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Wiki source code of Automation

Version 5.1 by Robert Schaub on 2025/12/12 15:41
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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 == POC v1 (Fully Automated "Text to Truth Landscape") ==
13
14 The goal of POC v1 is to validate the automated reasoning capabilities of the data model without human intervention.
15
16 === Workflow ===
17
18 1. **Input**: User pastes a block of raw text.
19 1. **Deep Analysis (Background)**: The system autonomously performs the full pipeline **before** displaying the text:
20 * Extraction & Normalisation
21 * Scenario & Sub-query generation
22 * Evidence retrieval & Verdict computation
23 1. **Visualisation (Extraction & Marking)**: The system displays the text with claims extracted and marked.
24 * **Verdict-Based Coloring**: The extraction highlights (e.g. Orange/Green) are chosen **according to the computed verdict** for each claim.
25 1. **Inspection**: User clicks a highlighted claim to see the **Reasoning Trail**, showing exactly which evidence and sub-queries led to that verdict.
26
27 === Technical Scope ===
28
29 * **Fully Automated**: No human-in-the-loop for this phase.
30 * **Structured Sub-Queries**: Logic is generated by decomposing claims into the FactHarbor data model.
31 * **Latency**: Focus on accuracy of reasoning over real-time speed for v1.
32
33 ----
34
35 = Manual vs Automated Responsibilities =
36
37 == Human-Only Tasks ==
38
39 These require human judgment, ethics, or contextual interpretation:
40
41 * Definition of key terms in claims
42 * Approval or rejection of scenarios
43 * Interpretation of evidence in context
44 * Final verdict approval
45 * Governance decisions and dispute resolution
46 * High-risk domain oversight
47 * Ethical boundary decisions (especially medical, political, psychological)
48
49 == Semi-Automated (AI Draft → Human Review) ==
50
51 AKEL can draft these, but humans must refine/approve:
52
53 * Scenario structures (definitions, assumptions, context)
54 * Evaluation methods
55 * Evidence relevance suggestions
56 * Reliability hints
57 * Verdict reasoning chains
58 * Uncertainty and limitations
59 * Scenario comparison explanations
60 * Suggestions for merging or splitting scenarios
61 * Draft public summaries
62
63 == Fully Automated Structural Tasks ==
64
65 These require no human interpretation:
66
67 * Claim normalization
68 * Duplicate & cluster detection (vector embeddings)
69 * Evidence metadata extraction
70 * Basic reliability heuristics
71 * Contradiction detection
72 * Re-evaluation triggers
73 * Batch layout generation (diagrams, summaries)
74 * Federation integrity checks
75
76 ----
77
78 = Automation Roadmap =
79
80 Automation increases with maturity.
81
82 == POC (Low Automation) ==
83
84 === Automated ===
85 * Claim normalization
86 * Light scenario templates
87 * Evidence metadata extraction
88 * Simple verdict drafts (internal only)
89
90 === Human ===
91 * All scenario definitions
92 * Evidence interpretation
93 * Verdict creation
94 * Governance
95
96 == Beta 0 (Medium Automation) ==
97
98 === Automated ===
99 * Detailed scenario drafts
100 * Evidence reliability scoring
101 * Cross-scenario comparisons
102 * Contradiction detection (local + remote nodes)
103 * Internal Truth Landscape drafts
104
105 === Human ===
106 * Scenario approval
107 * Final verdict validation
108
109 == Release 1.0 (High Automation) ==
110
111 === Automated ===
112 * Full scenario generation (definitions, assumptions, boundaries)
113 * Evidence relevance scoring and ranking
114 * Bayesian verdict scoring across scenario sets
115 * Multi-scenario summary generation
116 * Anomaly detection across nodes
117 * AKEL-assisted federated synchronization
118
119 === Human ===
120 * Final approval of all scenarios and verdicts
121 * Ethical decisions
122 * Oversight and conflict resolution
123
124 ----
125
126 = Automation Levels =
127
128 == Level 0 — Human-Centric (POC) ==
129 AI is purely advisory, nothing auto-published.
130
131 == Level 1 — Assisted (Beta 0) ==
132 AI drafts structures; humans approve each part.
133
134 == Level 2 — Structured (Release 1.0) ==
135 AI produces near-complete drafts; humans refine.
136
137 == Level 3 — Distributed Intelligence (Future) ==
138 Nodes exchange embeddings, contradiction alerts, and scenario templates.
139 Humans still approve everything.
140
141 ----
142
143 = Automation Matrix =
144
145 == Always Human ==
146 * Final verdict approval
147 * Scenario validity
148 * Ethical decisions
149 * Dispute resolution
150
151 == Mostly AI (Human Validation Needed) ==
152 * Claim normalization
153 * Clustering
154 * Evidence metadata
155 * Reliability heuristics
156 * Scenario drafts
157 * Contradiction detection
158
159 == Mixed ==
160 * Definitions of ambiguous terms
161 * Boundary choices
162 * Assumption evaluation
163 * Evidence selection
164 * Verdict reasoning
165
166 ----
167
168 = Diagram References =
169
170 {{include reference="FactHarbor.Specification.Diagrams.Automation Roadmap.WebHome"/}}
171
172 {{include reference="FactHarbor.Specification.Diagrams.Automation Level.WebHome"/}}
173
174 {{include reference="FactHarbor.Specification.Diagrams.Manual vs Automated matrix.WebHome"/}}