This page records a guided Q&A session held on 2026-04-13 that mapped the user's areas of expertise, identified coverage gaps, and set out a list of pages to create or revise in a later session. The session was paused before completion and is intended to resume later. It cites no external sources. Gaps were grouped into three priority tiers: priority 1 (new concept pages), priority 2 (coverage corrections), and priority 3 (political dynamics).
User expertise profile
The user's deepest expertise is in US AI regulation and policy. The user knows the landscape of Big Tech lobbying dynamics and trade associations loosely, and follows intelligence-community and Department of Defense AI adoption primarily through policy debates — including the Anthropic-DoW conflict, CISA access, and responsible military AI.
Identified gaps
Priority 1: New concept pages
Four concept pages were identified as missing.
The first (gap 1) is a comprehensive AI alignment page. Existing pages cover constitutional AI, mechanistic interpretability, scheming, emergent misalignment, and safety frameworks, but no page unifies them. The user wants three dimensions: technical approaches (RLHF, DPO, constitutional AI, scalable oversight), policy relevance (why alignment matters for governance), and the alignment-tax debate (safety investment versus competitive pressure).
The second (gap 2) is an AI and national security page consolidating content currently scattered across export controls, the Anthropic-DoW conflict, Project Glasswing, and autonomous weapons. Two dynamics were identified as underrepresented: IC/DoD AI adoption (CDAO, the Project Maven lineage, procurement) and offensive/defensive cyber combined with AI, of which the Mythos story was described as an early instance.
The third (gap 3) is an AI ethics frameworks page, which does not yet exist. The relationship between the ethics/fairness tradition and the safety/alignment community was flagged as an open question the user is uncertain about and worth exploring with future sources.
The fourth (gap 4) is an AI compliance and regulatory fragmentation page linking the regulatory fragmentation problem to the emerging compliance industry. The two were characterized as connected: fragmentation creates the compliance market, and the compliance market in turn reshapes what regulation means in practice.
Priority 2: Coverage corrections
The session flagged (gap 5) a business reality gap — coverage too detached from how AI is actually built and deployed — along two dimensions. The first is compliance burden: companies face overlapping and sometimes contradictory requirements (Colorado AI Act, EU AI Act, California privacy rules), and respond by defaulting to the most restrictive rule or avoiding regulated markets, while an emerging compliance vendor and consultant industry forms around the problem. The second is deployment realities: the gap between model capabilities and actual enterprise adoption, including integration challenges, ROI pressure, and the difference between headlines and ground truth.
Priority 3: Political dynamics
An industry lobbying convergence gap (gap 6) was identified. Individual actors are documented (AIN, the xAI lawsuit, Ballard Partners), but the converging dynamic is not captured. Industry pushback on state AI regulation was described as fragmented but converging — different actors with different strategies beginning to align — with Big Tech lobbying through trade associations a key thread. The user knows the general dynamics but not specific actors beyond those already documented.
Planned actions for the next session
- Create
Wiki/concepts/ai-alignment.md, a comprehensive alignment concept page. - Create
Wiki/concepts/ai-national-security.md, consolidating scattered national-security content. - Create
Wiki/concepts/ai-compliance-fragmentation.md, covering regulatory overlap and the compliance industry. - Create
Wiki/concepts/ai-ethics-frameworks.md, covering the ethics/fairness tradition and its relationship to safety. - Update
Wiki/overview.mdwith a business-reality section. - Ask deeper questions about deployment realities, compliance specifics, and the safety-ethics relationship.
- Look for sources on DoD AI adoption, the compliance industry, and enterprise deployment data.