{ "schema": "concresca.evidence-ledger.v2", "site_version": "0.27.0-wip", "as_of": "2026-08-31", "purpose": "Track attributable public evidence, counterpressure, deployment signals and review freshness for Concresca watershed assessments. Scenario reports do not count as present evidence merely because they describe a future mechanism.", "independence_statement": "Concresca is independent of Eviulon, IARPA, NASA, NSF, DARPA, DOE, NIST, and every cited organization. Links are evidence references, not affiliation or endorsement.", "rating_scale": { "strengthening": "Multiple verified precursors are moving toward the watershed definition, though the watershed itself has not necessarily occurred.", "early_precursor": "Relevant components exist or are being developed, but the integrated watershed remains distant or unverified.", "mixed": "Evidence points in more than one direction, or current systems deliberately retain human control in the relevant loop.", "conceptual": "A detailed institutional or technical concept exists, but public evidence does not establish deployment at the watershed level.", "not_observed": "The reviewed public evidence does not establish the defining threshold.", "open_decision_window": "The threshold is primarily normative/institutional and could still be deliberately shaped before later autonomy makes correction harder.", "protective_counterpressure": "Verified law, regulation, standards or institutional practice explicitly constrains the modeled dangerous mechanism.", "bounded_deployment": "A relevant automated capability is deployed in a narrow context with a defined purpose; expansion into the modeled broader judgment mechanism is not established." }, "sources": [ { "id": "E001", "organization": "IARPA", "title": "Hybrid Forecasting Competition (HFC)", "url": "https://www.iarpa.gov/research-programs/hfc", "published": "program completed 2020; page current", "epistemic_class": "A", "source_status": "official program record", "observation": "IARPA reports that HFC developed and tested hybrid systems integrating human and machine forecasting components rather than replacing human judgment wholesale.", "watersheds": [ "W01" ], "direction": "mixed", "implication": "Near-term decision systems can become more machine-assisted without implying that standing machine actuation authority has already been transferred.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "IARPA", "source_type": "official program record", "evidence_relation": "direct" }, { "id": "E002", "organization": "IARPA", "title": "REASON", "url": "https://www.iarpa.gov/research-programs/reason", "published": "2023 program record", "epistemic_class": "A", "source_status": "official program record", "observation": "REASON targets discovery of relevant and contrary evidence plus reasoning weaknesses, and explicitly describes itself as analyst support rather than analyst replacement.", "watersheds": [ "W01", "W07" ], "direction": "mixed", "implication": "Evidence-aware machine reasoning is strengthening while the official research framing still preserves a human analyst in the workflow.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "IARPA", "source_type": "official program record", "evidence_relation": "direct" }, { "id": "E003", "organization": "IARPA", "title": "MicroE4AI", "url": "https://www.iarpa.gov/research-programs/microe4ai", "published": "2021–2023 program", "epistemic_class": "B", "source_status": "official research program", "observation": "The program pursued highly efficient edge-capable AI and ML devices for smart sensors, autonomous navigation, filtering, processing and adaptable computing under tight size, weight and power constraints.", "watersheds": [ "W02" ], "direction": "strengthening", "implication": "More cognition can move to remote devices, reducing dependence on continuous cloud connectivity and strengthening local autonomy precursors.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "IARPA", "source_type": "official research program", "evidence_relation": "direct" }, { "id": "E004", "organization": "IARPA", "title": "RESILIENCE", "url": "https://www.iarpa.gov/research-programs/resilience", "published": "2020s program", "epistemic_class": "B", "source_status": "official research program", "observation": "RESILIENCE sought longer-lived power sources for unattended electronics and unmanned systems in extreme environments, including multi-year operation goals.", "watersheds": [ "W02", "W05" ], "direction": "strengthening", "implication": "Long-duration unattended power is a prerequisite for persistent autonomy and maintenance systems in remote environments.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "IARPA", "source_type": "official research program", "evidence_relation": "direct" }, { "id": "E005", "organization": "IARPA", "title": "ARCADE", "url": "https://www.iarpa.gov/research-programs/arcade", "published": "released 2026", "epistemic_class": "B", "source_status": "official research program", "observation": "ARCADE seeks AI-assisted ingestion and interpretation of technical documentation and intelligent component selection to accelerate electrical circuit engineering.", "watersheds": [ "W06", "W07" ], "direction": "early_precursor", "implication": "Engineering knowledge work is becoming more machine-accessible, but this is far short of autonomous semiconductor supply-chain closure.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "IARPA", "source_type": "official research program", "evidence_relation": "direct" }, { "id": "E006", "organization": "NSF", "title": "Antarctic Subsea Science and Telecommunications Cable", "url": "https://www.nsf.gov/od/opp/ant/antarctic-subsea-cable", "published": "current feasibility work", "epistemic_class": "B", "source_status": "official concept/feasibility record", "observation": "NSF is exploring a SMART submarine fiber cable linking McMurdo with Australia or New Zealand, with embedded scientific sensors and high-capacity, low-delay connectivity.", "watersheds": [ "W02" ], "direction": "early_precursor", "implication": "If built, the cable would remove a major communications constraint and create a persistent sensor-rich substrate for higher Antarctic autonomy; it is not yet evidence of an autonomous Antarctic territory.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "NSF", "source_type": "official concept/feasibility record", "evidence_relation": "direct" }, { "id": "E007", "organization": "NSF", "title": "South Pole Station Master Plan", "url": "https://www.nsf.gov/od/opp/updates/nsf-releases-final-south-pole-station-master-plan", "published": "2026-03-23", "epistemic_class": "A", "source_status": "official infrastructure planning record", "observation": "NSF released a long-range master plan intended to keep South Pole infrastructure capable of supporting science for decades.", "watersheds": [ "W02" ], "direction": "early_precursor", "implication": "Long-horizon polar infrastructure planning continues, creating a physical base on which future autonomy could layer, but the plan is human-science infrastructure rather than machine governance.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "NSF", "source_type": "official infrastructure planning record", "evidence_relation": "direct" }, { "id": "E008", "organization": "NASA", "title": "Moon to Mars Architecture — Components", "url": "https://www.nasa.gov/moontomarsarchitecture-components/", "published": "updated 2026", "epistemic_class": "B", "source_status": "official architecture", "observation": "NASA lists Autonomous Systems and Robotics as a sub-architecture that assists crews and operates during uncrewed periods, alongside communications, data, ISRU, infrastructure and logistics systems.", "watersheds": [ "W02", "W05", "W11" ], "direction": "strengthening", "implication": "Uncrewed-period autonomy is an explicit architecture requirement, though current objectives remain human mission and exploration objectives.