EvidenceStrong architectural inferencev1.22.1
In plain English
This page shows what kind of support exists for each claim: real systems, experiments, early evidence, architectural reasoning, open questions, or speculative scenarios.
- Why this matters: AI risk can come from the whole arrangement, not one obvious model.
- What to look for: data, memory, routes, adapters, tools, evaluators, updates, and rollback paths.
- Technical version below: the expert terminology remains available and is linked through the glossary.
Source Dossier: Decentralized Persistence and Local AI Risk Surface
Evidence card
- Claim
- Decentralized AI deployments can compound distributed behavioral persistence by increasing local state, adapter, memory, router, evaluator, and handoff reservoirs.
- Evidence level
- Architectural inference
- Source
- docs/source-reports/raw-markdown/analyzing-reports-impact-on-cognivirus-risks.md
- Publication date
- 2026-06-29
- Authors or institution
- User-supplied source dossier
- System tested
- Source-dossier synthesis; no deployed Cognivirus system test claimed.
- Limitations
- External citations require independent verification. Cognitive-interface risk remains future-facing unless supported by specific evidence. Specific deployment statistics should not be repeated without source validation.
- What the evidence does show
- Decentralized AI deployments can compound distributed behavioral persistence by increasing local state, adapter, memory, router, evaluator, and handoff reservoirs.
- What the evidence does not show
- It does not prove a named Cognivirus malware incident, AI consciousness, local AI inherent unsafety, or that the full future-risk scenario has occurred.
- Date last reviewed in UTC
- 2026-06-29T02:15:00Z
Boundary note
Evidence levelStrong architectural inferenceTechnical label: Architectural inference
This card records a report-derived synthesis. It does not certify external claims, does not claim a named malware family exists, and does not turn cognitive-interface future concerns into demonstrated incidents.