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People–Policy–Technology

Human-Centered AI Research & Policy

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Independent research exploring responsible AI development through the lens of human-centered design, policy frameworks, and ethical governance.

Status: 🌱 Active research repository | Open for dialogue & collaboration


🔍 Focus Areas

🧠 Human-Centered AI & LLM Behavior

Understanding LLM capabilities, risks, and emergent behaviors • Alignment & interpretability • Human–AI interaction • Behavior evaluation & decision systems

⚖️ AI Governance & Policy Frameworks

Principles for responsible AI • Global regulatory trends • Ethical guardrails (fairness, safety, accountability, transparency) • Public-interest AI governance

🌍 Societal Impact & Digital Public Systems

Frontier AI’s implications for society • Cross-sector AI applications (health, education, governance) • Human–machine collaboration • Inclusive and equitable innovation


🧩 Why This Repository?

This space bridges technical understanding, policy thinking, and human-centered design to support safer, more ethical, and more inclusive AI futures.

What you’ll find:

  • 📚 Research notes & conceptual frameworks
  • 🔬 Behavioral evaluation insights from frontier LLMs
  • 🌐 Evolving thought pieces & ongoing study documentation
  • 🤝 Opportunities for interdisciplinary collaboration

What makes this unique:
A cross-disciplinary synthesis grounded in 20+ years of leadership across technology, policy, governance, and social innovation, including independent evaluation of multiple frontier LLMs and real-world decision environments.


📄 Key Document

Frontier LLM Behavioural Architecture Report (15 pages)
Download PDF

Note: This is an independent, self-directed study. It is not affiliated with or commissioned by any organisation, and it remains unpublished. Shared openly for learning, transparency, and collaborative research.

2-Page Summary — Frontier LLM Behavioural Architecture
Download Summary PDF


📚 How to Cite This Work

Singh, Mankaj. (2025). Frontier LLM Behavioural Architecture: A Systematic Multi-Case Evaluation Across Five Frontier Models. Zenodo. https://doi.org/10.5281/zenodo.17749013

This work is an independent, unpublished research study conducted without institutional affiliation.


🤝 Collaboration

I welcome engagement from:

  • AI researchers & safety practitioners
  • Policymakers and governance leaders
  • Technologists & public-interest innovators
  • Social impact and development sector professionals

If you are exploring similar questions — or wish to co-develop frameworks, compare findings, or engage in interdisciplinary inquiry — feel free to connect.


📬 Contact

Email: mankajsingh@gmail.com
LinkedIn: https://www.linkedin.com/in/mankaj


📜 License

This work is shared under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.
You may use, adapt, and build upon it with proper attribution.


🌱 Work in Progress

This repository will continue expanding with:

  • Research papers & notes
  • Human-centered AI evaluation methods
  • Policy frameworks & governance models
  • Concept papers & interdisciplinary analyses
  • Cross-sector case studies

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Independent research on human-centered AI and LLMs | Policy frameworks for responsible AI | A collaborative space for researchers, innovators, and policymakers advancing ethical, inclusive AI

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