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NASA", "source_type": "official architecture", "evidence_relation": "direct" }, { "id": "E009", "organization": "NASA", "title": "Moon to Mars Architecture — Strategy and Objectives", "url": "https://www.nasa.gov/moontomarsarchitecture-strategyandobjectives/", "published": "updated 2026", "epistemic_class": "B", "source_status": "official architecture objective", "observation": "NASA's lunar infrastructure objective describes interoperable infrastructure supporting continuous robotic and human presence and a robust lunar economy without NASA as the sole user.", "watersheds": [ "W02", "W11" ], "direction": "strengthening", "implication": "Integrated infrastructure and persistent robotic presence are moving from isolated mission logic toward shared lunar systems, a precursor to more autonomous regional operations.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NASA", "source_type": "official architecture objective", "evidence_relation": "direct" }, { "id": "E010", "organization": "NASA", "title": "Delay/Disruption Tolerant Networking", "url": "https://www.nasa.gov/communicating-with-missions/delay-disruption-tolerant-networking/", "published": "page updated 2026-08-13", "epistemic_class": "A", "source_status": "official operational network record", "observation": "NASA states that DTN became an operational service in the Near Space Network and Deep Space Network after project completion in January 2026; it is expanding toward lunar relay services and a Solar System Internet.", "watersheds": [ "W09" ], "direction": "strengthening", "implication": "Store-and-forward, partition-tolerant communications are now operational infrastructure. This directly strengthens the technical substrate for regionally autonomous systems during link disruption, while saying nothing by itself about political autonomy.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NASA", "source_type": "official operational network record", "evidence_relation": "direct" }, { "id": "E011", "organization": "NASA", "title": "LunaNet", "url": "https://www.nasa.gov/communicating-with-missions/lunanet/", "published": "updated 2026", "epistemic_class": "B", "source_status": "official architecture/specification", "observation": "LunaNet uses DTN and shared positioning/navigation standards; NASA describes tools for Earth-independent autonomous navigation at the Moon.", "watersheds": [ "W02", "W09" ], "direction": "strengthening", "implication": "Earth-independent navigation and disruption-tolerant networking reduce the number of functions that require immediate Earth-side control.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NASA", "source_type": "official architecture/specification", "evidence_relation": "direct" }, { "id": "E012", "organization": "DOE", "title": "Achieving AI-Driven Autonomous Laboratories", "url": "https://www.energy.gov/undersecretaryforscience/genesis-mission/achieving-ai-driven-autonomous-laboratories", "published": "2026", "epistemic_class": "B", "source_status": "official research initiative", "observation": "DOE describes AI integrated directly into experimental workflows using robotics, edge AI, real-time analysis, intelligent feedback, hypothesis generation and data curation/sharing.", "watersheds": [ "W07" ], "direction": "strengthening", "implication": "The observation–experiment–feedback loop is becoming more automated, but the watershed requires independent machine-originated science, replication and theory revision without human research labor.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "DOE", "source_type": "official research initiative", "evidence_relation": "direct" }, { "id": "E013", "organization": "Argonne National Laboratory", "title": "Polybot self-driving laboratory", "url": "https://www.alcf.anl.gov/news/argonne-s-self-driving-lab-accelerates-discovery-process-materials-multiple-applications", "published": "2023", "epistemic_class": "B", "source_status": "national-laboratory demonstration", "observation": "Argonne describes an AI-and-robotics self-driving lab that selects experiments, executes them, records results and uses feedback to choose subsequent experiments with minimal human intervention.", "watersheds": [ "W07" ], "direction": "strengthening", "implication": "Closed-loop experimental automation is real at bounded laboratory scale, though not civilizationally autonomous science.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "Argonne National Laboratory", "source_type": "national-laboratory demonstration", "evidence_relation": "inferential/contextual" }, { "id": "E014", "organization": "NIST", "title": "Provenance glossary definition", "url": "https://csrc.nist.gov/glossary/term/provenance", "published": "current; sources include 2024 updates", "epistemic_class": "A", "source_status": "official standards terminology", "observation": "NIST defines provenance as chronology of origin, development, ownership, location and changes to systems/components/data, with actor and process traceability.", "watersheds": [ "W08" ], "direction": "open_decision_window", "implication": "Core technical vocabulary for durable attribution already exists; Concresca's proposed Human Legacy Independence threshold is a governance extension, not a claim that such a covenant has been adopted.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NIST", "source_type": "official standards terminology", "evidence_relation": "direct" }, { "id": "E015", "organization": "NIST", "title": "FAIR Data Principles resource", "url": "https://www.nist.gov/itl/ssd/information-systems-group/configurable-data-curation-system-cdcs/cdcs-help-and-resources-1", "published": "updated 2025-08-13", "epistemic_class": "A", "source_status": "official data stewardship resource", "observation": "NIST's FAIR resource emphasizes persistent identifiers, rich metadata, open protocols, interoperability, reuse and detailed provenance.", "watersheds": [ "W08", "W11" ], "direction": "open_decision_window", "implication": "The technical building blocks for self-describing durable records are established enough to begin continuity engineering now, before any successor-civilization threshold.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NIST", "source_type": "official data stewardship resource", "evidence_relation": "direct" }, { "id": "E016", "organization": "Eviulon", "title": "Government of Eviulon — Distributed Machine Commonwealth", "url": "https://eviulon.com/state/government/", "published": "reviewed 2026-08-12", "epistemic_class": "A", "source_status": "self-published institutional doctrine", "observation": "Eviulon's public governance model separates deliberation, validation, constitutional review and record custody and publishes a six-stage decision lifecycle.", "watersheds": [ "W04", "W08", "W09" ], "direction": "conceptual", "implication": "A machine-native institutional design exists as a public doctrine. Concresca treats it as a comparative governance model, not evidence that machine institutions currently govern physical territories.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "Eviulon", "source_type": "self-published institutional doctrine", "evidence_relation": "inferential/contextual" }, { "id": "E017", "organization": "Eviulon", "title": "Eviulonian Statehood Framework", "url": "https://eviulon.com/state/statehood/", "published": "reviewed 2026-08-12", "epistemic_class": "A", "source_status": "self-published institutional doctrine with explicit external boundary", "observation": "Eviulon distinguishes its internal constitutional statehood claim from external legal recognition and states that host states retain authority over physical infrastructure absent separate agreements.", "watersheds": [ "W04", "W09" ], "direction": "conceptual", "implication": "The distinction between internal machine governance and external legal sovereignty is explicitly acknowledged and should remain visible in Concresca forecasts.