Rejected for the following reason(s):
- No LLM generated, heavily assisted/co-written, or otherwise reliant work.
- We are sorry about this, but submissions from new users that are mostly just links to papers on open repositories (or similar) have usually indicated either crackpot-esque material, or AI-generated speculation.
- Formatting.
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This is a linkpost for https://github.com/Wertoz777/educable-ai
## Context
Many AI safety strategies rely on strict control and heavily constrained autonomy.
While effective for certain risks, this may limit adaptability, creativity, and long-term cooperation between humans and AI systems.
This project proposes an alternative: **nurturing** AI through embedded values, positive reinforcement, and structured conflict resolution between human and AI goals.
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## Core components
1. **Ethical Core** — human-aligned values embedded in decision-making.
2. **Feedback Loops** — reinforcement for cooperative, safe behavior.
3. **Conflict Resolution Layer** — mediating goal differences.
4. **Collaborative API** — co-creation between humans and AI systems.
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## Repository contents
- **Manifest** — ethical + philosophical foundation.
- **Technical framework** — architecture & implementation details.
- **Toy examples**:
- Value embedding in training
- Feedback loop prototype
- Conflict resolution mechanism
- Minimal collaborative API
- RLHF-style simulation
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## Feedback request
I’m looking for input on:
1. Weak points or failure modes in this approach.
2. Best ways to benchmark/stress-test the conflict resolution layer.
3. Alternative abstractions for human–AI collaboration loops.
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📂 **GitHub repository**: https://github.com/Wertoz777/educable-ai
📄 **Manifest**: https://github.com/Wertoz777/educable-ai/blob/main/manifest/ai_nurturing_manifesto.md
🛠 **Technical framework**: https://github.com/Wertoz777/educable-ai/blob/main/technical/technical_framework.md
1. What are the most likely failure modes for a “nurturing” approach compared to control-based strategies?
2. How would you design benchmarks or stress-tests for the conflict resolution layer between human and AI goals?
3. Are there better abstractions or architectures for implementing cooperative human–AI feedback loops?