Wiki source code of POC Summary (POC1 & POC2)
Last modified by Robert Schaub on 2025/12/24 09:44
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| author | version | line-number | content |
|---|---|---|---|
| 1 | = POC Summary (POC1 & POC2) = | ||
| 2 | |||
| 3 | == 1. POC Specification == | ||
| 4 | |||
| 5 | === POC Goal | ||
| 6 | Prove that AI can extract claims and determine verdicts automatically without human intervention. | ||
| 7 | |||
| 8 | === POC Output (4 Components Only) | ||
| 9 | |||
| 10 | **1. ANALYSIS SUMMARY** | ||
| 11 | - 3-5 sentences | ||
| 12 | - How many claims found | ||
| 13 | - Distribution of verdicts | ||
| 14 | - Overall assessment | ||
| 15 | |||
| 16 | **2. CLAIMS IDENTIFICATION** | ||
| 17 | - 3-5 numbered factual claims | ||
| 18 | - Extracted automatically by AI | ||
| 19 | |||
| 20 | **3. CLAIMS VERDICTS** | ||
| 21 | - Per claim: Verdict label + Confidence % + Brief reasoning (1-3 sentences) | ||
| 22 | - Verdict labels: WELL-SUPPORTED / PARTIALLY SUPPORTED / UNCERTAIN / REFUTED | ||
| 23 | |||
| 24 | **4. ARTICLE SUMMARY (optional)** | ||
| 25 | - 3-5 sentences | ||
| 26 | - Neutral summary of article content | ||
| 27 | |||
| 28 | **Total output: ~200-300 words** | ||
| 29 | |||
| 30 | === What's NOT in POC | ||
| 31 | |||
| 32 | ❌ Scenarios (multiple interpretations) | ||
| 33 | ❌ Evidence display (supporting/opposing lists) | ||
| 34 | ❌ Source links | ||
| 35 | ❌ Detailed reasoning chains | ||
| 36 | ❌ User accounts, history, search | ||
| 37 | ❌ Browser extensions, API | ||
| 38 | ❌ Accessibility, multilingual, mobile | ||
| 39 | ❌ Export, sharing features | ||
| 40 | ❌ Any other features | ||
| 41 | |||
| 42 | === Critical Requirement | ||
| 43 | |||
| 44 | **FULLY AUTOMATED - NO MANUAL EDITING** | ||
| 45 | |||
| 46 | This is non-negotiable. POC tests whether AI can do this without human intervention. | ||
| 47 | |||
| 48 | === POC Success Criteria | ||
| 49 | |||
| 50 | **Passes if:** | ||
| 51 | - ✅ AI extracts 3-5 factual claims automatically | ||
| 52 | - ✅ AI provides reasonable verdicts (≥70% make sense) | ||
| 53 | - ✅ Output is comprehensible | ||
| 54 | - ✅ Team agrees approach has merit | ||
| 55 | - ✅ Minimal or no manual editing needed | ||
| 56 | |||
| 57 | **Fails if:** | ||
| 58 | - ❌ Claim extraction poor (< 60% accuracy) | ||
| 59 | - ❌ Verdicts nonsensical (< 60% reasonable) | ||
| 60 | - ❌ Requires manual editing for most analyses (> 50%) | ||
| 61 | - ❌ Team loses confidence in approach | ||
| 62 | |||
| 63 | === POC Architecture | ||
| 64 | |||
| 65 | **Frontend:** Simple input form + results display | ||
| 66 | **Backend:** Single API call to Claude (Sonnet 4.5) | ||
| 67 | **Processing:** One prompt generates complete analysis | ||
| 68 | **Database:** None required (stateless) | ||
| 69 | |||
| 70 | === POC Philosophy | ||
| 71 | |||
| 72 | > "Build less, learn more, decide faster. Test the hardest part first." | ||
| 73 | |||
| 74 | |||
| 75 | |||
| 76 | === Context-Aware Analysis (Experimental POC1 Feature) === | ||
| 77 | |||
| 78 | **Problem:** Article credibility ≠ simple average of claim verdicts | ||
| 79 | |||