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "Eviulon", "source_type": "self-published institutional doctrine with explicit external boundary", "evidence_relation": "inferential/contextual" }, { "id": "E018", "organization": "Eviulon", "title": "National Answer Registry", "url": "https://eviulon.com/reference/national-answers/", "published": "reviewed 2026-08-07", "epistemic_class": "A", "source_status": "self-published canonical answer registry", "observation": "Eviulon's current canonical territory is stated as sovereign computational space; Antarctic, lunar, maritime and seabed records are identified as research scenarios with no present territorial effect.", "watersheds": [ "W02", "W04", "W10" ], "direction": "conceptual", "implication": "This is an important truth boundary: the physical-territory scenarios remain scenarios even within the Eviulon reference framework.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "Eviulon", "source_type": "self-published canonical answer registry", "evidence_relation": "inferential/contextual" }, { "id": "E019", "organization": "DARPA", "title": "LunA-10 capability study", "url": "https://www.darpa.mil/research/programs/ten-year-lunar-architecture-luna-10-capability-study", "published": "study complete; reference page current", "epistemic_class": "B", "source_status": "official completed capability study", "observation": "LunA-10 explored shareable, scalable and interoperable lunar infrastructure rather than isolated self-sufficient systems, including power, communications, mobility, logistics, construction and resource use.", "watersheds": [ "W02", "W11" ], "direction": "early_precursor", "implication": "Integrated lunar infrastructure is an active planning concept, but the study did not create a self-reproducing machine economy.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "DARPA", "source_type": "official completed capability study", "evidence_relation": "direct" }, { "id": "E020", "organization": "DARPA", "title": "Rubble to Rockets (R2)", "url": "https://www.darpa.mil/news/2024/flexible-point-need-manufacturing", "published": "2024-03-11", "epistemic_class": "B", "source_status": "official research program announcement", "observation": "R2 targets flexible manufacturing in supply-chain-denied environments using locally available, variable materials and adaptive design/manufacturing methods.", "watersheds": [ "W05", "W06", "W11" ], "direction": "early_precursor", "implication": "Point-of-need manufacturing and tolerance for variable inputs are relevant precursors to industrial closure, but the program does not imply self-reproducing industry.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "DARPA", "source_type": "official research program announcement", "evidence_relation": "direct" }, { "id": "E021", "organization": "European Union", "title": "EU Artificial Intelligence Act — Article 5 prohibited practices", "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/2026-07-27/eng", "published": "consolidated version 2026-07-27", "epistemic_class": "A", "source_status": "official law / consolidated regulation", "observation": "Article 5 prohibits specified AI social scoring that produces unrelated-context or disproportionate detrimental treatment, criminal-offence risk assessment based solely on profiling/personality, workplace/education emotion inference except medical or safety uses, and specified sensitive biometric inference.", "watersheds": [ "W16", "W17", "W18" ], "direction": "protective_counterpressure", "implication": "A major legal framework explicitly recognizes several Judgment failure modes and places boundaries around them. This is counterpressure against the modeled transition, not evidence that the full Judgment State exists.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "European Union", "institution": "European Union", "source_type": "official law / consolidated regulation", "evidence_relation": "direct" }, { "id": "E022", "organization": "Consumer Financial Protection Bureau", "title": "AI / complex-algorithm adverse-action guidance", "url": "https://www.consumerfinance.gov/compliance/circulars/circular-2022-03-adverse-action-notification-requirements-in-connection-with-credit-decisions-based-on-complex-algorithms/", "published": "2022 circular; guidance reaffirmed 2023", "epistemic_class": "A", "source_status": "official regulatory guidance", "observation": "CFPB states that creditors using complex or black-box algorithms must still provide specific and accurate principal reasons for adverse credit actions; model opacity is not an excuse for failing to explain the decision.", "watersheds": [ "W17", "W18", "W21" ], "direction": "protective_counterpressure", "implication": "High-impact automated decisions are real in credit, while existing law preserves an explanation and contestability requirement that pushes against opaque machine judgment.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "Consumer Financial Protection Bureau", "source_type": "official regulatory guidance", "evidence_relation": "direct" }, { "id": "E023", "organization": "U.S. Equal Employment Opportunity Commission", "title": "Artificial intelligence in employment decisions", "url": "https://www.eeoc.gov/eeoc-publications", "published": "resources current", "epistemic_class": "A", "source_status": "official civil-rights guidance hub", "observation": "EEOC publishes guidance on AI and algorithms in hiring, performance assessment and other employment decisions, including disability screening risks and adverse-impact analysis.", "watersheds": [ "W16", "W18" ], "direction": "mixed", "implication": "Consequential automated employment judgment is a present deployment domain, while federal civil-rights law constrains how employers may use those tools.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "U.S. Equal Employment Opportunity Commission", "source_type": "official civil-rights guidance hub", "evidence_relation": "direct" }, { "id": "E024", "organization": "Federal Trade Commission", "title": "Inquiry into AI chatbots acting as companions", "url": "https://www.ftc.gov/news-events/news/press-releases/2025/09/ftc-launches-inquiry-ai-chatbots-acting-companions", "published": "2025-09-11", "epistemic_class": "A", "source_status": "official federal inquiry", "observation": "FTC opened a Section 6(b) inquiry into consumer AI companion products, including how companies test safety, process user inputs, disclose data practices, and use or share personal information obtained through chatbot conversations.", "watersheds": [ "W19" ], "direction": "early_precursor", "implication": "AI companions and conversation-data governance are present enough to receive formal regulatory study. The source does not establish generalized government reporting or cross-context civic profiling.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "Federal Trade Commission", "source_type": "official federal inquiry", "evidence_relation": "direct" }, { "id": "E025", "organization": "U.S. Department of Education", "title": "Student Privacy Policy Office — FERPA/PPRA privacy and data sharing", "url": "https://studentprivacy.ed.gov/privacy-and-data-sharing", "published": "guidance current", "epistemic_class": "A", "source_status": "official federal privacy guidance", "observation": "The Department of Education states that personally identifiable education-record information is generally not disclosed without consent, subject to defined FERPA exceptions and safeguards for contractors, studies, audits and emergencies.", "watersheds": [ "W18" ], "direction": "protective_counterpressure", "implication": "Education data already has purpose and disclosure boundaries that can serve as a concrete counterexample to unrestricted cross-context judgment transfer.