PROJECT

OVERVIEW OF THE PROJECT

Human reasoning is increasingly unstable in a world saturated with information and amplified by AI systems that produce answers without revealing how they were derived. Most disagreements do not originate in conclusions, but in unexamined premises and implicit assumptions. No current tool — intellectual or technological — exposes these premises, tests their coherence, or compares different worldviews structurally.

This project proposes a general-purpose reasoning framework in which axioms become *explicit parameters*. You select the axioms; the method derives their implications, compares multiple configurations, and reveals divergences in a transparent, reproducible way. The method is universal; the values remain open.

An initial phase will formalize the meta-method, develop complete worked examples, and produce a White Paper V1. The long-term vision is to establish a stable cognitive architecture for high-stakes reasoning in individuals, institutions, and human-AI interaction.

1. The Problem: A Cognitive Architecture Breakdown

Reasoning processes are failing under modern conditions. Information overload, shifting definitions, and fragmented worldviews make stable reasoning increasingly difficult. People debate conclusions while relying on premises they cannot articulate. Institutions struggle to maintain coherent frameworks for decision-making. AI models make this worse by producing fluent outputs without clarifying their logical structure.

The core issue: “our current cognitive tools cannot reveal the structure of our own thought.” Without a transparent way to examine premises and their consequences, disagreements become intractable and decisions become unstable.

2. The Proposition: A reasoning framework, not a moral system

This project does not propose a new morality, ideology, or system of values. Instead, it introduces a *meta-method*: a structure for examining any reasoning process along three layers:

• Logical layer: definitions, categories, contradictions.
• Epistemic layer: observed facts vs interpretations vs assumptions.
• Normative layer: axioms as explicit, adjustable parameters.

The novelty lies in treating axioms not as immutable truths but as variables that can be selected, modified, and compared.

The goal is clarity, not consensus.

3. The Core Mechanism: Axioms as Parameters

The framework operates as follows:

1. Select the axioms an individual or group implicitly uses.
2. Formalize them as explicit parameters.
3. Derive their consequences using the meta-method.
4. Compare multiple configurations of axioms.
5. Reveal structural divergences without judging which set is “right.”

Key properties:

• Transparency: hidden assumptions become visible.
• Reproducibility: same inputs yield same outputs.
• Comparability: two worldviews can be structurally contrasted.
• Anti-authoritarian: no value is imposed; all parameters are editable.

This transforms reasoning from a rhetorical process into an analyzable structure.