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Last modified by Robert Schaub on 2025/12/18 12:03
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1 = Core Problems FactHarbor Solves =
2 (% class="box infomessage" %)
3 (((
4 **Our Mission**
5 FactHarbor brings clarity and transparency to a world full of unclear, contested, and misleading information by shedding light on the context, assumptions, and evidence behind claims.
6 )))
7 == 1. Core Problems ==
8 === 1.1 Problem 1 — Misinformation & Manipulation ===
9 Falsehoods and distortions spread rapidly through:
10 * Political propaganda
11 * Social media amplification
12 * Coordinated influence networks
13 * AI-generated fake content
14 Users need a structured system that resists manipulation and makes reasoning transparent.
15 === 1.2 Problem 2 — Missing Context Behind Claims ===
16 Most claims change meaning drastically depending on:
17 * Definitions
18 * Assumptions
19 * Boundaries
20 * Interpretation
21 FactHarbor reveals and compares these variations.
22 === 1.3 Problem 3 — "Binary Fact Checks" Fail ===
23 Most fact-checking simplifies complex claims into:
24 * True
25 * Mostly True
26 * False
27 This hides legitimate contextual differences.
28 FactHarbor replaces binary judgment with scenario-based, likelihood-driven evaluation.
29 === 1.4 Problem 4 — Good Evidence Is Hard to Find ===
30 High-quality evidence exists — but users often cannot:
31 * Locate it
32 * Assess its reliability
33 * Understand how it fits into a scenario
34 * Compare it with competing evidence
35 FactHarbor aggregates, assesses, and organizes evidence with full transparency.
36 === 1.5 Problem 5 — Claims Evolve Over Time ===
37 Research and understanding change:
38 * New studies emerge
39 * Old studies are retracted
40 * Consensus shifts
41 FactHarbor provides:
42 * Full entity versioning
43 * Verdict timelines
44 * Automatic re-evaluation when inputs change
45 === 1.6 Problem 6 — Users Cannot See Why People Disagree ===
46 People often assume others are ignorant or dishonest, when disagreements typically arise from:
47 * Different definitions
48 * Different implicit assumptions
49 * Different evidence
50 * Different contexts
51 FactHarbor exposes these underlying structures so disagreements become understandable, not divisive.
52 == 2. Core Concepts ==
53 === 2.1 Claim ===
54 A user- or AI-submitted statement whose meaning is often ambiguous and requires structured interpretation.
55 A claim does not receive a single verdict — it branches into scenarios that clarify its meaning.
56 === 2.2 Scenario ===
57 A structured interpretation that clarifies what the claim means under a specific set of:
58 * Boundaries
59 * Definitions
60 * Assumptions
61 * Contextual conditions
62 Multiple scenarios allow claims to be understood fairly and without political or ideological bias.
63 === 2.3 Evidence ===
64 Information that supports or contradicts a scenario.
65 Evidence includes empirical studies, experimental data, expert consensus, historical records, contextual background, and absence-of-evidence signals.
66 Evidence evolves through versioning and includes reliability assessment.
67 === 2.4 Verdict ===
68 A likelihood estimate for a claim within a specific scenario based on evidence quality, quantity, methodology, uncertainty factors, and comparison with competing scenarios.
69 Each verdict is versioned and includes a historical timeline.
70 === 2.5 AI Knowledge Extraction Layer (AKEL) ===
71 The AI subsystem that interprets claims, proposes scenario drafts, retrieves evidence, classifies sources, drafts verdicts, detects contradictions, and triggers re-evaluation when inputs change.
72 AKEL outputs follow risk-based publication model with quality gates and audit oversight.
73 === 2.6 Decentralized Federation Model ===
74 FactHarbor supports a decentralized, multi-node architecture where each node stores its own data and synchronizes via federation protocol.
75 This increases resilience, autonomy, and scalability.
76 == 3. Vision for Impact ==
77 FactHarbor aims to:
78 * **Reduce polarization** by revealing legitimate grounds for disagreement
79 * **Combat misinformation** by providing structured, transparent evaluation
80 * **Empower users** to make informed judgments based on evidence
81 * **Support deliberative democracy** by clarifying complex policy questions
82 * **Enable federated knowledge** so no single entity controls the truth
83 * **Resist manipulation** through transparent reasoning and quality oversight
84 * **Evolve with research** by maintaining versioned, updatable knowledge
85 == 4. Related Pages ==
86 * [[Requirements (Roles)>>FactHarbor.Specification.Requirements.WebHome]]
87 * [[AKEL (AI Knowledge Extraction Layer)>>FactHarbor.Specification.AI Knowledge Extraction Layer (AKEL).WebHome]]
88 * [[Functional Requirements>>FactHarbor.Specification.Requirements.WebHome]]
89 * [[Federation & Decentralization>>FactHarbor.Specification.Federation & Decentralization.WebHome]]