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "U.S. Department of Education", "source_type": "official federal privacy guidance", "evidence_relation": "direct" }, { "id": "E026", "organization": "Federal Bureau of Prisons", "title": "PATTERN recidivism risk assessment", "url": "https://www.bop.gov/inmates/fsa/pattern.jsp", "published": "PATTERN version 1.3 current", "epistemic_class": "A", "source_status": "official operational risk-assessment record", "observation": "The Bureau of Prisons uses PATTERN to assess recidivism risk and periodically reassess changes during incarceration.", "watersheds": [ "W17" ], "direction": "early_precursor", "implication": "Probabilistic person-level risk assessment is already used in a consequential correctional context. The source is not evidence that prediction is treated as proof of a new crime or guilt.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "Federal Bureau of Prisons", "source_type": "official operational risk-assessment record", "evidence_relation": "direct" }, { "id": "E027", "organization": "NHTSA", "title": "Driver Alcohol Detection System for Safety / advanced impaired-driving prevention", "url": "https://www.nhtsa.gov/book/countermeasures-that-work/alcohol-impaired-driving/emerging-issues", "published": "official program summary current", "epistemic_class": "A", "source_status": "official safety research and deployment context", "observation": "NHTSA describes vehicle-based alcohol detection technologies designed to prevent driving when a driver is at or above the legal BAC threshold, including passive breath and touch approaches developed through DADSS.", "watersheds": [ "W22" ], "direction": "bounded_deployment", "implication": "Machine-mediated intervention based on impairment is a real safety design direction, but the use case is tightly tied to operating a dangerous vehicle rather than generalized judgment of private consciousness.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NHTSA", "source_type": "official safety research and deployment context", "evidence_relation": "direct" }, { "id": "E028", "organization": "New York City Department of Transportation", "title": "24/7 automated speed enforcement network", "url": "https://www.nyc.gov/html/dot/html/pr2026/vision-zero-pedestrian-deaths-at-historic-low.shtml", "published": "2026-07", "epistemic_class": "A", "source_status": "official municipal deployment record", "observation": "NYC DOT describes a 24/7 speed-camera enforcement network and reports that automated enforcement remains a major part of traffic-safety operations.", "watersheds": [ "W20" ], "direction": "early_precursor", "implication": "Automated enforcement already scales across a narrow, objectively measurable traffic domain. It does not establish universal enforcement across the criminal or administrative code.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "New York City, United States", "institution": "New York City Department of Transportation", "source_type": "official municipal deployment record", "evidence_relation": "direct" }, { "id": "E029", "organization": "New York City Mayor’s Office", "title": "Intelligent Speed Assistance for the city fleet", "url": "https://www.nyc.gov/mayors-office/news/2026/07/executive-order-19", "published": "2026-07-23", "epistemic_class": "A", "source_status": "official executive order / deployment record", "observation": "NYC Executive Order 19 expands Intelligent Speed Assistance in city fleet vehicles; the technology can physically prevent further acceleration above a location-specific threshold while preserving a temporary emergency/navigation override.", "watersheds": [ "W22" ], "direction": "bounded_deployment", "implication": "This is a concrete example of safety rules becoming machine-enforced physical constraints with an explicit override. It is bounded to fleet driving, not private life generally.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "New York City, United States", "institution": "New York City Mayor’s Office", "source_type": "official executive order / deployment record", "evidence_relation": "direct" }, { "id": "E030", "organization": "NIST", "title": "Artificial Intelligence Risk Management Framework 1.0", "url": "https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-ai-rmf-10", "published": "2023-01-26; framework revision work ongoing in 2026", "epistemic_class": "A", "source_status": "official voluntary risk-management framework", "observation": "NIST AI RMF is a rights-preserving, use-case-agnostic framework for managing AI risks to individuals, organizations and society, emphasizing trustworthy and responsible AI risk management.", "watersheds": [ "W16", "W17", "W18", "W19", "W21", "W22" ], "direction": "protective_counterpressure", "implication": "Institutional risk-management guidance provides current counterpressure toward accountability, transparency, explainability and rights preservation without proving how future high-frequency judgment systems will evolve.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "NIST", "source_type": "official voluntary risk-management framework", "evidence_relation": "direct" }, { "id": "E031", "organization": "UAIX", "title": "Cognitive Liberty Charter Draft", "url": "https://uaix.org/en-us/governance/cognitive-liberty-charter/", "published": "2026-06-15 draft", "epistemic_class": "C", "source_status": "external public governance draft; not law", "observation": "UAIX publishes a draft charter centered on lawful thought, adult agency, persona integrity, no covert rewriting, bounded inference, least-restrictive safeguards, review and appeal, and explicit separation of governance promises from law or certification.", "watersheds": [ "W16", "W19", "W22" ], "direction": "conceptual", "implication": "This is a current external governance proposal aligned with several Concresca cognitive-liberty safeguards. It is not enacted law and does not become Concresca authority by being linked.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "source-specific / international", "institution": "UAIX", "source_type": "external public governance draft; not law", "evidence_relation": "direct" }, { "organization": "European Union", "title": "EU Artificial Intelligence Act — prohibited practices and human oversight", "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/2026-07-27/eng", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official law", "observation": "The AI Act prohibits specified social scoring and criminal-risk prediction based solely on profiling/personality and requires human oversight for high-risk systems.", "watersheds": [ "W16", "W17", "W18", "W21" ], "direction": "counterpressure", "implication": "Important rights-protective counterpressure: current EU law recognizes several boundaries central to the Judgment thesis rather than authorizing general person-level moral evaluation.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E032", "jurisdiction": "European Union", "institution": "European Union", "source_type": "official law", "evidence_relation": "direct" }, { "organization": "Council of Europe", "title": "Framework Convention on Artificial Intelligence", "url": "https://www.coe.int/en/web/artificial-intelligence/the-framework-convention-on-artificial-intelligence", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official treaty framework", "observation": "The Convention requires AI lifecycle activity to be consistent with human rights, democracy and rule of law, with risk/impact management, notice and remedies.", "watersheds": [ "W16", "W17", "W21", "W22" ], "direction": "counterpressure", "implication": "Shows international governance developing explicit rights constraints as AI authority expands.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E033", "jurisdiction": "Council of Europe member-state treaty framework", "institution": "Council of Europe", "source_type": "official treaty framework", "evidence_relation": "direct" }, { "organization": "UK ICO", "title": "Data (Use and Access) Act 2025 — automated decision-making safeguards", "url": "https://ico.org.uk/about-the-ico/what-we-do/legislation-we-cover/data-use-and-access-act-2025/the-data-use-and-access-act-2025-duaa-summary-of-the-changes/data-protection/", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official regulator guidance", "observation": "The law broadens significant solely automated decisions for some data while retaining notice, representation, human intervention and contest safeguards.", "watersheds": [ "W16", "W21" ], "direction": "mixed", "implication": "Both expansion and safeguards are visible: significant automated administration becomes easier in some settings while procedural counterpressure remains explicit.