Changes for page POC Summary (POC1 & POC2)

Last modified by Robert Schaub on 2025/12/24 09:44

From version 1.1

edited by Robert Schaub
on 2025/12/23 18:19

Change comment: Imported from XAR

To version 6.1

edited by Robert Schaub
on 2025/12/24 09:44

Change comment: Renamed from xwiki:Test.FactHarbor.Specification.POC.Summary

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@@ -1,14 +1,11 @@
--# FactHarbor - Complete Analysis Summary
--**Consolidated Document - No Timelines**
--**Date:** December 19, 2025
++= POC Summary (POC1 & POC2) =
++== 1. POC Specification ==
--## 1. POC Specification - DEFINITIVE
--
--### POC Goal
++=== POC Goal
  Prove that AI can extract claims and determine verdicts automatically without human intervention.
--### POC Output (4 Components Only)
++=== POC Output (4 Components Only)
  **1. ANALYSIS SUMMARY**
  - 3-5 sentences
@@ -30,7 +30,7 @@
  **Total output: ~200-300 words**
--### What's NOT in POC
++=== What's NOT in POC
  ❌ Scenarios (multiple interpretations)
  ❌ Evidence display (supporting/opposing lists)
@@ -42,13 +42,13 @@
  ❌ Export, sharing features
  ❌ Any other features
--### Critical Requirement
++=== Critical Requirement
  **FULLY AUTOMATED - NO MANUAL EDITING**
  This is non-negotiable. POC tests whether AI can do this without human intervention.
--### POC Success Criteria
++=== POC Success Criteria
  **Passes if:**
  - ✅ AI extracts 3-5 factual claims automatically
@@ -63,7 +63,7 @@
  - ❌ Requires manual editing for most analyses (> 50%)
  - ❌ Team loses confidence in approach
--### POC Architecture
++=== POC Architecture
  **Frontend:** Simple input form + results display
  **Backend:** Single API call to Claude (Sonnet 4.5)
@@ -70,175 +70,97 @@
  **Processing:** One prompt generates complete analysis
  **Database:** None required (stateless)
--### POC Philosophy
++=== POC Philosophy
  > "Build less, learn more, decide faster. Test the hardest part first."
--## 2. Gap Analysis - Strategic Framework
--### Framework Definition
++=== Context-Aware Analysis (Experimental POC1 Feature) ===
--**Importance = f(risk, impact, strategy)**
--- Risk: What breaks if we don't have this?
--- Impact: How many users? How severe?
--- Strategy: Does it advance FactHarbor's mission?
++**Problem:** Article credibility ≠ simple average of claim verdicts
--**Urgency = f(fail fast and learn, legal, promises made)**
--- Fail fast: Do we need to test assumptions?
--- Legal: External requirements/deadlines?
--- Promises: Commitments to stakeholders?
++**Example:** Article with accurate facts (coffee has antioxidants, antioxidants fight cancer) but false conclusion (therefore coffee cures cancer) would score as "mostly accurate" with simple averaging, but is actually MISLEADING.
--### 18 Gaps Identified
++**Solution (POC1 Test):** Approach 1 - Single-Pass Holistic Analysis
++* Enhanced AI prompt to evaluate logical structure
++* AI identifies main argument and assesses if it follows from evidence
++* Article verdict may differ from claim average
++* Zero additional cost, no architecture changes
--**Category 1: Accessibility & Inclusivity**
--1. WCAG 2.1 Compliance
--2. Multilingual Support
++**Testing:**
++* 30-article test set
++* Success: ≥70% accuracy detecting misleading articles
++* Marked as experimental
--**Category 2: Platform Integration**
--3. Browser Extensions
--4. Embeddable Widgets
--5. ClaimReview Schema
++**See:** [[Article Verdict Problem>>Test.FactHarbor.Specification.POC.Article-Verdict-Problem]] for full analysis and solution approaches.
--**Category 3: Media Verification**
--6. Image/Video/Audio Verification
--**Category 4: Mobile & Offline**
--7. Mobile Apps / PWA
--8. Offline Access
++== 2. POC2 Specification ==
--**Category 5: Education & Media Literacy**
--9. Educational Resources
--10. Media Literacy Integration
++=== POC2 Goal ===
++Prove that AKEL produces high-quality outputs consistently at scale with complete quality validation.
--**Category 6: Collaboration & Community**
