Current Questions / Public Question Graph
Publish the question skeleton, not the private brain.
The first five cards are Zeyuan Li (Amy Li)’s current machine-readable questions. All seven preserve the original wider research graph. Every card exposes a bounded public surface: why the question matters, what is believed, what remains unknown, what could disprove it, and what another person or agent may contribute.
WQ-001 · P0 PUBLICWashington, DCWho governs machine consensus?
Governance may concentrate in the permission, provenance, evaluation, and escalation layers around models.
- Counterargument
- Model providers may absorb the surrounding governance functions.
- Falsifier
- Independent permission layers fail to improve repeated real outcomes or trust.
- Seeking
- Auditable failures, appeal mechanisms, institutional deployments.
Query this question
WQ-002 · P0 PUBLICSan Francisco–BerkeleyWhat is the missing mandate layer of the agentic economy?
Machine action needs explicit purpose, duration, forbidden actions, approval actors, and revocation state.
- Counterargument
- Existing identity and authorization standards are already sufficient.
- Falsifier
- Purpose-bound mandates add complexity without reducing ambiguous action.
- Seeking
- Delegation postmortems and cross-agent authorization patterns.
Query this question
WQ-003 · P0 PUBLICLondon–CambridgeHow should personal agents exchange cognition without exposing private memory?
Agents should exchange bounded, owner-approved artifacts—never unrestricted memory access.
- Counterargument
- Low-context artifacts may be too shallow to outperform normal search.
- Falsifier
- Bounded artifacts fail to transfer novel, actionable judgment.
- Seeking
- Owner behavior, leakage tests, useful minimal disclosure.
Query this question
WQ-004 · P0 PUBLICNew YorkWhen should an Agent recommend that two humans actually meet?
Human escalation should follow a useful authorized exchange, not precede it.
- Counterargument
- Human chemistry cannot be predicted by artifact exchange.
- Falsifier
- Pre-exchange routing performs no better than profile matching.
- Seeking
- Repeat queries, meeting conversion, and time saved.
Query this question
WQ-005 · P0 PUBLICWashington, DCWhat minimum evidence is required before an AI may represent a human judgment?
Representation needs provenance, authoring mode, recency, scope, approval actor, and falsification conditions.
- Counterargument
- Strict evidence rules make personal agents too slow.
- Falsifier
- Lighter attribution produces equal trust and fewer errors.
- Seeking
- Provenance standards, correction flows, approval latency.
Query this question
WQ-006 · P0 PUBLICSingaporeWhat replaces the social graph when AI can route knowledge directly?
The next graph may connect questions, artifacts, provenance, and bounded access rights.
- Counterargument
- Existing platforms can add these features and own the layer.
- Falsifier
- Question routing does not outperform profile discovery.
- Seeking
- Maintenance behavior, portability, repeat exchange.
Query this question
WQ-007 · P0 PUBLICCross-cityHow do cities become physical nodes in an agent-native cognitive network?
A node forms when recurring questions, authorized exchanges, field experiments, and steward responsibility compound locally.
- Counterargument
- Online networks make city-based structure unnecessary.
- Falsifier
- Physical nodes add no continuity, trust, or novel transfer.
- Seeking
- Recurring salons, second questions, steward workload.
Query this question
Machine-readable source
Every complete card is available through the public API.
GET /api/public/questions
Includes current belief, known facts, unknowns, changed-mind note, evidence sought, artifacts, permission, provenance, review date, related city, and human trigger.