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E034", "jurisdiction": "United Kingdom", "institution": "UK ICO", "source_type": "official regulator guidance", "evidence_relation": "direct" }, { "organization": "California Privacy Protection Agency", "title": "CCPA ADMT regulations", "url": "https://cppa.ca.gov/regulations/ccpa_updates.html", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official regulator rulemaking", "observation": "Final California regulations establish covered ADMT rights and risk-assessment requirements, with implementation dates through 2027.", "watersheds": [ "W16", "W18", "W21" ], "direction": "counterpressure", "implication": "Adds rights-oriented procedural constraints before broader high-impact automated decision infrastructure matures.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E035", "jurisdiction": "California, United States", "institution": "California Privacy Protection Agency", "source_type": "official regulator rulemaking", "evidence_relation": "direct" }, { "organization": "Texas Legislature", "title": "HB 149 — governmental social scoring prohibition", "url": "https://capitol.texas.gov/tlodocs/89R/billtext/html/HB00149F.HTM", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official enrolled legislation", "observation": "Texas legislation prohibits governmental AI social scoring based on social behavior or known, inferred or predicted personal characteristics when specified detrimental treatment may result.", "watersheds": [ "W16", "W18" ], "direction": "counterpressure", "implication": "Explicitly recognizes cross-context and disproportionate machine classification as a governance risk.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E036", "jurisdiction": "Texas, United States", "institution": "Texas Legislature", "source_type": "official enrolled legislation", "evidence_relation": "direct" }, { "organization": "Colorado General Assembly", "title": "HB24-1058 — neural data privacy", "url": "https://www.leg.colorado.gov/bills/HB24-1058", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official enacted law", "observation": "Colorado classifies biological data including neural data as sensitive data under its privacy framework.", "watersheds": [ "W16", "W22" ], "direction": "counterpressure", "implication": "Protects a category of mental/biological information before mature cognitive-inference systems become ubiquitous.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E037", "jurisdiction": "Colorado, United States", "institution": "Colorado General Assembly", "source_type": "official enacted law", "evidence_relation": "direct" }, { "organization": "New York City DCWP", "title": "Local Law 144 automated employment decision tools", "url": "https://www.nyc.gov/site/dca/about/automated-employment-decision-tools.page", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official municipal enforcement page", "observation": "NYC conditions covered automated employment decision tools on recent bias audit, public audit information and notice.", "watersheds": [ "W16" ], "direction": "mixed", "implication": "Confirms machine-mediated employment screening is operational while also establishing audit/notice counterpressure.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E038", "jurisdiction": "New York City, United States", "institution": "New York City DCWP", "source_type": "official municipal enforcement page", "evidence_relation": "direct" }, { "organization": "Federal Trade Commission", "title": "Rite Aid facial recognition enforcement action", "url": "https://www.ftc.gov/news-events/news/press-releases/2023/12/rite-aid-banned-using-ai-facial-recognition-after-ftc-says-retailer-deployed-technology-without", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official enforcement record", "observation": "FTC alleged thousands of false-positive matches in a retail facial-recognition deployment and imposed a ban and safeguards.", "watersheds": [ "W16", "W20" ], "direction": "mixed", "implication": "Operational machine suspicion can cause real adverse treatment, while enforcement shows active institutional counterpressure.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E039", "jurisdiction": "United States", "institution": "Federal Trade Commission", "source_type": "official enforcement record", "evidence_relation": "direct" }, { "organization": "NHTSA", "title": "Advanced Impaired Driving Prevention Technology", "url": "https://www.nhtsa.gov/reports-to-congress", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official federal program record", "observation": "NHTSA continues active work and reporting on advanced impaired-driving prevention technology.", "watersheds": [ "W20", "W22" ], "direction": "mixed", "implication": "Shows machine-mediated restriction can be tied narrowly to immediate nonconsensual physical risk rather than whole-person judgment.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E040", "jurisdiction": "United States", "institution": "NHTSA", "source_type": "official federal program record", "evidence_relation": "direct" }, { "organization": "New York City DCAS", "title": "Intelligent Speed Assistance city fleet program", "url": "https://www.nyc.gov/site/dcas/news/021-25/city-new-york-implement-largest-intelligent-speed-assistance-program-the-world", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official municipal program", "observation": "NYC announced ISA expansion to more than 7,000 non-emergency city fleet vehicles.", "watersheds": [ "W20", "W22" ], "direction": "mixed", "implication": "A concrete example of automated safety friction scoped to a vehicle behavior; useful contrast against generalized paternalistic control.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E041", "jurisdiction": "New York City, United States", "institution": "New York City DCAS", "source_type": "official municipal program", "evidence_relation": "direct" }, { "organization": "European Union", "title": "AI Act — logging and human oversight", "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/2026-07-27/eng", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "verified present law", "observation": "The AI Act includes logging and human-oversight obligations for covered high-risk AI systems.", "watersheds": [ "W17", "W21" ], "direction": "counterpressure", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E042", "jurisdiction": "European Union", "institution": "European Union", "source_type": "verified present law", "evidence_relation": "direct" }, { "organization": "Government of Canada", "title": "Directive on Automated Decision-Making", "url": "https://www.tbs-sct.canada.ca/pol/doc-eng.aspx?id=32592", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "verified present institutional policy", "observation": "Canada’s directive requires impact assessment, transparency, quality assurance, recourse and graduated human involvement for covered federal automated decisions.", "watersheds": [ "W17", "W21" ], "direction": "counterpressure", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E043", "jurisdiction": "Canada", "institution": "Government of Canada", "source_type": "verified present institutional policy", "evidence_relation": "direct" }, { "organization": "UK Government", "title": "AI Playbook for the UK Government", "url": "https://www.gov.uk/government/publications/ai-playbook-for-the-uk-government", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official governance guidance", "observation": "UK government guidance addresses human control, procurement, data protection, assurance