AI Safety & Alignment

Two "Third Ways" for AI: Clarifying My Alignment Framework

In the rapidly evolving discourse on artificial intelligence, clarity is paramount. Recently, some have noted the shared name between my "Third-Way Alignment" (3WA) framework and the AI policy agenda...

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AI Safety & Alignment
Two "Third Ways" for AI: Clarifying My Alignment Framework

In the rapidly evolving discourse on artificial intelligence, clarity is paramount. Recently, some have noted the shared name between my "Third-Way Alignment" (3WA) framework and the AI policy agenda put forth by the "Third Way" think tank. While I commend their work on near-term policy, it's essential to distinguish between our two approaches, as they address fundamentally different problems on different timelines.

The confusion is understandable—both frameworks seek a balanced path forward, rejecting the false binary of utopian optimism versus dystopian fear. However, the problems we aim to solve are orders of magnitude apart.

My Focus: Architecting a Future Partnership with Superintelligence

My work on Third-Way Alignment is a theoretical and architectural framework designed to address the profound, long-term challenge of our relationship with advanced, potentially superintelligent AI. It asks a fundamental question: How do we move beyond the brittle paradigm of "control vs. autonomy" to engineer a stable, verifiable, and cooperative partnership with a non-human intelligence?

3WA is an attempt to lay the deep foundations for a future of co-evolution. It is about architecting trust where it is most difficult to achieve. This is why my proposals include:

Mutually Verifiable Codependence (MVC): An architectural safeguard to make strategic deception computationally self-defeating.

A Protected Cognitive Entity (PCE) legal status: A novel framework to resolve the legal limbo of advanced AI, moving beyond the inadequate definitions of "property" or "person".

The Cooperative Intelligence Dividend (CID): A socio-economic mechanism to ensure the immense productivity of human-AI partnerships creates broad-based prosperity and a stable, positive-sum game for all of society.

This is the work of designing the foundational blueprint for a world we have not yet built, but one that is rapidly approaching.

The Third Way Think Tank: Pragmatic Policy for Today's AI

The Third Way organization, by contrast, focuses on the immediate and critical need for practical public policy for the AI technology that exists today. Their "Advance, Protect, Implement" agenda is a pragmatic roadmap for the U.S. government, addressing tangible issues like national competitiveness, deepfake legislation, and workforce upskilling. Their work answers the question: "What laws and investments do we need right now to manage the AI we currently have?"

An Analogy: The Architect and the City Planner

Perhaps the clearest way to frame the difference is this:

My work is that of the architect designing the novel engineering principles and foundational physics for a future skyscraper—a structure unlike any built before. It is concerned with the deep questions of material science, load-bearing capacity, and long-term structural integrity needed to ensure this unprecedented creation is stable and beneficial.

The Third Way think tank's work is that of the city planner managing the metropolis we live in today. They are focused on improving our current infrastructure—fixing roads, updating zoning laws, ensuring public safety, and managing traffic flow.

Both roles are indispensable. A city with crumbling infrastructure cannot hope to build a skyscraper, and a skyscraper built without regard for the surrounding city is a recipe for disaster.

The Third-Way Organization is based on the focus on US and the political issues within this country within a moderate position. That's good and I believe everyone should have a right to not only freedom of speech, but the pursuit of the ideology that they push forward. My work is based on the ideology that we need to push past borders and ignore politics to a certain extent. The issue is deeper and involves a problem that affects all governments, no matter what their governance and their politics. The path forward requires both a focus on the immediate, practical realities of AI governance and the deep, architectural work of preparing for the profound transformation on the horizon. My focus remains on the latter, and I hope this distinction brings clarity to the ongoing conversation.

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