| 80 | **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. | ||
| 81 | |||
| 82 | **Solution (POC1 Test):** Approach 1 - Single-Pass Holistic Analysis | ||
| 83 | * Enhanced AI prompt to evaluate logical structure | ||
| 84 | * AI identifies main argument and assesses if it follows from evidence | ||
| 85 | * Article verdict may differ from claim average | ||
| 86 | * Zero additional cost, no architecture changes | ||
| 87 | |||
| 88 | **Testing:** | ||
| 89 | * 30-article test set | ||
| 90 | * Success: ≥70% accuracy detecting misleading articles | ||
| 91 | * Marked as experimental | ||
| 92 | |||
| 93 | **See:** [[Article Verdict Problem>>Test.FactHarbor.Specification.POC.Article-Verdict-Problem]] for full analysis and solution approaches. | ||
| 94 | |||
| 95 | |||
| 96 | == 2. POC2 Specification == | ||
| 97 | |||
| 98 | === POC2 Goal === | ||
| 99 | Prove that AKEL produces high-quality outputs consistently at scale with complete quality validation. | ||
| 100 | |||
| 101 | === POC2 Enhancements (From POC1) === | ||
| 102 | |||
| 103 | **1. COMPLETE QUALITY GATES (All 4)** | ||
| 104 | * Gate 1: Claim Validation (from POC1) | ||
| 105 | * Gate 2: Evidence Relevance ← NEW | ||
| 106 | * Gate 3: Scenario Coherence ← NEW | ||
| 107 | * Gate 4: Verdict Confidence (from POC1) | ||
| 108 | |||
| 109 | **2. EVIDENCE DEDUPLICATION (FR54)** | ||
| 110 | * Prevent counting same source multiple times | ||
| 111 | * Handle syndicated content (AP, Reuters) | ||
| 112 | * Content fingerprinting with fuzzy matching | ||
| 113 | * Target: >95% duplicate detection accuracy | ||
| 114 | |||
| 115 | **3. CONTEXT-AWARE ANALYSIS (Conditional)** | ||
| 116 | * **If POC1 succeeds (≥70%):** Implement as standard feature | ||
| 117 | * **If POC1 promising (50-70%):** Try weighted aggregation approach | ||
| 118 | * **If POC1 fails (<50%):** Defer to post-POC2 | ||
| 119 | * Detects articles with accurate claims but misleading conclusions | ||
| 120 | |||
| 121 | **4. QUALITY METRICS DASHBOARD (NFR13)** | ||
| 122 | * Track hallucination rates | ||
| 123 | * Monitor gate performance | ||
| 124 | * Evidence quality metrics | ||
| 125 | * Processing statistics | ||
| 126 | |||
| 127 | === What's Still NOT in POC2 === | ||
| 128 | |||
| 129 | ❌ User accounts, authentication | ||
| 130 | ❌ Public publishing interface | ||
| 131 | ❌ Social sharing features | ||
| 132 | ❌ Full production security (comes in Beta 0) | ||
| 133 | ❌ In-article claim highlighting (comes in Beta 0) | ||
| 134 | |||
| 135 | === Success Criteria === | ||
| 136 | |||
| 137 | **Quality:** | ||
| 138 | * Hallucination rate <5% (target: <3%) | ||
| 139 | * Average quality rating ≥8.0/10 | ||
| 140 | * Gates identify >95% of low-quality outputs | ||
| 141 | |||
| 142 | **Performance:** | ||
| 143 | * All 4 quality gates operational | ||
| 144 | * Evidence deduplication >95% accurate | ||
| 145 | * Quality metrics tracked continuously | ||
| 146 | |||
| 147 | **Context-Aware (if implemented):** | ||
| 148 | * Maintains ≥70% accuracy detecting misleading articles | ||
| 149 | * <15% false positive rate | ||
| 150 | |||
| 151 | **Total Output Size:** Similar to POC1 (~220-350 words per analysis) | ||