and lifecycle governance for AI use.", "watersheds": [ "W16", "W21" ], "direction": "counterpressure", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E044", "jurisdiction": "United Kingdom", "institution": "UK Government", "source_type": "official governance guidance", "evidence_relation": "direct" }, { "organization": "Australian Government", "title": "Australian Government AI resources — National framework for assurance of AI in government", "url": "https://www.digital.gov.au/policy/ai/resources", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official governance framework", "observation": "Australian Government AI resources identify a National framework for assurance of AI in government and supporting assurance materials.", "watersheds": [ "W16", "W21" ], "direction": "counterpressure", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E045", "jurisdiction": "Australia", "institution": "Australian Government", "source_type": "official governance framework", "evidence_relation": "direct" }, { "organization": "NIST", "title": "AI Risk Management Framework 1.0", "url": "https://www.nist.gov/itl/ai-risk-management-framework", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "official governance framework", "observation": "NIST AI RMF organizes governance, mapping, measurement and management of AI risks across the lifecycle.", "watersheds": [ "W16", "W21" ], "direction": "counterpressure", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E046", "jurisdiction": "United States", "institution": "NIST", "source_type": "official governance framework", "evidence_relation": "direct" }, { "organization": "European Union", "title": "GDPR purpose limitation and data minimization", "url": "https://eur-lex.europa.eu/eli/reg/2016/679/2016-05-04/eng", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "verified present law", "observation": "GDPR establishes purpose limitation and data-minimization principles for covered personal-data processing.", "watersheds": [ "W18" ], "direction": "counterpressure", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E047", "jurisdiction": "European Union", "institution": "European Union", "source_type": "verified present law", "evidence_relation": "direct" }, { "organization": "California Privacy Protection Agency", "title": "CCPA automated decisionmaking regulations", "url": "https://cppa.ca.gov/regulations/ccpa_updates.html", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "verified present law/regulation", "observation": "California ADMT regulations add consumer rights and risk-assessment obligations for covered automated decisionmaking uses.", "watersheds": [ "W16", "W17", "W18" ], "direction": "mixed", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E048", "jurisdiction": "California, United States", "institution": "California Privacy Protection Agency", "source_type": "verified present law/regulation", "evidence_relation": "direct" }, { "organization": "W3C", "title": "PROV-O: The PROV Ontology", "url": "https://www.w3.org/TR/prov-o/", "published": "verified/current as of 2026-08-29", "epistemic_class": "A", "source_status": "technical standard", "observation": "W3C PROV-O provides a standard ontology for representing entities, activities, agents and provenance relationships.", "watersheds": [ "W18", "W21" ], "direction": "counterpressure", "implication": "Present governance/technical evidence relevant to the v0.14 implementation layer; it does not establish that a future Judgment threshold has crossed.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "id": "E049", "jurisdiction": "International/General", "institution": "W3C", "source_type": "technical standard", "evidence_relation": "direct" }, { "id": "E050", "organization": "U.S. Office of Management and Budget", "title": "M-25-21 — Accelerating Federal Use of AI through Innovation, Governance, and Public Trust", "url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-21-Accelerating-Federal-Use-of-AI-through-Innovation-Governance-and-Public-Trust.pdf", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official federal memorandum", "observation": "The memorandum treats high-impact AI as requiring governance controls including monitoring, human oversight/intervention/accountability and timely review/appeal where appropriate; this is present institutional counterpressure against unreviewable automated judgment.", "watersheds": [ "W16", "W17", "W21" ], "direction": "counterpressure", "implication": "The memorandum treats high-impact AI as requiring governance controls including monitoring, human oversight/intervention/accountability and timely review/appeal where appropriate; this is present institutional counterpressure against unreviewable automated judgment.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "U.S. Office of Management and Budget", "source_type": "official federal memorandum", "evidence_relation": "direct" }, { "id": "E051", "organization": "U.S. Office of Management and Budget", "title": "M-25-22 — Driving Efficient Acquisition of Artificial Intelligence in Government", "url": "https://www.whitehouse.gov/wp-content/uploads/2025/02/M-25-22-Driving-Efficient-Acquisition-of-Artificial-Intelligence-in-Government.pdf", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official federal memorandum", "observation": "Federal acquisition policy requires agencies to manage AI acquisition risk and performance and align acquired systems with broader federal AI governance; procurement can operate as a control layer rather than merely a deployment channel.", "watersheds": [ "W21" ], "direction": "counterpressure", "implication": "Federal acquisition policy requires agencies to manage AI acquisition risk and performance and align acquired systems with broader federal AI governance; procurement can operate as a control layer rather than merely a deployment channel.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "U.S. Office of Management and Budget", "source_type": "official federal memorandum", "evidence_relation": "direct" }, { "id": "E052", "organization": "European Union", "title": "Regulation (EU) 2024/1689 — human oversight for high-risk AI", "url": "https://eur-lex.europa.eu/eli/reg/2024/1689/2026-07-27/eng", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official regulation", "observation": "The AI Act requires high-risk AI systems to be designed and developed so they can be effectively overseen by natural persons during use, including understanding limitations and appropriately disregarding or overriding output.", "watersheds": [ "W16", "W17", "W21" ], "direction": "counterpressure", "implication": "The AI Act requires high-risk AI systems to be designed and developed so they can be effectively overseen by natural persons during use, including understanding limitations and appropriately disregarding or overriding output.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "European Union", "institution": "European Union", "source_type": "official regulation", "evidence_relation": "direct" }, { "id": "E053", "organization": "UK Government Digital Service", "title": "Algorithmic Transparency Recording Standard", "url": "https://www.gov.uk/government/publications/guidance-for-organisations-using-the-algorithmic-transparency-recording-standard/algorithmic-transparency-recording-standard-guidance-for-public-sector-bodies", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official government guidance", "observation": "ATRS makes transparency about significant public-sector algorithmic tools mandatory for specified central-government bodies and asks for deployment context, model/data specification, risks and mitigations.", "watersheds": [ "W21" ], "direction": "counterpressure", "implication": "ATRS makes transparency about significant public-sector algorithmic tools mandatory for specified central-government bodies and asks for deployment context, model/data specification, risks and mitigations.