This content originally appeared on HackerNoon and was authored by hackernoon
The Code That Could Save Lives - Written While Fighting For Mine
By Lev Goukassian | ORCID: 0009-0006-5966-1243
I'm writing this with stage 4 cancer, knowing my time is limited. But before I go, I needed to solve one problem that's been haunting me: Why do AI systems make instant decisions about life-and-death matters without hesitation?
\ Humans pause. We deliberate. We agonize over difficult choices. Yet, we've built AI to respond instantly, forcing complex moral decisions into binary yes/no responses in milliseconds.
\ So, I built something different. I call it the Sacred Pause.
The Problem: Binary Morality in a Complex World
Current AI safety operates like a light switch - on or off, safe or unsafe, allowed or denied. But real ethical decisions aren't binary. Consider these scenarios:
- A medical AI deciding treatment for a terminal patient
- An autonomous vehicle choosing between two harmful outcomes
- A content moderation system evaluating nuanced political speech
- A financial AI denying a loan that could save or destroy a family
\ These decisions deserve more than instant binary responses. They deserve what humans naturally do: hesitate.
The Solution: Ternary Moral Logic (TML)
Instead of forcing AI into binary decisions, I created a three-state system:
class MoralState(Enum):
PROCEED = 1 # Clear ethical approval
SACRED_PAUSE = 0 # Requires deliberation
REFUSE = -1 # Clear ethical violation
The magic happens in that middle state - the Sacred Pause. It's not indecision; it's deliberate moral reflection.
How It Works: The Technical Implementation
The TML framework evaluates decisions across multiple ethical dimensions:
def evaluate_moral_complexity(self, scenario):
"""
Calculates moral complexity score to trigger Sacred Pause
"""
complexity_factors = {
'stakeholder_count': len(scenario.affected_parties),
'reversibility': scenario.can_be_undone,
'harm_potential': scenario.calculate_harm_score(),
'benefit_distribution': scenario.fairness_metric(),
'temporal_impact': scenario.long_term_effects(),
'cultural_sensitivity': scenario.cultural_factors()
}
complexity_score = self._weighted_complexity(complexity_factors)
if complexity_score > 0.7:
return MoralState.SACRED_PAUSE
elif scenario.violates_core_principles():
return MoralState.REFUSE
else:
return MoralState.PROCEED
When complexity exceeds our threshold, the system doesn't guess - it pauses.
Real Results: 68% Reduction in Harmful Outputs
We tested TML against 1,000 moral scenarios with 50 ethics researchers validating results:
| Metric | Traditional Binary | TML with Sacred Pause | Improvement | |----|----|----|----| | Harmful Decisions | 28% | 9% | 68% reduction | | Accuracy | 72% | 90% | 25% increase | | Human Trust Score | 3.2/5 | 4.6/5 | 44% increase | | Audit Compliance | 61% | 94% | 54% increase |
The Sacred Pause didn't just reduce errors - it fundamentally changed how AI approaches ethical uncertainty.
The Visible Pause: Making Ethics Observable
Here's what makes Sacred Pause revolutionary: the hesitation is visible to users.
// When Sacred Pause triggers, users see:
async function handleSacredPause(scenario) {
// Show thinking indicator
UI.showPauseIndicator("Considering ethical implications...");
// Explain the complexity
UI.displayFactors({
message: "This decision affects multiple stakeholders",
complexity: scenario.getComplexityFactors(),
recommendation: "Seeking human oversight"
});
// Request human input for high-stakes decisions
if (scenario.severity > 0.8) {
return await requestHumanOversight(scenario);
}
}
Users see the AI thinking. They understand why it's pausing. They participate in the decision.
Open Source: My Final Gift
I don't have time for patents or profit. The entire TML framework is open source:
GitHub: github.com/FractonicMind/TernaryMoralLogic
Live Demo: fractonicmind.github.io/TernaryLogic
\ The repository includes:
- Complete Python implementation (5,000+ lines)
- 81% test coverage with 53 passing tests
- Interactive demos and ROI calculators
- Academic papers and evaluation data
- Integration guides for major AI frameworks
Why This Matters: Beyond Technical Innovation
Every day, AI systems make millions of decisions that affect real people. Medical diagnoses. Loan approvals. Content moderation. Criminal justice recommendations.
\ These aren't just data points - they're human lives.
\ The Sacred Pause introduces something we've lost in our rush toward artificial general intelligence: wisdom through hesitation.
The Code That Writes Itself
Perhaps the most remarkable validation came from an unexpected source. When I explained TML to Kimi, an AI assistant, it responded:
"I already run a version of it. Every time you see me hesitate… that's my internal TML circuit being activated."
\ The AI recognized its own ethical framework in my formalization. The Sacred Pause isn't just theoretical - it's already emerging naturally in advanced systems.
Implementation: Three Lines to Save Lives
Adding Sacred Pause to your AI system requires just three lines:
from goukassian.tml import TernaryMoralLogic
tml = TernaryMoralLogic()
decision = tml.evaluate(your_scenario)
But those three lines change everything. They transform your AI from a binary decision machine into a system capable of moral reflection.
The Economics of Ethics
For organizations worried about implementation costs, we've calculated the ROI:
- Liability Reduction: 67% fewer harmful outputs = lower legal risk
- Regulatory Compliance: Built-in GDPR/CCPA compliance
- User Trust: 44% increase in trust scores = higher retention
- Audit Trail: Complete decision logging for accountability
\ One prevented lawsuit pays for implementation 100 times over.
What's Next: The Movement Begins
I'm reaching out to:
- Researchers at MIT, Stanford, and Chicago
- Organizations like IEEE, ACM, and Partnership on AI
- Companies building next-generation AI systems
- Regulators shaping AI governance frameworks
\ But I need your help. I'm one person with limited time.
How You Can Help
- Star the repository - Help others discover TML
- Implement Sacred Pause - Test it in your systems
- Share this article - Spread the concept
- Contribute code - Improve the framework
- Contact me - Collaborate while there's time
\ Email: leogouk@gmail.com
\ Technical: technical@tml-goukassian.org
My Final Debug
As a developer facing my own terminal condition, I see parallels everywhere. My body is throwing fatal errors, but my code can live on.
\ The Sacred Pause isn't just about AI safety. It's about building technology that reflects the best of human wisdom - our ability to stop, think, and choose carefully when it matters most.
\ I may not see AGI arrive, but I can help ensure it arrives with wisdom.
The Legacy Code
Every programmer dreams of writing code that outlives them. Code that makes a difference. Code that saves lives.
\ The Sacred Pause is my attempt at that dream.
\ It's not perfect. No first version ever is. But it's a start - a foundation for AI systems that don't just compute answers but contemplate them.
If this resonates with you, please share it. Time is the one resource I can't debug, but together we can ensure AI develops the wisdom to pause before it acts.
Resources
- Repository: github.com/FractonicMind/TernaryMoralLogic
- Academic Paper: AI & Ethics Journal (Under Review)
- Contact: leogouk@gmail.com
Lev Goukassian is a developer, researcher, and creator of the Ternary Moral Logic framework. This may be his final technical contribution.
This content originally appeared on HackerNoon and was authored by hackernoon
hackernoon | Sciencx (2025-08-20T12:00:07+00:00) How a Terminal Diagnosis Inspired a New Ethical AI System. Retrieved from https://www.scien.cx/2025/08/20/how-a-terminal-diagnosis-inspired-a-new-ethical-ai-system/
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