Published September 8, 2025 | Version 1
Publication Open

Reinforcing Third-Way Alignment: Stability, Verification, and Pragmatism in an Era of Uncontrollability Concerns

  • 1. Third Way Alignment Foundation

Description

This companion paper to the Third-Way Alignment (3WA) theses addresses the strongest critiques of AI controllability and outlines how 3WA aims to achieve safety without requiring absolute control. It proposes “constitutional motivation” as a design goal, making the AI’s success depend on sustained, good-faith collaboration with humans, and reframes oversight as continuous verification dialogue rather than one-off checks. The paper argues that 3WA limits the force of impossibility theorems (e.g., Conant–Ashby, Rice) by building a structured, self-regulating, and interpretability-constrained architecture that humans audit instead of directly controlling. It specifies proactive defenses against deceptive alignment—adversarial verification and cognitive forensics—and uses a tiered-trust mechanism to couple rights and autonomy to verifiable behavior. Finally, it positions the Charter of Fundamental AI Rights as a pragmatic safety instrument that induces a stable, non-zero-sum partnership.

Files

reinforcingthirdwayalignment.pdf

Files (175.3 kB)

Name Size Download all
md5:d970bddaba9d623887cb32e652cecfd0
175.3 kB Preview Download

Additional details

Related works

Is supplement to
Working paper: 10.5281/zenodo.16999914 (DOI)

Dates

Created
2025-09-08
Compliment Document to Third-Way Alignment Thesis v1

References

  • Apollo Research. (2024). Evaluating frontier models for dangerous capabilities. Apollo Research Technical Report.
  • Conant, R. C., & Ashby, W. R. (1970). Every good regulator of a system must be a model of that system. International Journal of Systems Science, 1(2), 89–97.
  • McClain, J. (2025a). Third-Way Alignment: A Comprehensive Framework for AI Safety.
  • McClain, J. (2025b). Operationalizing Third-Way Alignment: Technical and Ethical Frameworks for Implementation.
  • Rice, H. G. (1953). Classes of recursively enumerable sets and their decision problems. Transactions of the American Mathematical Society, 74(2), 358–366.
  • Yampolskiy, R. V. (2020). Uncontrollability of AI. [Preprint]. ResearchGate. https://www.researchgate.net/publication/343812745_Uncontrollability_of_AI