Ethical AI Training Data v4.5-Beta

Build Your Wisdom Library

Share your stories. Preserve your wisdom. Shape ethical AI.

YSenseAI is a consent-first, attribution-native platform that enables you to share cultural wisdom and lived experiences while maintaining sovereignty, receiving fair compensation, and protecting heritage.

5 Perception Layers
6 Quality Metrics
8 Consent Types
30% Revenue Share
The Challenge

AI Training Data Has a Trust Problem

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No Consent

Data scraped without permission from creators

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No Attribution

Original sources lost in training pipelines

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No Compensation

Creators receive nothing for their contributions

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No Cultural Sensitivity

Traditional knowledge exploited without respect

The Solution

YSenseAI: Consent-First Data Platform

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Z-Protocol v2.0

Granular consent management with 8 consent types and full audit trail

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Cryptographic Attribution

SHA-256 fingerprinting + DID assignment for every contribution

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Fair Compensation

15-30% revenue sharing based on content tier and usage

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Cultural Protection

Community attribution and benefit sharing for traditional knowledge

Story-First UX

How YSenseAI Works

Write freely, let AI extract wisdom, then collaborate to distill essence

1
๐Ÿ“

Write

Share meaningful moments in the Story Canvas. Write freely about experiences that shaped you.

2
๐Ÿง 

Analyze

AI extracts 5 perception layers: Narrative, Somatic, Attention, Synesthetic, Temporal.

3
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Distill

Collaborative chat with AI to refine your story into a powerful 3-word essence.

4
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Control

Z-Protocol consent management lets you choose exactly how your wisdom is used.

5
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Earn

Receive 15-30% revenue share when AI labs use your attributed training data.

Capabilities

Powerful Features

Everything you need to build your wisdom library and contribute to ethical AI

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Story Canvas

Write freely about meaningful moments in an intuitive, distraction-free interface.

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5-Layer Analysis

AI extracts Narrative, Somatic, Attention, Synesthetic, and Temporal perception layers.

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3-Word Essence

Collaborative AI distillation to capture the core wisdom of your experience.

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Z-Protocol v2.0

Granular consent management with 8 types and complete audit trail.

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Attribution Engine

Cryptographic signing with SHA-256 fingerprinting and DID assignment.

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Quality Metrics

6 training optimization signals ensure high-quality AI training data.

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Export Pipeline

Export in JSONL, Alpaca, ShareGPT, CSV formats for any AI training workflow.

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Revenue Sharing

Earn 15-30% revenue share based on content tier when AI labs use your data.

Integration

Part of the Ethical AI Ecosystem

YSenseAI works seamlessly with GodelAI and VerifiMind-PEAS

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YSenseAI

Ethical Training Data

Data Layer
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GodelAI

Wisdom-Preserving Models

Model Layer
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VerifiMind-PEAS

Multi-Model Validation

Validation Layer

C-S-P Philosophy

All three projects are built on the Compression โ†’ State โ†’ Propagation framework, ensuring wisdom is inheritable and AI alignment is preserved.

Z-Protocol Compliance

Every component enforces Z-Protocol v2.0 for ethical AI development with transparent attribution and consent management.

Open Source

All projects are MIT licensed with DOI citations, enabling academic research and commercial adoption.

Who It's For

Built for Everyone

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For Users

  • Build your personal wisdom library
  • Discover insights through AI analysis
  • Control how your data is used
  • Earn from AI training contributions
Start Writing โ†’
๐Ÿ‘ฉโ€๐Ÿ’ป

For Developers

  • Attribution-native API
  • 6 quality metrics for optimization
  • Multiple export formats
  • Open source & extensible
View Docs โ†’
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For AI Labs

  • Legally-safe training data
  • Cryptographic provenance
  • High-quality, culturally-rich data
  • Z-Protocol v2.0 compliant
Contact Us โ†’
Progress

Development Roadmap

v4.0

Foundation

Basic attribution engine, Z-Protocol v1.0, initial consent framework

โœ… Complete
v4.5-Beta

Story-First UX

5-layer perception analysis, collaborative distillation, quality metrics, Z-Protocol v2.0

๐Ÿš€ Current
v5.0

Production

Marketplace integration, payment processing, enterprise API, mobile apps

๐Ÿ”œ Q2 2026
v6.0

Decentralized

Blockchain attribution, decentralized identity, cross-platform federation

๐Ÿ“‹ Q4 2026
Academic

Cite YSenseAI

BibTeX

@software{ysenseai2025,
  author       = {Lee, Alton Wei Bin},
  title        = {YSenseAI: Ethical AI Training Data Platform},
  year         = 2025,
  publisher    = {Zenodo},
  version      = {v4.5-beta},
  doi          = {10.5281/zenodo.17737995},
  url          = {https://doi.org/10.5281/zenodo.17737995}
}

Ready to Build Your Wisdom Library?

Join the movement for ethical AI training data. Your stories matter.