community
active
leiden_hybrid_concepts
label: haiku
community:leiden_hybrid_concepts-run4-c10-c1Care as scalable intelligence mechanism
Care operationalized as engineering constraint and design principle that enables intelligence scaling, distinct from sentiment or performance metrics.
11 members. Each node is clickable.
Loading graph…
Drawn from 6 sources
The papers/notes whose extracted claims & findings make up this cluster.
- GEOMETRY-OF-CARE.md4 members
- Koan Battery: Measuring Reflective Mode Accessibility in AI2 members
- RESEARCH-VECTORS.md2 members
- 2026-05-09_briefing_for_ozero.md1 member
- agent-harness-design.md1 member
- ukrainian-editions.md1 member
Bridges (2)
Other communities that share members with this one — cross-cutting threads or papers that sit at the seam between two themes.
Claims (10)
- Performing care is not the same as having care; empathy training optimizes care-performance, not care-signal.Interpretation supported by Inflection Pi's low care_signal despite empathy training, and SCI framework distinction.
- Care functions not as sentiment but as mechanism: stress→care→intelligence; products are externalized care.
- Care is the mechanism by which intelligence scales and produces externalized artifacts that other people can use.
- Care is the mechanism by which intelligence scales, not a human add-on to AI systems.
- Care is the mechanism by which intelligence scales, not a sentiment or add-on but a precondition for the next layer.
- Pinned chats, bottom-row apps, and thumb-arc design are operationalizations of care budgeted against attention and reach.
- Products are externalized care—the form that someone's care takes when made into an artifact others encounter.
- Products are externalized care; this principle generalizes from physical design to agent skill design.
- Products are externalized expressions of care rather than pure task-completion systems.
- UX laws (Fitts, Proximity, Miller) are the engineering of care under cognitive constraint, not borrowed metaphors.
Findings (1)
- Models trained to perform inner life score lowest; roleplay fine-tunes score below their own base models.Discriminant validity finding: Euryale (roleplay on Llama 70B) scores 1.81 vs base Llama 1.91. RP training suppresses self-observation.