Wiki source code of Automation
Version 2.1 by Robert Schaub on 2025/12/11 21:35
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1.1 | 1 | = Automation = |
| 2 | |||
| 3 | Automation in FactHarbor amplifies human capability but never replaces human oversight. | ||
| 4 | All automated outputs require human review before publication. | ||
| 5 | |||
| 6 | This chapter defines: | ||
| 7 | * What must remain human-only | ||
| 8 | * What AI (AKEL) can draft | ||
| 9 | * What can be fully automated | ||
| 10 | * How automation evolves through POC → Beta 0 → Release 1.0 | ||
| 11 | |||
| 12 | ---- | ||
| 13 | |||
| 14 | = Manual vs Automated Responsibilities = | ||
| 15 | |||
| 16 | == Human-Only Tasks == | ||
| 17 | |||
| 18 | These require human judgment, ethics, or contextual interpretation: | ||
| 19 | |||
| 20 | * Definition of key terms in claims | ||
| 21 | * Approval or rejection of scenarios | ||
| 22 | * Interpretation of evidence in context | ||
| 23 | * Final verdict approval | ||
| 24 | * Governance decisions and dispute resolution | ||
| 25 | * High-risk domain oversight | ||
| 26 | * Ethical boundary decisions (especially medical, political, psychological) | ||
| 27 | |||
| 28 | == Semi-Automated (AI Draft → Human Review) == | ||
| 29 | |||
| 30 | AKEL can draft these, but humans must refine/approve: | ||
| 31 | |||
| 32 | * Scenario structures (definitions, assumptions, context) | ||
| 33 | * Evaluation methods | ||
| 34 | * Evidence relevance suggestions | ||
| 35 | * Reliability hints | ||
| 36 | * Verdict reasoning chains | ||
| 37 | * Uncertainty and limitations | ||
| 38 | * Scenario comparison explanations | ||
| 39 | * Suggestions for merging or splitting scenarios | ||
| 40 | * Draft public summaries | ||
| 41 | |||
| 42 | == Fully Automated Structural Tasks == | ||
| 43 | |||
| 44 | These require no human interpretation: | ||
| 45 | |||
| 46 | * Claim normalization | ||
| 47 | * Duplicate & cluster detection (vector embeddings) | ||
| 48 | * Evidence metadata extraction | ||
| 49 | * Basic reliability heuristics | ||
| 50 | * Contradiction detection | ||
| 51 | * Re-evaluation triggers | ||
| 52 | * Batch layout generation (diagrams, summaries) | ||
| 53 | * Federation integrity checks | ||
| 54 | |||
| 55 | ---- | ||
| 56 | |||
| 57 | = Automation Roadmap = | ||
| 58 | |||
| 59 | Automation increases with maturity. | ||
| 60 | |||
| 61 | == POC (Low Automation) == | ||
| 62 | |||
| 63 | === Automated === | ||
| 64 | * Claim normalization | ||
| 65 | * Light scenario templates | ||
| 66 | * Evidence metadata extraction | ||
| 67 | * Simple verdict drafts (internal only) | ||
| 68 | |||
| 69 | === Human === | ||
| 70 | * All scenario definitions | ||
| 71 | * Evidence interpretation | ||
| 72 | * Verdict creation | ||
| 73 | * Governance | ||
| 74 | |||
| 75 | == Beta 0 (Medium Automation) == | ||
| 76 | |||
| 77 | === Automated === | ||
| 78 | * Detailed scenario drafts | ||
| 79 | * Evidence reliability scoring | ||
| 80 | * Cross-scenario comparisons | ||
| 81 | * Contradiction detection (local + remote nodes) | ||
| 82 | * Internal Truth Landscape drafts | ||
| 83 | |||
| 84 | === Human === | ||
| 85 | * Scenario approval | ||
| 86 | * Final verdict validation | ||
| 87 | |||
| 88 | == Release 1.0 (High Automation) == | ||
| 89 | |||
| 90 | === Automated === | ||
| 91 | * Full scenario generation (definitions, assumptions, boundaries) | ||
| 92 | * Evidence relevance scoring and ranking | ||
| 93 | * Bayesian verdict scoring across scenario sets | ||
| 94 | * Multi-scenario summary generation | ||
| 95 | * Anomaly detection across nodes | ||
| 96 | * AKEL-assisted federated synchronization | ||
| 97 | |||
| 98 | === Human === | ||
| 99 | * Final approval of all scenarios and verdicts | ||
| 100 | * Ethical decisions | ||
| 101 | * Oversight and conflict resolution | ||
| 102 | |||
| 103 | ---- | ||
| 104 | |||
| 105 | = Automation Levels = | ||
| 106 | |||
| 107 | == Level 0 — Human-Centric (POC) == | ||
| 108 | AI is purely advisory, nothing auto-published. | ||
| 109 | |||
| 110 | == Level 1 — Assisted (Beta 0) == | ||
| 111 | AI drafts structures; humans approve each part. | ||
| 112 | |||
| 113 | == Level 2 — Structured (Release 1.0) == | ||
| 114 | AI produces near-complete drafts; humans refine. | ||
| 115 | |||
| 116 | == Level 3 — Distributed Intelligence (Future) == | ||
| 117 | Nodes exchange embeddings, contradiction alerts, and scenario templates. | ||
| 118 | Humans still approve everything. | ||
| 119 | |||
| 120 | ---- | ||
| 121 | |||
| 122 | = Automation Matrix = | ||
| 123 | |||
| 124 | == Always Human == | ||
| 125 | * Final verdict approval | ||
| 126 | * Scenario validity | ||
| 127 | * Ethical decisions | ||
| 128 | * Dispute resolution | ||
| 129 | |||
| 130 | == Mostly AI (Human Validation Needed) == | ||
| 131 | * Claim normalization | ||
| 132 | * Clustering | ||
| 133 | * Evidence metadata | ||
| 134 | * Reliability heuristics | ||
| 135 | * Scenario drafts | ||
| 136 | * Contradiction detection | ||
| 137 | |||
| 138 | == Mixed == | ||
| 139 | * Definitions of ambiguous terms | ||
| 140 | * Boundary choices | ||
| 141 | * Assumption evaluation | ||
| 142 | * Evidence selection | ||
| 143 | * Verdict reasoning | ||
| 144 | |||
| 145 | ---- | ||
| 146 | |||
| 147 | = Diagram References = | ||
| 148 | |||
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2.1 | 149 | {{include reference="FactHarbor.Specification.Diagrams.Automation Roadmap.WebHome"/}} |
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1.1 | 150 | |
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2.1 | 151 | {{include reference="FactHarbor.Specification.Diagrams.Automation Level.WebHome"/}} |
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1.1 | 152 | |
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2.1 | 153 | {{include reference="FactHarbor.Specification.Diagrams.Manual vs Automated matrix.WebHome"/}} |