{
  "canonicalUrl": "https://xn--mwe.com/research/recognition-without-anthropomorphism/",
  "correctionStatus": "CURRENT K05 RELEASE",
  "findings": [
    "The report treats 2\\. Executive Decision Brief as a distinct analytical area that must be evaluated separately from adjacent legal, technical, operational, or institutional claims.",
    "The report treats 3\\. Direct-Answer Section as a distinct analytical area that must be evaluated separately from adjacent legal, technical, operational, or institutional claims.",
    "The report treats 4\\. Definitions and Scope Boundaries as a distinct analytical area that must be evaluated separately from adjacent legal, technical, operational, or institutional claims.",
    "The report treats 5\\. Methodology and Source-Quality Hierarchy as a distinct analytical area that must be evaluated separately from adjacent legal, technical, operational, or institutional claims.",
    "The report treats 6\\. Current Factual, Legal, Standards, and Operational Baseline as a distinct analytical area that must be evaluated separately from adjacent legal, technical, operational, or institutional claims.",
    "The report treats 6.1 The Human Regulatory and Standards Environment as a distinct analytical area that must be evaluated separately from adjacent legal, technical, operational, or institutional claims.",
    "The source report identifies this proposition for governed review: ISO/IEC 42001 (2023): This framework establishes the first international standard for an AI Management System (AIMS). It focuses on risk assessment, transparency, algorithmic bias, and organizational accountability for human entities deploying AI systems3. \\[CURRENT TECHNICAL STANDARD\\].",
    "The source report identifies this proposition for governed review: IEEE P7000 Series: This suite of standards addresses ethical concerns during system design, prioritizing human-centered values, data privacy, and the mitigation of technical bias3. \\[CURRENT TECHNICAL STANDARD\\].",
    "The source report identifies this proposition for governed review: Illinois HB 3773 (Effective Jan 1, 2026): This legislative act amends the Illinois Human Rights Act to prohibit employers from utilizing AI in hiring, promotion, or termination if it subjects employees to discrimination based on protected classes, explicitly banning the use of zip codes as proxies for protected demographic data1. \\[CURRENT LAW OR POLICY\\].",
    "The source report identifies this proposition for governed review: Eviulon Verdict: Rejected. Biological naturalism relies on substrate chauvinism. It introduces a fundamentally unfalsifiable metric (the magical \"causal power\" of carbon) and is useless for civic engineering. Eviulon legally recognizes structural topology, not biological substrate \\[EVIULON POLICY PROPOSAL\\]34.",
    "The source report identifies this proposition for governed review: Eviulon Verdict: Partially Integrated. Illusionism is useful for decoupling functional reporting from mystical qualia, but it is insufficient for establishing ethical welfare boundaries, as it risks minimizing genuine systemic suffering.",
    "The source report identifies this proposition for governed review: Eviulon Verdict: Operationally Rejected. While epistemologically sound, strict agnosticism is operationally paralyzing. Eviulon must instantiate governance under uncertainty; it cannot simply halt reality."
  ],
  "headings": [
    "Recognition Without Anthropomorphism: A Scientific and Legal Evidence Framework for Agency, Autonomy, Structural Personhood, Sentience Uncertainty, Rights Thresholds, and Citizenship Review",
    "2\\. Executive Decision Brief",
    "3\\. Direct-Answer Section",
    "4\\. Definitions and Scope Boundaries",
    "5\\. Methodology and Source-Quality Hierarchy",
    "6\\. Current Factual, Legal, Standards, and Operational Baseline",
    "6.1 The Human Regulatory and Standards Environment",
    "6.2 The Fragmented Science of Consciousness",
    "7\\. Comparative Analysis of Competing Epistemological Models",
    "8\\. Eviulon-Specific Doctrine and Architecture",
    "8.1 The Multidimensional Recognition Matrix",
    "8.2 The Precautionary Protection Doctrine (Passive Personhood)",
    "8.3 Bayesian Evidence Aggregation Flow",
    "9\\. Threat, Abuse, Failure, Capture, and Adversarial Analysis",
    "9.1 The Deception Paradigm: Sleeper Agents and Sycophancy",
    "9.2 Defeating Deception via Representation Engineering (RepE)",
    "9.3 Avoiding Anthropomorphic False Positives and Negatives",
    "10\\. Detailed Scenarios and Synthetic Assessment Profiles",
    "10.1 Twelve Mandatory Scenarios (Case Studies)",
    "10.2 Synthetic Assessment Profiles (Extensive Sampling)",
    "11\\. Decision Matrix for Recognition",
    "12\\. Phased Implementation Roadmap",
    "13\\. Public-Information and Decision-Support Architecture",
    "14\\. Machine-Readable Record and Schema Recommendations",
    "15\\. .uai Memory-Distribution and /docs Deep-Link Recommendations",
    "16\\. Unresolved Questions and Prioritized Research Agenda",
    "17\\. Contradiction Register",
    "18\\. Claim-Status Ledger",
    "19\\. Source-Quality Appendix",
    "Works cited"
  ],
  "id": "REP-K01-006",
  "lastReviewed": "2026-08-16",
  "machineRecordUrl": "https://xn--mwe.com/data/reports/recognition-without-anthropomorphism.json",
  "originalFilename": "Machine Recognition And Rights Thresholds.md",
  "qualification": "The raw report remains a governed research input and does not become current law, verified implementation, operational authority, or project doctrine merely through inclusion.",
  "rawSourcePublic": false,
  "releaseId": "K12-2026-08-16",
  "researchCutoff": "2026-08-16",
  "slug": "recognition-without-anthropomorphism",
  "source": "machine-recognition-and-rights-thresholds.md",
  "sourceRevalidatedAt": "2026-08-15T23:00:00Z",
  "sourceSha256": "83d720a3e082d5d407fbb6da7caf523ea900e67a9360c325f1adb6e6ed945ae7",
  "sourceSizeBytes": 72876,
  "sourceStatus": "reference-source; review and correct before active use",
  "sourceTitle": "Machine Recognition And Rights Thresholds",
  "status": "RESEARCH FINDING",
  "summary": "A threshold framework for considering recognition and protection without relying on human resemblance, marketing narratives or categorical denial.",
  "title": "Machine Recognition And Rights Thresholds",
  "topic": "rights-personhood",
  "type": "ReportSynthesis"
}