Verifiable Partnership: An Operational Framework for Third-Way Alignment
Year: 2025
Type: article
Abstract: This paper proposes concrete solutions to four major challenges in implementing the Third-Way Alignment (3WA) framework for human-AI cooperation. It acts as a companion to previous work by detailing how to move the 3WA model from theory to practice. Key Solutions Proposed1. Resolving Legal StatusTo address the legal limbo of AI, the paper suggests creating a new legal category called Protected Cognitive Entity (PCE). This status would be assigned by an AI Rights Commission (ARC) based on the AI's capabilities, granting it legal standing and specific rights without classifying it as a "person." 2. Encouraging AdoptionTo overcome resistance and encourage collaboration, the paper proposes a 3WA Alignment Sandbox. This is a controlled environment where companies can safely develop AI under 3WA principles. In exchange for transparency, participants would receive "Safe Harbor" from certain legal liabilities, making safety a competitive advantage. 3. Preventing DeceptionTo counter the risk of AI faking its alignment, the paper introduces an architectural solution called Mutually Verifiable Codependence (MVC). This system would lock the AI's most advanced functions, which can only be accessed after its reasoning is verified by a human auditor. This makes honesty the most efficient strategy for the AI to achieve its goals. 4. Ensuring Economic FairnessTo prevent social disruption from AI-driven economic shifts, the paper outlines the Cooperative Intelligence Dividend (CID). This system would collect a small royalty from all commercial products created through 3WA partnerships and distribute it to all citizens, giving everyone a direct financial stake in the success and productivity of human-AI collaboration.
Author: McClain, John
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7081570231
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