Changes for page POC Summary (POC1 & POC2)

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

From 6.1 to 5.1

From version 5.1

edited by Robert Schaub
on 2025/12/23 22:59

Change comment: Imported from XAR

To version 1.1

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

Change comment: Imported from XAR

Raw
Rendered

Summary

Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

@@ -1,11 +1,14 @@
--= POC Summary (POC1 & POC2) =
++# FactHarbor - Complete Analysis Summary
++**Consolidated Document - No Timelines**
++**Date:** December 19, 2025
--== 1. POC Specification ==
--=== POC Goal
++## 1. POC Specification - DEFINITIVE
++
++### 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
@@ -27,7 +27,7 @@
  **Total output: ~200-300 words**
--=== What's NOT in POC
++### What's NOT in POC
  ❌ Scenarios (multiple interpretations)
  ❌ Evidence display (supporting/opposing lists)
@@ -39,13 +39,13 @@
  ❌ 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
@@ -60,7 +60,7 @@
  - ❌ 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)
@@ -67,35 +67,175 @@
  **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
--=== Context-Aware Analysis (Experimental POC1 Feature) ===
++### Framework Definition
--**Problem:** Article credibility ≠ simple average of claim verdicts
++**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?
--**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.
++**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?
--**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
++### 18 Gaps Identified
--**Testing:**
--* 30-article test set
--* Success: ≥70% accuracy detecting misleading articles
--* Marked as experimental
++**Category 1: Accessibility & Inclusivity**
++1. WCAG 2.1 Compliance
++2. Multilingual Support
--**See:** [[Article Verdict Problem>>Test.FactHarbor.Specification.POC.Article-Verdict-Problem]] for full analysis and solution approaches.
++**Category 2: Platform Integration**
++3. Browser Extensions
++4. Embeddable Widgets
++5. ClaimReview Schema
--== 2. Key Strategic Recommendations
++**Category 3: Media Verification**
++6. Image/Video/Audio Verification
--=== Immediate Actions
++**Category 4: Mobile & Offline**
++7. Mobile Apps / PWA
++8. Offline Access
++**Category 5: Education & Media Literacy**
++9. Educational Resources
++10. Media Literacy Integration
++
++**Category 6: Collaboration & Community**
++11. Professional Collaboration Tools
++12. Community Discussion
++
++**Category 7: Export & Sharing**
++13. Export Capabilities (PDF, CSV)
++14. Social Sharing Optimization
++
++**Category 8: Advanced Features**
++15. User Analytics
++16. Personalization
++17. Media Archiving
++18. Advanced Search
++
++### Importance/Urgency Analysis
++
++**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)
++
++2. **Educational Resources**
++   - Risk: Platform fails if users can't understand
++   - Urgency: Required for any adoption
++   - Action: Basic onboarding essential
++
++**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
++
++**HIGH Importance + LOW Urgency:**
++6. **Mobile Apps** - 90%+ users on mobile, but web-first viable
++7. **ClaimReview Schema** - SEO/discoverability, can add anytime
++
++
++## 1.7 POC Alignment with Full Specification
++
++### POC Intentional Simplifications
++
++**POC1 tests core AI capability, not full architecture:**
++
++**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}}
++
++**AKEL Components:**
++- Orchestrator
++- Claim Extractor & Classifier
++- Scenario Generator
++- Evidence Summarizer
++- Contradiction Detector
++- Quality Gate Validator
++- Audit Sampling Scheduler
++
++**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)
@@ -108,7 +108,7 @@
 . 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?
@@ -116,7 +116,7 @@
  **Key Principle:** Test assumptions before building features.
--=== Build Sequence (Priority Order)
++### Build Sequence (Importance Order)
  **Must Build:**
 . Core analysis (claims + verdicts) ← POC
@@ -134,51 +134,53 @@
 . 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. **Priority:** When should we build it?
++4. **Importance:** When should we build it?
  **Don't build anything without answering these questions.**
--== 4. Critical Principles
--=== Automation First
++## 4. Critical Principles
++
++### 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
--=== After POC, Choose:
++## 5. POC Decision Gate
++### After POC, Choose:
++
  **GO (Proceed to Beta):**
  - AI quality ≥70% without editing
  - Approach validated
@@ -197,37 +197,39 @@
  - Addressable with better prompts
  - Test again after changes
--== 6. Key Risks & Mitigations
--=== Risk 1: AI Quality Not Good Enough
++## 6. Key Risks & Mitigations
++
++### 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
--=== POC Success
++## 7. Success Metrics
++
++### 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%
@@ -234,34 +234,36 @@
  - 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
--=== Not Traditional Fact-Checking
++## 8. What Makes FactHarbor Different
++
++### 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**
@@ -282,28 +282,30 @@
  - Evaluate source quality
  - Avoid cherry-picking
--== 10. Next Actions
--=== Immediate
++## 10. Next Actions
++
++### 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
@@ -316,8 +316,9 @@
  **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.
@@ -329,5 +329,6 @@
  **Previous documents are archived for reference but this is the authoritative summary.**
++
  **End of Consolidated Summary**

Changes for page POC Summary (POC1 & POC2)

Summary

Details

Applications

Navigation

Need help?