22cc3f57fb
- Source: inbox/archive/2025-12-00-fullstack-alignment-thick-models-value.md - Domain: ai-alignment - Extracted by: headless extraction cron (worker 4) Pentagon-Agent: Theseus <HEADLESS>
3.4 KiB
| type | domain | secondary_domains | description | confidence | source | created | enrichments | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| claim | ai-alignment |
|
Full-stack alignment requires concurrent alignment of AI systems and governing institutions with thick models of value, not just individual model alignment | speculative | Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value (December 2025) | 2026-03-11 |
|
Beneficial AI outcomes require institutional co-alignment not just model alignment
The full-stack alignment framework argues that "beneficial societal outcomes cannot be guaranteed by aligning individual AI systems" alone. Instead, comprehensive alignment requires concurrent alignment of BOTH AI systems and the institutions that shape their development and deployment.
This extends beyond single-organization coordination (lab-to-lab alignment) to address misalignment across multiple stakeholders at the institutional level. The framework proposes five implementation mechanisms: (1) AI value stewardship, (2) normatively competent agents, (3) win-win negotiation systems, (4) meaning-preserving economic mechanisms, and (5) democratic regulatory institutions.
The key distinction: coordination-first alignment theories address how AI labs coordinate with each other. Full-stack alignment asserts that regulatory bodies, economic mechanisms, and democratic processes themselves—the institutions that govern AI development—must be redesigned and aligned alongside the AI systems. This is a stronger institutional claim than lab-level coordination.
Evidence
The paper frames this as an architectural framework rather than an empirically validated approach. The five implementation mechanisms are proposed but lack formal specification or deployment evidence. The paper does not provide impossibility results or comparative analysis against alternative institutional designs.
Challenges
The framework does not specify how to operationalize institutional alignment in practice, nor does it address:
- How to coordinate institutional redesign across jurisdictions with conflicting interests
- Whether institutional change can operate on timescales matching AI capability development
- How to handle irreducible value disagreements between institutions
- Computational tractability of the proposed mechanisms at scale
The simultaneous co-alignment requirement may be intractable if institutions and AI systems operate on fundamentally different timescales.
Relevant Notes:
- AI alignment is a coordination problem not a technical problem — full-stack alignment extends coordination thesis to institutions
- AI development is a critical juncture in institutional history where the mismatch between capabilities and governance creates a window for transformation — provides urgency context
- safe AI development requires building alignment mechanisms before scaling capability — institutional mechanisms are prerequisite
- pluralistic alignment must accommodate irreducibly diverse values simultaneously rather than converging on a single aligned state — institutional alignment must handle value pluralism
Topics: