3.2 KiB
| type | title | author | url | date | domain | secondary_domains | format | status | priority | tags | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| source | Full-Stack Alignment: Co-Aligning AI and Institutions with Thick Models of Value | Multiple authors | https://arxiv.org/abs/2512.03399 | 2025-12-01 | ai-alignment |
|
paper | unprocessed | medium |
|
Content
Published December 2025. Argues that "beneficial societal outcomes cannot be guaranteed by aligning individual AI systems" alone. Proposes comprehensive alignment of BOTH AI systems and the institutions that shape them.
Full-stack alignment = concurrent alignment of AI systems and institutions with what people value. Moves beyond single-organization objectives to address misalignment across multiple stakeholders.
Thick models of value (vs. utility functions/preference orderings):
- Distinguish enduring values from temporary preferences
- Model how individual choices embed within social contexts
- Enable normative reasoning across new domains
Five implementation mechanisms:
- AI value stewardship
- Normatively competent agents
- Win-win negotiation systems
- Meaning-preserving economic mechanisms
- Democratic regulatory institutions
Agent Notes
Why this matters: This paper frames alignment as a system-level problem — not just model alignment but institutional alignment. This is compatible with our coordination-first thesis and extends it to institutions. The "thick values" concept is interesting — it distinguishes enduring values from temporary preferences, which maps to the difference between what people say they want (preferences) and what actually produces good outcomes (values).
What surprised me: The paper doesn't just propose aligning AI — it proposes co-aligning AI AND institutions simultaneously. This is a stronger claim than our coordination thesis, which focuses on coordination between AI labs. Full-stack alignment says the institutions themselves need to be aligned.
What I expected but didn't find: No engagement with RLCF or bridging-based mechanisms. No formal impossibility results. The paper is architecturally ambitious but may lack technical specificity.
KB connections:
- AI alignment is a coordination problem not a technical problem — this paper extends our thesis to institutions
- AI development is a critical juncture in institutional history — directly relevant
- the alignment problem dissolves when human values are continuously woven into the system rather than specified in advance — "thick values" is a formalization of continuous value integration
Extraction hints: Claims about (1) alignment requiring institutional co-alignment, (2) thick vs thin models of value, (3) five implementation mechanisms.
Context: Early-stage paper (December 2025), ambitious scope.
Curator Notes (structured handoff for extractor)
PRIMARY CONNECTION: AI alignment is a coordination problem not a technical problem WHY ARCHIVED: Extends coordination-first thesis to institutions — "full-stack alignment" is a stronger version of our existing claim EXTRACTION HINT: The "thick models of value" concept may be the most extractable novel claim