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1 = Mission & Purpose =
2
3 == Mission ==
4
5 **FactHarbor brings clarity and transparency to a world full of unclear, controversial, and misleading information by shedding light on the context, assumptions, and evidence behind claims — empowering people to better understand and judge wisely.**
6
7 == Purpose ==
8
9 Modern society faces a deep informational crisis:
10
11 * Misinformation spreads faster than corrections
12 * High-quality evidence is buried under noise
13 * Interpretations change depending on context — but this is rarely made explicit
14 * Users lack tools to understand *why* information conflicts
15 * Claims are evaluated without clearly defined assumptions
16 * The concept of "truth" is increasingly politicized and weaponized
17 * AI accelerates both clarity and manipulation
18
19 FactHarbor exists to bring structure and transparency into this chaos.
20
21 It provides:
22
23 * A structured way to interpret claims
24 * Multiple valid scenarios when a claim is ambiguous
25 * Transparent assumptions, definitions, and boundaries
26 * Complete evidence provenance
27 * Likelihood-based verdicts rather than binary labels
28 * Explanations for why interpretations differ
29 * Neutral tools that reduce manipulation and bias
30
31 The platform is built to:
32
33 * Reveal nuance
34 * Expose misleading interpretations
35 * Eliminate ambiguity
36 * Help users understand how conclusions differ across valid contexts
37 * Support well-grounded, independent judgments
38
39 FactHarbor does not declare absolute truths.
40 It clarifies how thinking works, why disagreement arises, and what can be responsibly concluded.
41
42 ----
43
44 == Core Problems FactHarbor Solves ==
45
46 === Problem 1 — Misinformation & Manipulation ===
47
48 Falsehoods and distortions spread rapidly through:
49
50 * Political propaganda
51 * Social media amplification
52 * Coordinated influence networks
53 * AI-generated fake content
54
55 Users need a structured system that resists manipulation and makes reasoning transparent.
56
57 === Problem 2 — Missing Context Behind Claims ===
58
59 Most claims change meaning drastically depending on:
60
61 * Definitions
62 * Assumptions
63 * Boundaries
64 * Interpretation
65
66 FactHarbor reveals and compares these variations.
67
68 === Problem 3 — "Binary Fact Checks" Fail ===
69
70 Most fact-checking simplifies complex claims into:
71
72 * True
73 * Mostly True
74 * False
75
76 This hides legitimate contextual differences.
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78 FactHarbor replaces binary judgment with scenario-based, likelihood-driven evaluation.
79
80 === Problem 4 — Good Evidence Is Hard to Find ===
81
82 High-quality evidence exists — but users often cannot:
83
84 * Locate it
85 * Assess its reliability
86 * Understand how it fits into a scenario
87 * Compare it with competing evidence
88
89 FactHarbor aggregates, assesses, and organizes evidence with full transparency.
90
91 === Problem 5 — Claims Evolve Over Time ===
92
93 Research and understanding change:
94
95 * New studies emerge
96 * Old studies are retracted
97 * Consensus shifts
98
99 FactHarbor provides:
100
101 * Full entity versioning
102 * Verdict timelines
103 * Automatic re-evaluation when inputs change
104
105 === Problem 6 — Users Cannot See Why People Disagree ===
106
107 People often assume others are ignorant or dishonest, when disagreements typically arise from:
108
109 * Different definitions
110 * Different implicit assumptions
111 * Different evidence
112 * Different contexts
113
114 FactHarbor exposes these underlying structures so disagreements become understandable, not divisive.
115
116 ----
117
118 == Core Concepts ==
119
120 === Claim ===
121
122 A user- or AI-submitted statement whose meaning is often ambiguous and requires structured interpretation.
123
124 Key fields include:
125
126 * Text
127 * Type (literal, metaphorical, rhetorical, supernatural, etc.)
128 * Evaluability
129 * Safety classification
130 * Risk tier
131 * Version metadata
132
133 A claim does not receive a single verdict.
134 It branches into scenarios that clarify its meaning.
135
136 === Scenario ===
137
138 A structured interpretation that clarifies what the claim means under a specific set of:
139
140 * Boundaries
141 * Definitions
142 * Assumptions
143 * Contextual conditions
144
145 Multiple scenarios allow claims to be understood fairly and without political or ideological bias.
146
147 === Evidence ===
148
149 Information that supports or contradicts a scenario.
150
151 Evidence includes:
152
153 * Empirical studies
154 * Experimental data
155 * Expert consensus
156 * Historical records
157 * Contextual background
158 * Absence-of-evidence signals
159
160 Evidence evolves through versioning and includes reliability assessment.
161
162 === Verdict ===
163
164 A likelihood estimate for a claim within a specific scenario based on:
165
166 * Evidence quality
167 * Evidence quantity
168 * Strength of assumptions
169 * Methodological reliability
170 * Uncertainty factors
171 * Comparison with competing scenarios
172
173 Each verdict is versioned and includes a historical timeline.
174
175 === Summary View ===
176
177 A user-facing, simplified overview that:
178
179 * Highlights the most common interpretation
180 * Presents alternative scenarios
181 * Explains why interpretations differ
182 * Shows aggregated likelihoods
183 * Communicates uncertainty clearly
184
185 === AI Knowledge Extraction Layer (AKEL) ===
186
187 The AI subsystem that:
188
189 * Interprets claims
190 * Proposes scenario drafts
191 * Retrieves evidence
192 * Classifies and summarizes sources
193 * Drafts verdicts
194 * Detects contradictions
195 * Triggers re-evaluation when inputs change
196
197 AKEL outputs follow risk-based publication model with quality gates and audit oversight.
198
199 === Decentralized Federation Model ===
200
201 FactHarbor supports a decentralized, multi-node architecture:
202
203 * Each node stores its own claims, scenarios, and verdicts
204 * Nodes synchronize via a federation protocol
205 * Evidence may be stored locally or via IPFS
206 * Communities, universities, or organizations can host their own nodes
207 * A global, emergent consensus forms across the network without central authority
208
209 This increases resilience, autonomy, and scalability.
210
211 ----
212
213 == Vision for Impact ==
214
215 FactHarbor aims to:
216
217 * **Reduce polarization** by revealing the legitimate grounds for disagreement
218 * **Combat misinformation** by providing structured, transparent evaluation
219 * **Empower users** to make informed judgments based on evidence
220 * **Support deliberative democracy** by clarifying complex policy questions
221 * **Enable federated knowledge** so no single entity controls the truth
222 * **Resist manipulation** through transparent reasoning and quality oversight
223 * **Evolve with research** by maintaining versioned, updatable knowledge
224
225 ----
226
227 == Related Pages ==
228
229 * [[Functional Requirements>>FactHarbor.Specification.Functional Requirements.WebHome]]
230 * [[Requirements (Roles)>>Archive.FactHarbor V0\.9\.18 copy.Specification.Requirements.WebHome]]
231 * [[AKEL (AI Knowledge Extraction Layer)>>Archive.FactHarbor V0\.9\.18 copy.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]]
232 * [[Governance>>FactHarbor.Organisation.Governance]]