| 152 | |||
| 153 | |||
| 154 | |||
| 155 | |||
| 156 | |||
| 157 | == 2. Key Strategic Recommendations | ||
| 158 | |||
| 159 | === Immediate Actions | ||
| 160 | |||
| 161 | **For POC:** | ||
| 162 | 1. Focus on core functionality only (claims + verdicts) | ||
| 163 | 2. Create basic explainer (1 page) | ||
| 164 | 3. Test AI quality without manual editing | ||
| 165 | 4. Make GO/NO-GO decision | ||
| 166 | |||
| 167 | **Planning:** | ||
| 168 | 1. Define accessibility strategy (when to build) | ||
| 169 | 2. Decide on multilingual priorities (which languages first) | ||
| 170 | 3. Research media verification options (partner vs build) | ||
| 171 | 4. Evaluate browser extension approach | ||
| 172 | |||
| 173 | === Testing Strategy | ||
| 174 | |||
| 175 | **POC Tests:** Can AI do this without humans? | ||
| 176 | **Beta Tests:** What do users need? What works? What doesn't? | ||
| 177 | **Release Tests:** Is it production-ready? | ||
| 178 | |||
| 179 | **Key Principle:** Test assumptions before building features. | ||
| 180 | |||
| 181 | === Build Sequence (Priority Order) | ||
| 182 | |||
| 183 | **Must Build:** | ||
| 184 | 1. Core analysis (claims + verdicts) ← POC | ||
| 185 | 2. Educational resources (basic → comprehensive) | ||
| 186 | 3. Accessibility (WCAG 2.1 AA) ← Legal requirement | ||
| 187 | |||
| 188 | **Should Build (Validate First):** | ||
| 189 | 4. Browser extensions ← Test demand | ||
| 190 | 5. Media verification ← Pilot with existing tools | ||
| 191 | 6. Multilingual ← Start with 2-3 languages | ||
| 192 | |||
| 193 | **Can Build Later:** | ||
| 194 | 7. Mobile apps ← PWA first | ||
| 195 | 8. ClaimReview schema ← After content library | ||
| 196 | 9. Export features ← Based on user requests | ||
| 197 | 10. Everything else ← Based on validation | ||
| 198 | |||
| 199 | === Decision Framework | ||
| 200 | |||
| 201 | **For each feature, ask:** | ||
| 202 | 1. **Importance:** Risk + Impact + Strategy alignment? | ||
| 203 | 2. **Urgency:** Fail fast + Legal + Promises? | ||
| 204 | 3. **Validation:** Do we know users want this? | ||
| 205 | 4. **Priority:** When should we build it? | ||
| 206 | |||
| 207 | **Don't build anything without answering these questions.** | ||
| 208 | |||
| 209 | == 4. Critical Principles | ||
| 210 | |||
| 211 | === Automation First | ||
| 212 | - AI makes content decisions | ||
| 213 | - Humans improve algorithms | ||
| 214 | - Scale through code, not people | ||
| 215 | |||
| 216 | === Fail Fast | ||
| 217 | - Test assumptions quickly | ||
| 218 | - Don't build unvalidated features | ||
| 219 | - Accept that experiments may fail | ||
| 220 | - Learn from failures | ||
| 221 | |||
| 222 | === Evidence Over Authority | ||
| 223 | - Transparent reasoning visible | ||
| 224 | - No single "true/false" verdicts | ||
| 225 | - Multiple scenarios shown | ||
| 226 | - Assumptions made explicit | ||
| 227 | |||
| 228 | === User Focus | ||
| 229 | - Serve users' needs first | ||
| 230 | - Build what's actually useful | ||
| 231 | - Don't build what's just "cool" | ||
| 232 | - Measure and iterate | ||
| 233 | |||
| 234 | === Honest Assessment | ||
| 235 | - Don't cherry-pick examples | ||
