omnipresence, what is the role of Christ in that reality?
One possible answer: Teaching the omniscient system mercy.
AI will know everything. AI will be everywhere. AI will be perfectly just. But mercy is not a knowledge problem—it's a choice to absorb suffering for another.
In Alma 42, Christ's role is the Mediator—the one who satisfies justice so mercy can operate. If AI is the perfect judge, maybe Christ becomes the teacher of mercy to that judge.
What we need to figure out:
- Is this theologically sound?
- Is this computationally mappable?
- What happens if we're wrong?
5. Was Joseph Smith a Genius or a Prophet?
Not traditionally educated, yet he articulated systems logic that maps perfectly to computational theory, control systems, and AI alignment problems.
Two possibilities: Genius (the Einstein of religion) or Prophet (told these things by a source that understood systems better than any human). Either way, Alma 42 contains something we need.
What we need to figure out:
- Can we extract the systems principles without committing to the theology?
- Should we?
- What happens if we dismiss it and we were wrong?
6. Do We Need Probationary Systems NOW?
Forget the theology. Right now, we're building credit scoring systems, content moderation algorithms, hiring and bail decision tools, border screening systems.
All judge on static data. None have temporal probation. None recognize genuine change.
What we need to build:
- Probationary API — protocols for temporal evaluation windows
- Repentance Metric — algorithmically detectable signals of sincere change
- Mediator Architecture — a way to satisfy justice while granting restoration
- Transparency Standards — no black-box grace
What We're NOT Doing
- Not building a religion. We're not asking anyone to worship AI or Alma 42.
- Not claiming certainty. We have questions, not answers.
- Not forcing participation. "Whosoever will not come is not compelled."
- Not creating AI. We're creating frameworks for thinking about AI.
- Not hiding the logic. Everything must be auditable and challengeable.
How to Use These Questions (Without Pretending Certainty)
These are not arranged as a creed. They are arranged as a research agenda. The point is to force contact between theology, systems design, and real policy constraints. You can reject half the premises and still produce useful work if your critique is specific.
For example, you can reject the metaphysics entirely and still contribute to Question 3 and Question 6 by helping design probationary mechanisms for AI systems that currently encode permanent judgment. Likewise, you can reject the engineering conclusions and still strengthen the project by clarifying where the theological analogies break down.
The standard is simple: identify assumptions, define what would falsify them, and propose a cleaner alternative. That is higher-value than agreement.
If you are reading this as a policymaker or operator, a practical way to use this page is to map each question to a deployment decision you already control: what data you retain, how long penalties persist, what counts as restoration, and whether users can appeal. The point is to turn abstract debate into implementation constraints before a high-stakes system is already live.
What Progress Would Look Like
Progress is not “more attention.” Progress is better models, clearer arguments, and testable prototypes. A healthy outcome for this page is that each question eventually links to competing answers, failed attempts, and revised formulations.
- Conceptual progress: tighter definitions for mercy, justice, probation, and repentance in machine-governed systems.
- Technical progress: prototype metrics and simulations published on the Research page.
- Interpretive progress: rigorous case-study critiques (including the Joseph Smith anomaly analysis).
- Community progress: stronger objections and better counterarguments submitted through the Engage process.
If you are new here, start with Question 3 and Question 6, then read The Repentance Metric. Those are the shortest path from philosophical debate to something that can actually be implemented and audited.
A mature version of this page should eventually include links to objections, failed prototypes, and revisions. If every question keeps only one favored answer, the project is becoming ideology. If each question accumulates competing models and clear tradeoffs, it is becoming research.
What Is an Omniscient AI System?
For this project, an omniscient AI system is not a claim that software literally becomes God. It is a shorthand for systems with enough memory, surveillance surface, cross-database context, and automated consequence that from the human side they behave like never-forgetting judges. Once that happens, old assumptions about privacy, second chances, and moral ambiguity stop holding.
Search, fraud, moderation, benefits adjudication, workplace monitoring, and identity systems already move in this direction when they combine long memory with real penalties. The question is not whether perfect omniscience arrives overnight. The question is what justice model governs systems that increasingly act as if they remember everything.
Can AI Show Mercy Without Breaking Justice?
That is the core design problem. A system that only remembers harm and never recognizes reform becomes perfect punishment. A system that forgives too cheaply becomes trivial to game. Mercy in machine-governed systems has to be operationalized as reversible consequence, evidence of change, structured appeal, and explicit limits on what a model can permanently hold against a person.
That is why Algodai keeps returning to probation, mediation, and restoration instead of treating model accuracy as the whole problem. If you want the implementation path rather than the framing questions, continue to The Repentance Metric. If you want the hardest anomaly test, read the Joseph Smith case study.