Wiki source code of Automation

Last modified by Robert Schaub on 2025/12/24 20:33

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1 = Automation =
2
3 Automation in FactHarbor amplifies human capability while implementing risk-based oversight.
4
5 This chapter defines:
6
7 * Risk-based publication model
8 * Quality gates for AI-generated content
9 * What must remain human-only
10 * What AI (AKEL) can draft and publish
11 * What can be fully automated
12 * How automation evolves through POC → Beta 0 → Release 1.0
13
14 == 1. POC v1 (AI-Generated Publication Demonstration) ==
15
16 The goal of POC v1 is to validate the automated reasoning capabilities and demonstrate AI-generated content publication.
17
18 === 1.1 Workflow ===
19
20 1. **Input**: User pastes a block of raw text.
21 1. **Deep Analysis (Background)**: The system autonomously performs the full pipeline **before** displaying the text:
22
23 * Extraction & Normalisation
24 * Scenario & Sub-query generation
25 * Evidence retrieval with **contradiction search**
26 * Quality gate validation
27 * Verdict computation
28
29 1. **Visualisation (Extraction & Marking)**: The system displays the text with claims extracted and marked.
30
31 * **Verdict-Based Coloring**: The extraction highlights (e.g. Orange/Green) are chosen **according to the computed verdict** for each claim.
32 * **AI-Generated Label**: Clear indication that content is AI-produced
33
34 1. **Inspection**: User clicks a highlighted claim to see the **Reasoning Trail**, showing exactly which evidence and sub-queries led to that verdict.
35
36 === 1.2 Technical Scope ===
37
38 * **AI-Generated Publication**: Content published as Mode 2 (AI-Generated, no prior human review)
39 * **Quality Gates Active**: All automated quality checks enforced
40 * **Contradiction Search Demonstrated**: Shows counter-evidence and reservation detection
41 * **Risk Tier Classification**: POC shows tier assignment (demo purposes)
42 * **No Human Approval Gate**: Demonstrates scalable AI publication
43 * **Structured Sub-Queries**: Logic generated by decomposing claims into the FactHarbor data model
44
45 == 2. Publication Model ==
46
47 FactHarbor implements a risk-based publication model with three modes:
48
49 === 2.1 Mode 1: Draft-Only ===
50
51 * Failed quality gates
52 * High-risk content pending expert review
53 * Internal review queue only
54
55 === 2.2 Mode 2: AI-Generated (Public) ===
56
57 * Passed all quality gates
58 * Risk tier B or C
59 * Clear AI-generated labeling
60 * Users can request human review
61
62 === 2.3 Mode 3: Human-Reviewed ===
63
64 * Validated by human reviewers/experts
65 * "Human-Reviewed" status badge
66 * Required for Tier A content publication
67
68 See [[AKEL page>>Archive.FactHarbor V0\.9\.23 Lost Data.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]] for detailed publication mode descriptions.
69
70
71 == 3. Risk Tiers and Automation Levels ==
72
73 === 3.1 Tier A (High Risk) ===
74
75 * **Domains**: Medical, legal, elections, safety, security
76 * **Automation**: AI can draft, human review required for "Human-Reviewed" status
77 * **AI publication**: Allowed with prominent disclaimers and warnings
78 * **Audit rate**: Recommendation: 30-50%
79
80 === 3.2 Tier B (Medium Risk) ===
81
82 * **Domains**: Complex policy, science, causality claims
83 * **Automation**: AI can draft and publish (Mode 2)
84 * **Human review**: Optional, audit-based
85 * **Audit rate**: Recommendation: 10-20%
86
87 === 3.3 Tier C (Low Risk) ===
88
89 * **Domains**: Definitions, established facts, historical data
90 * **Automation**: AI publication default
91 * **Human review**: On request or via sampling
92 * **Audit rate**: Recommendation: 5-10%
93
94 == 4. Human-Only Tasks ==
95
96 These require human judgment and cannot be automated:
97
98 * **Ethical boundary decisions** (especially medical, political, psychological harm assessment)
99 * **Dispute resolution** between conflicting expert opinions
100 * **Governance policy** setting and enforcement
101 * **Final authority** on Tier A "Human-Reviewed" status
102 * **Audit system oversight** and quality standard definition
103 * **Risk tier policy** adjustments based on societal context
104
105 == 5. AI-Draft with Audit (Semi-Automated) ==
106
107 AKEL drafts these; humans validate via sampling audits:
108
109 * **Scenario structures** (definitions, assumptions, context)
110 * **Evaluation methods** and reasoning chains
111 * **Evidence relevance** assessment and ranking
112 * **Reliability scoring** and source evaluation
113 * **Verdict reasoning** with uncertainty quantification
114 * **Contradiction and reservation** identification
115 * **Scenario comparison** explanations
116 * **Public summaries** and accessibility text
117
118 Most Tier B and C content remains in AI-draft status unless:
119
120 * Users request human review
121 * Audits identify errors
122 * High engagement triggers review
123 * Community flags issues
124
125 == 6. Fully Automated Structural Tasks ==
126
127 These require no human interpretation:
128
129 * **Claim normalization** (canonical form generation)
130 * **Duplicate detection** (vector embeddings, clustering)
131 * **Evidence metadata extraction** (dates, authors, publication info)
132 * **Basic reliability heuristics** (source reputation scoring)
133 * **Contradiction detection** (conflicting statements across sources)
134 * **Re-evaluation triggers** (new evidence, source updates)
135 * **Layout generation** (diagrams, summaries, UI presentation)
136 * **Federation integrity checks** (cross-node data validation)
137
138 == 7. Quality Gates (Automated) ==
139
140 Before AI-draft publication (Mode 2), content must pass:
141
142 1. **Source Quality Gate**
143
144 * Primary sources verified
145 * Citations complete and accessible
146 * Source reliability scored
147
148 2. **Contradiction Search Gate** (MANDATORY)
149
150 * Counter-evidence actively sought
151 * Reservations and limitations identified
152 * Bubble detection (echo chambers, conspiracy theories)
153 * Diverse perspective verification
154
155 3. **Uncertainty Quantification Gate**
156
157 * Confidence scores calculated
158 * Limitations stated
159 * Data gaps disclosed
160
161 4. **Structural Integrity Gate**
162
163 * No hallucinations detected
164 * Logic chain valid
165 * References verifiable
166
167 See [[AKEL page>>Archive.FactHarbor V0\.9\.23 Lost Data.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]] for detailed quality gate specifications.