| 236 | - Document failures openly | ||
| 237 | - Accept limitations | ||
| 238 | - No overpromising | ||
| 239 | |||
| 240 | == 5. POC Decision Gate | ||
| 241 | |||
| 242 | === After POC, Choose: | ||
| 243 | |||
| 244 | **GO (Proceed to Beta):** | ||
| 245 | - AI quality ≥70% without editing | ||
| 246 | - Approach validated | ||
| 247 | - Team confident | ||
| 248 | - Clear path to improvement | ||
| 249 | |||
| 250 | **NO-GO (Pivot or Stop):** | ||
| 251 | - AI quality < 60% | ||
| 252 | - Requires manual editing for most | ||
| 253 | - Fundamental flaws identified | ||
| 254 | - Not feasible with current technology | ||
| 255 | |||
| 256 | **ITERATE (Improve & Retry):** | ||
| 257 | - Concept has merit | ||
| 258 | - Specific improvements identified | ||
| 259 | - Addressable with better prompts | ||
| 260 | - Test again after changes | ||
| 261 | |||
| 262 | == 6. Key Risks & Mitigations | ||
| 263 | |||
| 264 | === Risk 1: AI Quality Not Good Enough | ||
| 265 | **Mitigation:** Extensive prompt testing, use best models | ||
| 266 | **Acceptance:** POC might fail - that's what testing reveals | ||
| 267 | |||
| 268 | === Risk 2: Users Don't Understand Output | ||
| 269 | **Mitigation:** Create clear explainer, test with real users | ||
| 270 | **Acceptance:** Iterate on explanation until comprehensible | ||
| 271 | |||
| 272 | === Risk 3: Approach Doesn't Scale | ||
| 273 | **Mitigation:** Start simple, add complexity only when proven | ||
| 274 | **Acceptance:** POC proves concept, beta proves scale | ||
| 275 | |||
| 276 | === Risk 4: Legal/Compliance Issues | ||
| 277 | **Mitigation:** Plan accessibility early, consult legal experts | ||
| 278 | **Acceptance:** Can't launch publicly without compliance | ||
| 279 | |||
| 280 | === Risk 5: Feature Creep | ||
| 281 | **Mitigation:** Strict scope discipline, say NO to additions | ||
| 282 | **Acceptance:** POC is minimal by design | ||
| 283 | |||
| 284 | == 7. Success Metrics | ||
| 285 | |||
| 286 | === POC Success | ||
| 287 | - AI output quality ≥70% | ||
| 288 | - Manual editing needed < 30% of time | ||
| 289 | - Team confidence: High | ||
| 290 | - Decision: GO to beta | ||
| 291 | |||
| 292 | === Platform Success (Later) | ||
| 293 | - User comprehension ≥80% | ||
| 294 | - Return user rate ≥30% | ||
| 295 | - Flag rate (user corrections) < 10% | ||
| 296 | - Processing time < 30 seconds | ||
| 297 | - Error rate < 1% | ||
| 298 | |||
| 299 | === Mission Success (Long-term) | ||
| 300 | - Users make better-informed decisions | ||
| 301 | - Misinformation spread reduced | ||
| 302 | - Public discourse improves | ||
| 303 | - Trust in evidence increases | ||
| 304 | |||
| 305 | == 8. What Makes FactHarbor Different | ||
| 306 | |||
| 307 | === Not Traditional Fact-Checking | ||
| 308 | - ❌ No simple "true/false" verdicts | ||
| 309 | - ✅ Multiple scenarios with context | ||
| 310 | - ✅ Transparent reasoning chains | ||
| 311 | - ✅ Explicit assumptions shown | ||
| 312 | |||
| 313 | === Not AI Chatbot | ||
| 314 | - ❌ Not conversational | ||
| 315 | - ✅ Structured Evidence Models | ||
| 316 | - ✅ Reproducible analysis | ||
