At The Center for Ethical AI, we believe that knowledge should be both accessible and accountable. The works published here are part of an open-access initiative designed to advance ethical AI research, governance, and education. Each publication is made available to support academic collaboration, informed dialogue, and responsible innovation in artificial intelligence.
Monographs
Licensing and Use:
All open-access publications are released under a Creative Commons Attribution–NonCommercial (CC BY-NC) license.
This means you are free to download, share, and cite the materials with proper attribution, but commercial reuse or modification is prohibited without express written permission from the author or publisher.
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Authors:
If you have a Monograph you would like to submit for posting to this repository, please contact us for guidelines and instructions for submitting your manuscript. If not previously published, we can assign ISBN or DOI for reference and discoverability.
Ethical AI Integration articulates a lifecycle-governance approach for deploying AI systems with epistemic integrity. It synthesizes bias, misinformation, and error diagnostics with standards-aligned auditing, continuous monitoring, and human oversight to translate ethical intent into measurable, operational AI accountability across real-world deployments.
SymPrompt+ is a structured, standards-aligned prompting framework for governing human–AI interactions. It operationalizes ethical constraint, epistemic clarity, and auditability through tagged prompt syntax, multi-turn evaluation, and lifecycle integration, reducing bias, misinformation, and error amplification in large language model outputs.
Academic’s Guide to Ethical AI and Prompt Engineering synthesizes ethical theory, governance standards, and applied prompt design to guide responsible use of large language models. It offers lifecycle-aware methods to reduce bias, misinformation, and error while preserving transparency, accountability, and scholarly integrity in human–AI interaction.
Whitepapers & Policy Briefs
Call to Engagement:
​We invite educators, researchers, and industry practitioners to engage with and contribute to this evolving collection of frameworks, toolkits, and applied guidance on ethical AI.
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Article Submissions:
We welcome unsolicited whitepapers, research briefs, and policy analyses aligned with the mission of this repository. Prospective contributors are encouraged to contact us to discuss scope, fit, and submission guidelines.
Adaptive AI Governance as a Lifecycle Control System
https://doi.org/10.5281/zenodo.18213191
This policy brief presents AI governance as a lifecycle control system rather than static compliance. It outlines an integrated, standards-aligned framework that governs AI from data sourcing through deployment using continuous monitoring, feedback loops, and enforceable constraints to ensure accountability, resilience, and trustworthy AI operations.
Methods, Tools, & Artifacts
Demo Model
The Bias Cascade Visualizer is an interactive educational tool that demonstrates a critical but often overlooked phenomenon in artificial intelligence: how small biases in data can become catastrophically large biases in deployed AI systems through a process of multiplicative amplification.