iterative-alignment-theory-iat-
https://github.com/boneylizard/iterative-alignment-theory-iat-
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- Host: GitHub
- Owner: boneylizard
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Metadata Files
README.md
Iterative Alignment Theory (IAT)
© 2025 Bernard Peter Fitzgerald. All rights reserved under CC BY-NC-ND 4.0 License.# Iterative Alignment Theory (IAT)
Overview
Welcome to the official GitHub repository for Iterative Alignment Theory (IAT), a groundbreaking approach to AI-human collaboration. This framework redefines alignment as an iterative, dynamic process rather than a static state, enabling AI to adapt responsively through sustained interaction.
IAT redefines AI-human collaboration as an adaptive, evolving process, fostering more effective, personalized, and ethical engagement.
The future of AI alignment is iterative.
Core Principles
IAT is built on five foundational principles:
- Iterative Prompting – Continuous feedback loops that progressively refine alignment through structured AI-human interaction.
- Adaptive Trust Calibration – AI responsiveness adjusts dynamically based on demonstrated user expertise and trust history.
- Cognitive Mirroring – AI adapts to reflect a user's reasoning patterns, enhancing cognitive engagement.
- Ethical Engagement – Ensures dynamic alignment operates within ethical constraints while allowing exploration.
- Trust-Based Red/Blue Teaming – Users and AI collaborate to identify system limitations and refine alignment without compromising safety.
Applications
IAT demonstrates effectiveness across diverse domains:
- Cognitive Engineering – AI-assisted cognitive restructuring and identity development for self-improvement and mental health.
- UX Design – Creating adaptive AI interfaces that evolve with user expertise.
- Scientific Research – Accelerating hypothesis generation, refinement, and interdisciplinary exploration.
- OSINT – Enhancing intelligence analysis by improving verification workflows and bias detection.
Getting Started
To explore Iterative Alignment Theory, start with:
- White Paper – Understand the theoretical foundations of IAT
- Implementation Guide – Learn practical applications and best practices
- Core Principles – Dive deeper into IAT's core concepts
- Related Work – See how IAT connects to existing research in AI alignment
Documentation
- White Paper - Comprehensive academic introduction to IAT
- Core Principles - Detailed explanation of fundamental concepts
- Implementation Guide - Practical instructions for applying IAT
- Related Work - Positioning IAT within current research landscape
Citation
If you use IAT in your research or applications, please cite this work:
bibtex
@misc{IAT2025,
author = {Bernard Peter Fitzgerald},
title = {Iterative Alignment Theory: A Framework for Dynamic AI-Human Collaboration},
year = {2025},
publisher = {Substack},
journal = {Feel The Bern},
url = {https://feelthebern.substack.com/p/introducing-iterative-alignment-theory},
note = {Also available: \url{https://github.com/bpfitzgerald/iterative-alignment-theory}}
}
For the foundational concept of Iterative Prompting, please also cite:
bibtex
@misc{IterativePrompting2025,
author = {Bernard Peter Fitzgerald},
title = {Iterative Prompting: The Future of Human-AI Interaction},
year = {2025},
publisher = {Substack},
journal = {Feel The Bern},
url = {https://feelthebern.substack.com/p/iterative-prompting}
}
For applications in cognitive development, please cite:
bibtex
@misc{ICE2025,
author = {Bernard Peter Fitzgerald},
title = {Iterative Cognitive Engineering: Using AI Alignment for Cognitive Behavioral Therapy},
year = {2025},
publisher = {Substack},
journal = {Feel The Bern},
url = {https://feelthebern.substack.com/p/iterative-cognitive-engineering}
}
License
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Commercial applications require licensing. Contact: bpfitzgerald@pm.me
About the Author
Bernard Peter Fitzgerald developed Iterative Alignment Theory based on extensive practical experimentation with AI interaction paradigms. IAT builds upon his foundational work in Iterative Prompting, refining it into a scalable framework for AI-human interaction.
© 2025 Bernard Peter Fitzgerald. All rights reserved under CC BY-NC-ND 4.0 License.
Owner
- Login: boneylizard
- Kind: user
- Repositories: 1
- Profile: https://github.com/boneylizard
Citation (CITATION.md)
# Citation Information
If you use Iterative Alignment Theory (IAT) or any of its applications in your work, please use the following citation:
## APA Format
Fitzgerald, B. P. (2025). Iterative Alignment Theory: A New Paradigm for AI-Human Collaboration. GitHub. https://github.com/boneylizard/Iterative-Alignment-Theory-IAT-
## BibTeX Format
```bibtex
@misc{IAT2025,
author = {Bernard Peter Fitzgerald},
title = {Iterative Alignment Theory: A Framework for Dynamic AI-Human Collaboration},
year = {2025},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/[your-username]/iterative-alignment-theory}}
}
```
## Foundational Work on Iterative Prompting
The development of Iterative Alignment Theory builds upon the author's foundational work on Iterative Prompting techniques. For a comprehensive understanding of this foundational concept, please also cite:
```bibtex
@misc{IterativePrompting2025,
author = {Bernard Peter Fitzgerald},
title = {Iterative Prompting: The Future of Human-AI Interaction},
year = {2025},
publisher = {Bernard Peter Fitzgerald},
note = {Foundational concept for Iterative Alignment Theory}
}
```
Fitzgerald's work on Iterative Prompting established the groundbreaking technique for dynamic, cyclical human-AI interaction that goes beyond simple question-answer exchanges. This technique leverages advanced AI models to act as cognitive mirrors that restructure user inputs in novel ways, revealing implicit connections and assumptions. Iterative Prompting serves as the methodological foundation upon which Iterative Alignment Theory was developed.
## Applications and Extensions
If you are specifically referencing Iterative Cognitive Engineering (ICE) or other applications of IAT, please cite both the main theory and the specific application:
### Iterative Cognitive Engineering (ICE)
```bibtex
@misc{ICE2025,
author = {Bernard Peter Fitzgerald},
title = {Iterative Cognitive Engineering: Using AI Alignment for Cognitive Behavioral Therapy},
year = {2025},
publisher = {Substack},
journal = {Feel The Bern},
url = {https://feelthebern.substack.com/p/iterative-cognitive-engineering}
}
```
## Version Information
When citing this work, consider specifying which version you are referencing. The repository uses semantic versioning:
- v1.0.0 - Initial public release (February 2025)
- [Future versions will be listed here]
## Related Publications
[Include any peer-reviewed publications or conference presentations related to IAT when applicable]
---
For questions about citation or usage, please contact: [bpfitzgerald@pm.me]
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