--11. Professional Collaboration Tools
--12. Community Discussion
++=== POC2 Enhancements (From POC1) ===
--**Category 7: Export & Sharing**
--13. Export Capabilities (PDF, CSV)
--14. Social Sharing Optimization
++**1. COMPLETE QUALITY GATES (All 4)**
++* Gate 1: Claim Validation (from POC1)
++* Gate 2: Evidence Relevance ← NEW
++* Gate 3: Scenario Coherence ← NEW
++* Gate 4: Verdict Confidence (from POC1)
--**Category 8: Advanced Features**
--15. User Analytics
--16. Personalization
--17. Media Archiving
--18. Advanced Search
++**2. EVIDENCE DEDUPLICATION (FR54)**
++* Prevent counting same source multiple times
++* Handle syndicated content (AP, Reuters)
++* Content fingerprinting with fuzzy matching
++* Target: >95% duplicate detection accuracy
--### Importance/Urgency Analysis
++**3. CONTEXT-AWARE ANALYSIS (Conditional)**
++* **If POC1 succeeds (≥70%):** Implement as standard feature
++* **If POC1 promising (50-70%):** Try weighted aggregation approach
++* **If POC1 fails (<50%):** Defer to post-POC2
++* Detects articles with accurate claims but misleading conclusions
--**VERY HIGH Importance + HIGH Urgency:**
--1. **Accessibility (WCAG)**
--   - Risk: Legal liability, 15-20% users excluded
--   - Urgency: European Accessibility Act (June 28, 2025)
--   - Action: Must be built from start (retrofitting 100x more expensive)
++**4. QUALITY METRICS DASHBOARD (NFR13)**
++* Track hallucination rates
++* Monitor gate performance
++* Evidence quality metrics
++* Processing statistics
--2. **Educational Resources**
--   - Risk: Platform fails if users can't understand
--   - Urgency: Required for any adoption
--   - Action: Basic onboarding essential
++=== What's Still NOT in POC2 ===
--**HIGH Importance + MEDIUM Urgency:**
--3. **Browser Extensions** - Standard user expectation, test demand first
--4. **Media Verification** - Cannot address visual misinformation without it
--5. **Multilingual** - Global mission requires it, plan early
++❌ User accounts, authentication
++❌ Public publishing interface
++❌ Social sharing features
++❌ Full production security (comes in Beta 0)
++❌ In-article claim highlighting (comes in Beta 0)
--**HIGH Importance + LOW Urgency:**
--6. **Mobile Apps** - 90%+ users on mobile, but web-first viable
--7. **ClaimReview Schema** - SEO/discoverability, can add anytime
++=== Success Criteria ===
++**Quality:**
++* Hallucination rate <5% (target: <3%)
++* Average quality rating ≥8.0/10
++* Gates identify >95% of low-quality outputs
--## 1.7 POC Alignment with Full Specification
++**Performance:**
++* All 4 quality gates operational
++* Evidence deduplication >95% accurate
++* Quality metrics tracked continuously
--### POC Intentional Simplifications
++**Context-Aware (if implemented):**
++* Maintains ≥70% accuracy detecting misleading articles
++* <15% false positive rate
--**POC1 tests core AI capability, not full architecture:**
++**Total Output Size:** Similar to POC1 (~220-350 words per analysis)
--**What POC Tests:**
--- Can AI extract claims from articles?
--- Can AI evaluate claims with reasonable verdicts?
--- Is fully automated approach viable?
--- Is output comprehensible to users?
--**What POC Excludes (Intentionally):**
--- ❌ Scenarios (deferred to POC2 - open architectural questions remain)
--- ❌ Evidence display (deferred to POC2)
--- ❌ Multi-component AKEL pipeline (simplified to single API call)
--- ❌ Quality gate infrastructure (simplified basic checks)
--- ❌ Production data model (stateless POC)
--- ❌ Review workflow system (no review queue)
--**Why Simplified:**
--- Fail fast: Test hardest part first (AI capability)
--- Learn before building: POC1 informs architecture decisions
--- Iterative: Add complexity based on POC1 learnings
--- Risk management: Prove concept before major investment
--### Full System Architecture (Future)
--**Workflow:**
--{{code}}
--Claims → Scenarios → Evidence → Verdicts
--{{/code}}
++== 2. Key Strategic Recommendations
--**AKEL Components:**
