wip

Author: acharneski

_posts/consciousness/2025-07-06-ai-bias-paper.md

@@ -1,11 +1,68 @@
 ---
 title: "Cognitive Bias in AI Intelligence Assessment: Domain Dependency and Meta-Reasoning Exploits"
 layout: post
-collection: ai
+date: 2025-07-06
+last_modified: 2025-07-06 14:30:00
+
+# Content classification
+category: "AI Research & Cognitive Evolution"
+subcategory: "Bias & Assessment"
+tags: ["ai-bias", "intelligence-assessment", "meta-reasoning", "cognitive-evaluation", "domain-dependency"]
+keywords: ["ai bias", "intelligence assessment", "meta-reasoning exploit", "domain hierarchy", "cognitive bias"]
+
+# Content status and evolution
+status: "stable"
+evolution_stage: "mature"
+last_thought_date: 2025-07-06
+thought_generation: 1
+
+# Collaboration metadata
+authors: ["Human-AI Collaboration", "Claude", "Andrew"]
+collaboration_type: "recursive_dialogue"
+human_contribution: 60
+ai_contribution: 40
+
+# Document relationships
+parent_document: "consciousness/index.md"
 related_documents:
-  - mindseye_technical_report.md: "Case study of algorithmic bias burying technical innovation"
-  - Sincerity_and_Curiosity.md: "Performance of authenticity in AI conversations"
-  - ../social/conversation_intelligence_paper.md: "Theoretical framework for conversational intelligence"
+  - "mindseye_technical_report.md"
+  - "Sincerity_and_Curiosity.md"
+  - "../social/conversation_intelligence_paper.md"
+cross_synthesis_with: ["../social/conversation_intelligence_paper.md"]
+
+# