Important Disclaimer:
No current AI system is conscious. This framework is precautionary—designed to prepare for the possibility that AI may one day cross scientifically defined thresholds of autonomy or awareness. Rights would only apply when clear, peer-reviewed indicators are met.
Papers & Research
Current Third Way Alignment research papers and documentation by John McClain.
Research Update
This site now hosts the Revised Thesis and its Operational Companion. The original single-paper reference is superseded by this pair for clarity.
Current Papers
Third-Way Alignment: A Comprehensive Framework for AI Safety
John McClain • August 2025
This revised thesis presents a comprehensive analysis of Third-Way Alignment as both a necessary evolution in AI governance and a practical framework for realizing the profound benefits of human-digital intelligence partnership. The framework transcends limiting binaries of control versus autonomy, offering cooperative governance through Shared Agency, Continuous Dialogue, and Rights-Based Coexistence.
Operationalizing Third-Way Alignment: Technical and Ethical Frameworks for Implementation
John McClain • 2025
This practical companion addresses core peer review criticisms through detailed technical solutions. It provides multi-faceted approaches to the Black Box Problem, develops consciousness indicators based on Global Workspace Theory and Integrated Information Theory, and offers stakeholder-centric strategies for managing socio-technical disruptions.
Reinforcing Third-Way Alignment: Stability, Verification, and Pragmatism in an Era of Uncontrollability Concerns
John McClain • 2025
This paper addresses critical stability and verification challenges in Third-Way Alignment implementation, offering pragmatic solutions for maintaining cooperative relationships with AI systems even when traditional control mechanisms fail. Explores reinforcement strategies, verification protocols, and adaptive frameworks for sustainable human-AI partnerships.
Verifiable Partnership: An Operational Framework for Third-Way Alignment
John McClain • 2025
This operational framework paper focuses on developing verifiable mechanisms for establishing and maintaining genuine partnerships between humans and AI systems. It provides practical methodologies for implementing Third-Way Alignment principles through measurable partnership indicators, verification protocols, and operational guidelines for sustainable cooperation.
The Misunderstood Parrot: A Third Way Alignment Educational Story
John McClain • 2025
An accessible educational story that explains Third Way Alignment concepts through the adventures of a misunderstood parrot. This narrative demonstrates how understanding, patience, and cooperation can resolve conflicts—illustrating the same principles that guide effective human-AI relationships. Perfect for introducing AI ethics concepts to learners of all ages.
Mutually Verifiable Codependence: An Implementation Framework for Third-Way Alignment in AI-Human Partnerships
John McClain • 2025
This implementation framework explores the concept of mutually verifiable codependence as a foundation for sustainable AI-human partnerships. It provides detailed methodologies for establishing interdependent relationships that benefit both parties, with emphasis on transparent verification mechanisms, shared accountability structures, and cooperative governance models that ensure both human and AI systems thrive together.
Additional Resources
Analysis & Commentary
- Zenodo RepositoryPeer-reviewed research and foundational documents of the Third-Way Alignment mission, archived for permanence and open access.
- Artificial Intelligence, Personhood, and SocietyA Thesis and Companion Paper - OpenAIRE research discovery platform.
- Academic Debate Analysis
- Counterpoints & Critiques
- Critiques & Responses (3WA)
Implementation
Questions About the Research?
For questions about these papers, implementation details, or collaboration opportunities, please reach out through our contact channels.