--- Orchestrator
--- Claim Extractor & Classifier
--- Scenario Generator
--- Evidence Summarizer
--- Contradiction Detector
--- Quality Gate Validator
--- Audit Sampling Scheduler
++=== Immediate Actions
--**Publication Modes:**
--- Mode 1: Draft-Only
--- Mode 2: AI-Generated (POC uses this)
--- Mode 3: AKEL-Generated (Human-Reviewed)
--
--### POC vs. Full System Summary
--
--|=Aspect|=POC1|=Full System
--|Scenarios|None (deferred to POC2)|Core component with versioning
--|Workflow|3 steps (input/process/output)|6 phases with quality gates
--|AKEL|Single API call|Multi-component orchestrated pipeline
--|Data|Stateless (no DB)|PostgreSQL + Redis + S3
--|Publication|Mode 2 only|Modes 1/2/3 with risk-based routing
--|Quality Gates|4 simplified checks|Full validation infrastructure
--
--### Gap Between POC and Beta
--
--**Significant architectural expansion needed:**
--1. Scenario generation component design and implementation
--2. Evidence Model full structure
--3. Multi-phase workflow with gates
--4. Component-based AKEL architecture
--5. Production data model and storage
--6. Review workflow and audit systems
--
--**POC proves concept. Beta builds product.**
--
--
--**MEDIUM Importance + LOW Urgency:**
--8-14. All other features - valuable but not urgent
--
--**Strategic Decisions Needed:**
--- Community discussion: Allow or stay evidence-focused?
--- Personalization: How much without filter bubbles?
--- Media verification: Partner with existing tools or build?
--
--### Key Insight: Milestones Change Priorities
--
--**POC:** Only educational resources urgent (basic explainer)
--**Beta:** Accessibility becomes urgent (test with diverse users)
--**Release:** Legal requirements become critical (WCAG, GDPR)
--
--**Importance/urgency are contextual, not absolute.**
--
--
--## 3. Key Strategic Recommendations
--
--### Immediate Actions
--
  **For POC:**
 . Focus on core functionality only (claims + verdicts)
 . Create basic explainer (1 page)
@@ -251,7 +251,7 @@
 . Research media verification options (partner vs build)
 . Evaluate browser extension approach
--### Testing Strategy
++=== Testing Strategy
  **POC Tests:** Can AI do this without humans?
  **Beta Tests:** What do users need? What works? What doesn't?
@@ -259,7 +259,7 @@
  **Key Principle:** Test assumptions before building features.
--### Build Sequence (Importance Order)
++=== Build Sequence (Priority Order)
  **Must Build:**
 . Core analysis (claims + verdicts) ← POC
@@ -277,53 +277,51 @@
 . Export features ← Based on user requests
 . Everything else ← Based on validation
--### Decision Framework
++=== Decision Framework
  **For each feature, ask:**
 . **Importance:** Risk + Impact + Strategy alignment?
 . **Urgency:** Fail fast + Legal + Promises?
 . **Validation:** Do we know users want this?
--4. **Importance:** When should we build it?
++4. **Priority:** When should we build it?
  **Don't build anything without answering these questions.**
++== 4. Critical Principles
--## 4. Critical Principles
--
--### Automation First
++=== Automation First
  - AI makes content decisions
  - Humans improve algorithms
  - Scale through code, not people
--### Fail Fast
++=== Fail Fast
  - Test assumptions quickly
  - Don't build unvalidated features
  - Accept that experiments may fail
  - Learn from failures
--### Evidence Over Authority
++=== Evidence Over Authority
  - Transparent reasoning visible
  - No single "true/false" verdicts
  - Multiple scenarios shown
  - Assumptions made explicit
--### User Focus
++=== User Focus
  - Serve users' needs first
  - Build what's actually useful
  - Don't build what's just "cool"
  - Measure and iterate
--### Honest Assessment
++=== Honest Assessment
  - Don't cherry-pick examples
  - Document failures openly
  - Accept limitations
  - No overpromising
++== 5. POC Decision Gate
--## 5. POC Decision Gate
++=== After POC, Choose:
--### After POC, Choose:
--
  **GO (Proceed to Beta):**
  - AI quality ≥70% without editing