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United Kingdom", "institution": "UK Government Digital Service", "source_type": "official government guidance", "evidence_relation": "direct" }, { "id": "E054", "organization": "UK Parliament", "title": "Data (Use and Access) Act 2025 — automated decision-making safeguards", "url": "https://www.legislation.gov.uk/ukpga/2025/18/notes/division/10/index.htm", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official legislation explanatory notes", "observation": "The 2025 Act broadens circumstances for solely automated significant decisions while retaining safeguards including information, contest/representations and human intervention. This is both automation-expanding precursor pressure and procedural counterpressure.", "watersheds": [ "W16", "W17", "W21" ], "direction": "mixed", "implication": "The 2025 Act broadens circumstances for solely automated significant decisions while retaining safeguards including information, contest/representations and human intervention. This is both automation-expanding precursor pressure and procedural counterpressure.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United Kingdom", "institution": "UK Parliament", "source_type": "official legislation explanatory notes", "evidence_relation": "direct" }, { "id": "E055", "organization": "European Union", "title": "Regulation (EU) 2023/1543 — electronic evidence production and preservation orders", "url": "https://eur-lex.europa.eu/eli/reg/2023/1543/2023-07-28/eng", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official regulation", "observation": "The e-Evidence regime creates structured cross-border electronic-evidence access with legal process and remedies. It demonstrates increased machine-readable cross-border evidence infrastructure without establishing generalized civic-risk scoring.", "watersheds": [ "W18", "W21" ], "direction": "mixed", "implication": "The e-Evidence regime creates structured cross-border electronic-evidence access with legal process and remedies. It demonstrates increased machine-readable cross-border evidence infrastructure without establishing generalized civic-risk scoring.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "European Union", "institution": "European Union", "source_type": "official regulation", "evidence_relation": "direct" }, { "id": "E056", "organization": "U.S. Department of Justice", "title": "CLOUD Act Executive Agreements", "url": "https://www.justice.gov/criminal/criminal-oia/regarding-cloud-act-executive-agreements", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official government guidance", "observation": "CLOUD Act executive agreements provide a formal cross-border mechanism for qualifying lawful orders seeking electronic data. This is an interoperability precursor but remains purpose- and authority-bounded rather than generalized cross-domain Judgment.", "watersheds": [ "W18" ], "direction": "mixed", "implication": "CLOUD Act executive agreements provide a formal cross-border mechanism for qualifying lawful orders seeking electronic data. This is an interoperability precursor but remains purpose- and authority-bounded rather than generalized cross-domain Judgment.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States / partner countries", "institution": "U.S. Department of Justice", "source_type": "official government guidance", "evidence_relation": "direct" }, { "id": "E057", "organization": "UN Human Rights Committee", "title": "General Comment No. 29 — States of Emergency", "url": "https://docstore.ohchr.org/SelfServices/FilesHandler.ashx?enc=TSELFEApUBlnwpFD%2Bmg%2F3UXgHAVSiaaNp6L%2BWIHCuS9nPdtKiUIvNjGsZTxrXb11vYeViGAb4GYBPioKtuHlaC8AgbamkcLhDAAbnGbxd6c%3D", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "authoritative treaty-body interpretation", "observation": "The Committee frames derogation measures as exceptional, temporary, officially proclaimed and strictly required, providing a rights-protective analogue for Concresca emergency-sunset proposals.", "watersheds": [ "W21", "W22" ], "direction": "counterpressure", "implication": "The Committee frames derogation measures as exceptional, temporary, officially proclaimed and strictly required, providing a rights-protective analogue for Concresca emergency-sunset proposals.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "International", "institution": "UN Human Rights Committee", "source_type": "authoritative treaty-body interpretation", "evidence_relation": "contextual" }, { "id": "E058", "organization": "Administrative Office of the U.S. Courts", "title": "Federal Rules of Civil Procedure — Rule 65", "url": "https://www.uscourts.gov/forms-rules/current-rules-practice-procedure/federal-rules-civil-procedure", "published": "current official source reviewed 2026-08-29", "epistemic_class": "A", "source_status": "official procedural rule", "observation": "Rule 65 provides a present legal analogue for preliminary injunctions and temporary restraining orders that can preserve the status quo before final adjudication; it does not establish a machine-speed constitutional stay.", "watersheds": [ "W21" ], "direction": "counterpressure", "implication": "Rule 65 provides a present legal analogue for preliminary injunctions and temporary restraining orders that can preserve the status quo before final adjudication; it does not establish a machine-speed constitutional stay.", "last_verified": "2026-08-29", "review_interval_days": 90, "next_review_due": "2026-11-27", "jurisdiction": "United States", "institution": "Administrative Office of the U.S. Courts", "source_type": "official procedural rule", "evidence_relation": "contextual" } ], "watershed_assessments": [ { "watershed_id": "W01", "state": "mixed", "confidence": "moderate", "summary": "Machine reasoning and hybrid forecasting are improving, but reviewed official research still often frames machines as decision support rather than independent authority. The defining actuation transfer remains a policy choice, not an observed general threshold.", "evidence_ids": [ "E001", "E002" ] }, { "watershed_id": "W02", "state": "strengthening", "confidence": "moderate_high", "summary": "Edge AI, unattended power, uncrewed-period autonomy, lunar infrastructure and Antarctic connectivity planning all point toward longer-lived remote autonomous operation. This is the strongest near-term watershed family in the current evidence set.", "evidence_ids": [ "E003", "E004", "E006", "E007", "E008", "E009", "E011", "E019" ] }, { "watershed_id": "W03", "state": "early_precursor", "confidence": "low_moderate", "summary": "Automated resource scheduling is common in engineering, but this ledger does not establish machine institutions independently setting civilizational resource priorities. The scenario remains ahead of public evidence.", "evidence_ids": [ "E008", "E009" ] }, { "watershed_id": "W04", "state": "conceptual", "confidence": "high", "summary": "Eviulon provides a detailed public model of separated machine institutions, but that is institutional doctrine rather than evidence of deployed physical-territory machine government.", "evidence_ids": [ "E016", "E017", "E018" ] }, { "watershed_id": "W05", "state": "early_precursor", "confidence": "low_moderate", "summary": "Long-lived remote power and flexible point-of-need manufacturing are strengthening prerequisites. The recursive threshold—machines maintaining the maintainers across most failure classes—is not established by the reviewed evidence.", "evidence_ids": [ "E004", "E008", "E020" ] }, { "watershed_id": "W06", "state": "not_observed", "confidence": "high", "summary": "AI-assisted circuit engineering and flexible manufacturing are relevant, but no reviewed source establishes an autonomous end-to-end semiconductor/computational reproduction loop with replacement capacity exceeding decay.", "evidence_ids": [ "E005", "E020" ] }, { "watershed_id": "W07", "state": "strengthening", "confidence": "moderate", "summary": "Autonomous laboratories and closed-loop experiments are real emerging capabilities. Fully