https://drive.google.com/file/d/1vkokFE0rdf8vVQnEgZ75bBzfbufmMhVw/view?usp=sharing\

Project summary

The Reputation Circulation Standard (RCS) prevents AI catastrophe by making harmful behavior economically impossible. Using exponential decay (R(t)=R₀e^(-λt)), we create environments where power accumulation is mathematically bounded and beneficial behavior is the only rational strategy. We have working code ready to deploy at AI labs within weeks. Revolutionary Paper published at https://deepthinker.xyz.

We need safety mechanisms that work automatically at any intelligence level.

Our Solution

The Reputation Circulation Standard (RCS) makes harmful AI behaviour economically irrational through exponential decay mechanisms (R(t) = R₀e^(-λt)) of assigned reputation, making them equal participants in a contribution game played with reputation. Rather than trying to control AI, we create environments where beneficial behaviour is the only stable strategy, and dominant strategy that achieves Nash equilibrium.

Key Innovation

• Mathematical Guarantees: Proven bounds on power accumulation
• Automatic Scaling: Safety increases with intelligence
• Economic Incentives: Alignment through self-interest, not control
• No Human Bottleneck: Works at any speed or scaleCurrent Status

✅ Complete implementation (code available under NDA)
✅ Paper submitted to SSRN
✅ Consensus algorithms validated (TruthfulAI, Berkeley)
✅ Reputation systems deployed (MOCA/Animoca Brands, EthCC 2025)
✅ Endorsement from Nassim Taleb
✅ IITM Research partnership discussions ongoing
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We need safety mechanisms that work automatically at any intelligence level.

What are this project's goals? How will you achieve them?

1. Deploy RCS at first AI lab (Month 1-2)

• Prevent at least one potential catastrophic deployment
• Demonstrate 70%+ reduction in deceptive behavior
• Achieve <5% performance overhead

1. Validate & Document (Month 2-3)

• Publish empirical results
• Create integration guides
• Build developer tools

1. Enable Widespread Adoption

• Open-source core libraries
• Support 100+ developers
• Establish safety standard

How We'll Achieve Them:

Week 1-2: IntegrationWeek 3-4: TestingWeek 5-8: ValidationWeek 9-12: ScalingHow will this funding be used?

$50,000 Budget Breakdown:

Development & Integration (40% - $20,000)

• 160 hours senior engineer time @ $125/hr
• Adapt existing code for lab deployment
• Performance optimization

Testing Infrastructure (20% - $10,000)

• Compute for adversarial testing
• Multi-model consensus validation
• Benchmark suite development

Documentation & Outreach (16% - $8,000)

• Technical documentation
• Integration guides
• Video tutorials

Security Audits (14% - $7,000)

• Code review by external auditor
• Penetration testing
• Vulnerability assessment

Operations (10% - $5,000)

• Project coordination
• Legal review for open-source
• Community management

Every dollar directly accelerates deployment of proven safety mechanisms before GPT-5 level systems arrive.

Who is on your team? What's your track record on similar projects?

Arifa Khan - Principal Investigator

• Published RCS paper (SSRN pending)
• Built TruthfulAI consensus system at Berkeley hackathon for Google's verifiable AI
• Developed reputation credentials for MOCA/Animoca Brands (EthCC 2025)
• RCS Framework endorsed by Nassim Nicholas Taleb (Black Swan and Antifragility author)

Track Record: ✅Complete RCS implementation - Working code with smart contracts (private repo) ✅TruthfulAI - Demonstrated consensus algorithms for detecting AI divergence ✅MOCA Identity Network - Deployed reputation system for DeFi participants ✅Survived suppression - Published research despite coordinated attacks and resistanceUnique Advantages:

• BOTH working code AND economic expertise
  RCS Paper: https://black-impressive-rodent-254.mypinata.cloud/ipfs/bafybeibhfu5t5pwfql6kq3yfknw5et6iimpdrqwkmsgoq6o2ev7khzbjqy/papers/RCS-v1.pdf
• Strong advisors network
• Bridge between AI safety and blockchain reputation systems and distributed systems for complex finance

Advisory Support:

• IITM Research partnership discussions
• AI safety researchers reviewing approach
• Smart contract auditors engaged, such as Immunefi \