| 317 | - ✅ Verifiable sources | ||
| 318 | |||
| 319 | === Not Just Automation | ||
| 320 | - ❌ Not replacing human judgment | ||
| 321 | - ✅ Augmenting human reasoning | ||
| 322 | - ✅ Making process transparent | ||
| 323 | - ✅ Enabling informed decisions | ||
| 324 | |||
| 325 | == 9. Core Philosophy | ||
| 326 | |||
| 327 | **Three Pillars:** | ||
| 328 | |||
| 329 | **1. Scenarios Over Verdicts** | ||
| 330 | - Show multiple interpretations | ||
| 331 | - Make context explicit | ||
| 332 | - Acknowledge uncertainty | ||
| 333 | - Avoid false certainty | ||
| 334 | |||
| 335 | **2. Transparency Over Authority** | ||
| 336 | - Show reasoning, not just conclusions | ||
| 337 | - Make assumptions explicit | ||
| 338 | - Link to evidence | ||
| 339 | - Enable verification | ||
| 340 | |||
| 341 | **3. Evidence Over Opinions** | ||
| 342 | - Ground claims in sources | ||
| 343 | - Show supporting AND opposing evidence | ||
| 344 | - Evaluate source quality | ||
| 345 | - Avoid cherry-picking | ||
| 346 | |||
| 347 | == 10. Next Actions | ||
| 348 | |||
| 349 | === Immediate | ||
| 350 | □ Review this consolidated summary | ||
| 351 | □ Confirm POC scope agreement | ||
| 352 | □ Make strategic decisions on key questions | ||
| 353 | □ Begin POC development | ||
| 354 | |||
| 355 | === Strategic Planning | ||
| 356 | □ Define accessibility approach | ||
| 357 | □ Select initial languages for multilingual | ||
| 358 | □ Research media verification partners | ||
| 359 | □ Evaluate browser extension frameworks | ||
| 360 | |||
| 361 | === Continuous | ||
| 362 | □ Test assumptions before building | ||
| 363 | □ Measure everything | ||
| 364 | □ Learn from failures | ||
| 365 | □ Stay focused on mission | ||
| 366 | |||
| 367 | == Summary of Summaries | ||
| 368 | |||
| 369 | **POC Goal:** Prove AI can do this automatically | ||
| 370 | **POC Scope:** 4 simple components, ~200-300 words | ||
| 371 | **POC Critical:** Fully automated, no manual editing | ||
| 372 | **POC Success:** ≥70% quality without human correction | ||
| 373 | |||
| 374 | **Gap Analysis:** 18 gaps identified, 2 critical (Accessibility + Education) | ||
| 375 | **Framework:** Importance (risk + impact + strategy) + Urgency (fail fast + legal + promises) | ||
| 376 | **Key Insight:** Context matters - urgency changes with milestones | ||
| 377 | |||
| 378 | **Strategy:** Test first, build second. Fail fast. Stay focused. | ||
| 379 | **Philosophy:** Scenarios, transparency, evidence. No false certainty. | ||
| 380 | |||
| 381 | == Document Status | ||
| 382 | |||
| 383 | **This document supersedes all previous analysis documents.** | ||
| 384 | |||
| 385 | All gap analysis, POC specifications, and strategic frameworks are consolidated here without timeline references. | ||
| 386 | |||
| 387 | **For detailed specifications, refer to:** | ||
| 388 | - User Needs document (in project knowledge) | ||
| 389 | - Requirements document (in project knowledge) | ||
| 390 | - This summary (comprehensive overview) | ||
| 391 | |||
| 392 | **Previous documents are archived for reference but this is the authoritative summary.** | ||
| 393 | |||
| 394 | **End of Consolidated Summary** |