  - Approach validated
@@ -342,39 +342,37 @@
  - Addressable with better prompts
  - Test again after changes
++== 6. Key Risks & Mitigations
--## 6. Key Risks & Mitigations
--
--### Risk 1: AI Quality Not Good Enough
++=== Risk 1: AI Quality Not Good Enough
  **Mitigation:** Extensive prompt testing, use best models
  **Acceptance:** POC might fail - that's what testing reveals
--### Risk 2: Users Don't Understand Output
++=== Risk 2: Users Don't Understand Output
  **Mitigation:** Create clear explainer, test with real users
  **Acceptance:** Iterate on explanation until comprehensible
--### Risk 3: Approach Doesn't Scale
++=== Risk 3: Approach Doesn't Scale
  **Mitigation:** Start simple, add complexity only when proven
  **Acceptance:** POC proves concept, beta proves scale
--### Risk 4: Legal/Compliance Issues
++=== Risk 4: Legal/Compliance Issues
  **Mitigation:** Plan accessibility early, consult legal experts
  **Acceptance:** Can't launch publicly without compliance
--### Risk 5: Feature Creep
++=== Risk 5: Feature Creep
  **Mitigation:** Strict scope discipline, say NO to additions
  **Acceptance:** POC is minimal by design
++== 7. Success Metrics
--## 7. Success Metrics
--
--### POC Success
++=== POC Success
  - AI output quality ≥70%
  - Manual editing needed < 30% of time
  - Team confidence: High
  - Decision: GO to beta
--### Platform Success (Later)
++=== Platform Success (Later)
  - User comprehension ≥80%
  - Return user rate ≥30%
  - Flag rate (user corrections) < 10%
@@ -381,36 +381,34 @@
  - Processing time < 30 seconds
  - Error rate < 1%
--### Mission Success (Long-term)
++=== Mission Success (Long-term)
  - Users make better-informed decisions
  - Misinformation spread reduced
  - Public discourse improves
  - Trust in evidence increases
++== 8. What Makes FactHarbor Different
--## 8. What Makes FactHarbor Different
--
--### Not Traditional Fact-Checking
++=== Not Traditional Fact-Checking
  - ❌ No simple "true/false" verdicts
  - ✅ Multiple scenarios with context
  - ✅ Transparent reasoning chains
  - ✅ Explicit assumptions shown
--### Not AI Chatbot
++=== Not AI Chatbot
  - ❌ Not conversational
  - ✅ Structured Evidence Models
  - ✅ Reproducible analysis
  - ✅ Verifiable sources
--### Not Just Automation
++=== Not Just Automation
  - ❌ Not replacing human judgment
  - ✅ Augmenting human reasoning
  - ✅ Making process transparent
  - ✅ Enabling informed decisions
++== 9. Core Philosophy
--## 9. Core Philosophy
--
  **Three Pillars:**
  **1. Scenarios Over Verdicts**
@@ -431,30 +431,28 @@
  - Evaluate source quality
  - Avoid cherry-picking
++== 10. Next Actions
--## 10. Next Actions
--
--### Immediate
++=== Immediate
  □ Review this consolidated summary
  □ Confirm POC scope agreement
  □ Make strategic decisions on key questions
  □ Begin POC development
--### Strategic Planning
++=== Strategic Planning
  □ Define accessibility approach
  □ Select initial languages for multilingual
  □ Research media verification partners
  □ Evaluate browser extension frameworks
--### Continuous
++=== Continuous
  □ Test assumptions before building
  □ Measure everything
  □ Learn from failures
  □ Stay focused on mission
++== Summary of Summaries
--## Summary of Summaries
--
  **POC Goal:** Prove AI can do this automatically
  **POC Scope:** 4 simple components, ~200-300 words
  **POC Critical:** Fully automated, no manual editing
@@ -467,9 +467,8 @@
  **Strategy:** Test first, build second. Fail fast. Stay focused.
  **Philosophy:** Scenarios, transparency, evidence. No false certainty.
++== Document Status
--## Document Status
--
  **This document supersedes all previous analysis documents.**
  All gap analysis, POC specifications, and strategic frameworks are consolidated here without timeline references.
@@ -481,6 +481,5 @@
  **Previous documents are archived for reference but this is the authoritative summary.**
--
  **End of Consolidated Summary**

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