The End of Invisible Decisions

How Ternary Moral Logic (TML) makes AI accountability an automatic, undeniable reality.

The Problem: A Crisis of Evidence

When AI causes harm, the reasoning vanishes, leaving victims with no proof and organizations with no accountability. This isn't a bug; it's a feature of modern systems that prioritizes convenience over justice.

99%

Of harmful AI decisions leave no auditable trace, making justice nearly impossible.

Interview Duration: 6 minutes 26 seconds

Back to Repository

The Solution: The TML Architecture

TML embeds accountability into every action through an 8-pillar framework. Each step builds a verifiable chain of reasoning, culminating in an immutable Moral Trace Log created *before* any action is taken.

PILLAR 1

Sacred Zero (The Pause)

PILLARS 2-3

Ethical Analysis Engine

(Always Memory, Goukassian Promise)

PILLAR 4

Moral Trace Log Creation

The immutable, court-admissible evidence is generated and sealed.

PILLAR 5-8

Human Rights, Planetary Protection, Hybrid Shield, Blockchains

Impact Visualized: Justice by the Numbers

TML doesn't just promise accountability; it delivers quantifiable results. The existence of a Moral Trace Log fundamentally changes the dynamics of seeking justice after AI-driven harm.

Drastic Reduction in Time to Resolution

With undeniable proof available from day one, legal battles are shortened from years to months.

Fundamental Shift in Burden of Proof

The system carries the burden of proving its actions were ethical, not the victim.

Justice by Design

The impacts ripple across society, empowering those who were previously voiceless.

For Victims

Automatic evidence and smart-contract-based compensation remove the need for costly, prolonged fights for justice.

For Whistleblowers

System violations create their own proof, eliminating the personal risk of exposing wrongdoing from the inside.

For Humanity

Human rights and environmental protections gain a voice backed by mathematical enforcement, not just political will.