168
169
170 == 8. Audit System ==
171
172 Instead of reviewing all AI output, systematic sampling audits ensure quality:
173
174 === 8.1 Stratified Sampling ===
175
176 * Risk tier (A > B > C sampling rates)
177 * Confidence scores (low confidence → more audits)
178 * Traffic/engagement (popular content audited more)
179 * Novelty (new topics/claim types prioritized)
180 * User flags and disagreement signals
181
182 === 8.2 Continuous Improvement Loop ===
183
184 Audit findings improve:
185
186 * Query templates
187 * Source reliability weights
188 * Contradiction detection algorithms
189 * Risk tier assignment rules
190 * Bubble detection heuristics
191
192 === 8.3 Transparency ===
193
194 * Audit statistics published
195 * Accuracy rates by tier reported
196 * System improvements documented
197
198 == 9. Automation Roadmap ==
199
200 Automation capabilities increase with system maturity while maintaining quality oversight.
201
202 === 9.1 POC (Current Focus) ===
203
204 **Automated:**
205
206 * Claim normalization
207 * Scenario template generation
208 * Evidence metadata extraction
209 * Simple verdict drafts
210 * **AI-generated publication** (Mode 2, with quality gates)
211 * **Contradiction search**
212 * **Risk tier assignment**
213
214 **Human:**
215
216 * High-risk content validation (Tier A)
217 * Sampling audits across all tiers
218 * Quality standard refinement
219 * Governance decisions
220
221 === 9.2 Beta 0 (Enhanced Automation) ===
222
223 **Automated:**
224
225 * Detailed scenario generation
226 * Advanced evidence reliability scoring
227 * Cross-scenario comparisons
228 * Multi-source contradiction detection
229 * Internal Truth Landscape generation
230 * **Increased AI-draft coverage** (more Tier B content)
231
232 **Human:**
233
234 * Tier A final approval
235 * Audit sampling (continued)
236 * Expert validation of complex domains
237 * Quality improvement oversight
238
239 === 9.3 Release 1.0 (High Automation) ===
240
241 **Automated:**
242
243 * Full scenario generation (comprehensive)
244 * Bayesian verdict scoring across scenarios
245 * Multi-scenario summary generation
246 * Anomaly detection across federated nodes
247 * AKEL-assisted cross-node synchronization
248 * **Most Tier B and all Tier C** auto-published
249
250 **Human:**
251
252 * Tier A oversight (still required)
253 * Strategic audits (lower sampling rates, higher value)
254 * Ethical decisions and policy
255 * Conflict resolution
256
257 == 10. Automation Levels Diagram ==
258
259 {{include reference="Archive.FactHarbor V0\.9\.23 Lost Data.Specification.Diagrams.Automation Level.WebHome"}}
260
261
262 == 11. Automation Roadmap Diagram ==
263
264 {{include reference="Test.FactHarborV09.Specification.Diagrams.Automation Roadmap.WebHome"}}
265
266
267 == 12. Manual vs Automated Matrix ==
268
269 {{include reference="Test.FactHarborV09.Specification.Diagrams.Manual vs Automated matrix.WebHome"}}
270
271
272 == 13. Related Pages ==
273
274 * [[AKEL (AI Knowledge Extraction Layer)>>Test.FactHarborV09.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]]
275 * [[Requirements (Roles)>>Test.FactHarborV09.Specification.Requirements.WebHome]]
276 * [[Workflows>>Test.FactHarborV09.Specification.Workflows.WebHome]]
277 * [[Governance>>Test.FactHarborV09.Organisation.Governance]]
278 {{/include}}
279 {{/include}}
280 {{/include}}