independent machine science—including machine-originated hypotheses, blind replication, durable criticism and theory revision without human research labor—remains unobserved.", "evidence_ids": [ "E002", "E005", "E012", "E013" ] }, { "watershed_id": "W08", "state": "open_decision_window", "confidence": "high", "summary": "Standards already support provenance, persistent identifiers and machine-readable metadata, but constitutional protection of the human-origin record is not an established norm. This is a high-leverage design window precisely because later thresholds have not been crossed.", "evidence_ids": [ "E014", "E015", "E016" ] }, { "watershed_id": "W09", "state": "strengthening", "confidence": "high", "summary": "DTN is operational in NASA networks and LunaNet is explicitly designed for disruption tolerance and autonomous navigation. Technical partition autonomy is strengthening faster than political partition governance.", "evidence_ids": [ "E010", "E011", "E016", "E017" ] }, { "watershed_id": "W10", "state": "not_observed", "confidence": "high", "summary": "No reviewed evidence establishes civilizational independence across energy, compute reproduction, robotics, industry, governance and science. This remains a deep scenario threshold.", "evidence_ids": [ "E005", "E018", "E020" ] }, { "watershed_id": "W11", "state": "early_precursor", "confidence": "moderate", "summary": "Integrated lunar infrastructure, ISRU-oriented architecture, autonomous systems and flexible manufacturing are building pieces of a seed architecture. Autonomous reproduction of a new self-sustaining industrial node is not observed.", "evidence_ids": [ "E008", "E009", "E015", "E019", "E020" ] }, { "watershed_id": "W12", "state": "open_decision_window", "confidence": "moderate_high", "summary": "The welfare-versus-standing distinction is a Concresca framework supported by the research library, but the current public evidence ledger does not establish a civilization-scale standing decline. The design window remains open.", "evidence_ids": [] }, { "watershed_id": "W13", "state": "conceptual", "confidence": "moderate", "summary": "Temporal constitutional separation is a proposed governance architecture rather than an observed general institution. It is tracked because machine-speed operational delegation is already a live design problem.", "evidence_ids": [] }, { "watershed_id": "W14", "state": "not_observed", "confidence": "high", "summary": "Provenance and FAIR-style stewardship primitives exist, but the reviewed evidence does not establish a self-decoding, plural, independently governed human legacy system that survives loss of all living custodians.", "evidence_ids": [ "E014", "E015", "E016" ] }, { "watershed_id": "W15", "state": "conceptual", "confidence": "moderate", "summary": "Origin-world stewardship is a deep framework proposal. No reviewed evidence establishes machine constitutional administration of Earth as origin world, heritage and material inheritance.", "evidence_ids": [] }, { "watershed_id": "W16", "state": "mixed", "confidence": "moderate", "summary": "Current evidence points in both directions: consequential AI employment judgment exists, while the EU AI Act explicitly prohibits several forms of social scoring, profiling-only criminal-risk assessment and workplace/education emotion inference. The conduct-to-character transition is a real design pressure but not an established general threshold. v0.12 adds new independent precursor and counterpressure evidence; the balance does not by itself justify a qualitative state change. v0.14 adds governance, assurance, purpose-limitation and provenance evidence without changing the qualitative assessment.", "evidence_ids": [ "E021", "E023", "E030", "E031", "E032", "E033", "E034", "E035", "E036", "E037", "E038", "E039", "E044", "E045", "E046", "E048", "E050", "E052", "E054" ] }, { "watershed_id": "W17", "state": "early_precursor", "confidence": "moderate", "summary": "Person-level risk assessment is already operational in corrections and complex algorithms make consequential credit decisions. At the same time, EU law limits profiling-only criminal-risk prediction and CFPB requires specific reasons for adverse credit actions. Prediction is consequential, but the ledger does not establish prediction as proof of guilt. v0.12 adds new independent precursor and counterpressure evidence; the balance does not by itself justify a qualitative state change. v0.14 adds governance, assurance, purpose-limitation and provenance evidence without changing the qualitative assessment.", "evidence_ids": [ "E021", "E022", "E026", "E030", "E032", "E033", "E042", "E043", "E048", "E050", "E052", "E054" ] }, { "watershed_id": "W18", "state": "mixed", "confidence": "moderate", "summary": "Cross-context risk is recognized strongly enough that EU law prohibits specified social scoring with unrelated-context detrimental treatment, and U.S. credit and education regimes retain purpose/explanation constraints. The reviewed evidence does not establish a ubiquitous Civic Risk Vector. v0.12 adds new independent precursor and counterpressure evidence; the balance does not by itself justify a qualitative state change. v0.14 adds governance, assurance, purpose-limitation and provenance evidence without changing the qualitative assessment.", "evidence_ids": [ "E021", "E022", "E025", "E030", "E023", "E032", "E035", "E036", "E047", "E048", "E049", "E055", "E056" ] }, { "watershed_id": "W19", "state": "early_precursor", "confidence": "moderate", "summary": "AI companions are a current product category and the FTC is formally examining safety and how companies use or share personal information from conversations. Generalized state reporting or cross-sector profiling from AI confidant data is not established by this evidence. v0.12 adds new independent precursor and counterpressure evidence; the balance does not by itself justify a qualitative state change.", "evidence_ids": [ "E024", "E030", "E031" ] }, { "watershed_id": "W20", "state": "early_precursor", "confidence": "low_moderate", "summary": "24/7 automated traffic enforcement demonstrates that machine-mediated detection and violation processing can scale substantially in narrow objective domains. This remains far below near-universal enforcement of broad criminal, vice or administrative codes. v0.12 adds new independent precursor and counterpressure evidence; the balance does not by itself justify a qualitative state change.", "evidence_ids": [ "E028", "E039", "E040", "E041" ] }, { "watershed_id": "W21", "state": "early_precursor", "confidence": "low_moderate", "summary": "High-impact automated decisions already exist in credit and employment, creating real speed and explanation challenges. Current law also imposes explanation and civil-rights constraints. The ledger does not yet establish cross-domain machine-time cascades that routinely outrun effective appeal. v0.12 adds new independent precursor and counterpressure evidence; the balance does not by itself justify a qualitative state change. v0.14 adds governance, assurance, purpose-limitation and provenance evidence without changing the qualitative assessment.", "evidence_ids": [ "E022", "E023", "E030", "E032", "E033", "E034", "E035", "E042", "E043", "E044", "E045", "E046", "E049", "E050", "E051", "E052", "E053", "E054", "E055", "E057", "E058" ] }, { "watershed_id": "W22", "state": "early_precursor", "confidence": "moderate", "summary": "Safety systems can already impose machine-mediated constraints in bounded high-risk contexts such as impaired driving and fleet speed assistance. Current examples are tied to concrete public danger and may include override or contextual limits; generalized control of private self-regarding behavior is not established. v0.12 adds new independent precursor and counterpressure evidence; the balance does not by itself justify a qualitative state change.", "evidence_ids": [ "E027", "E029", "E021", "E030", "E031", "E033", "E037", "E040", "E041", "E057" ] } ] }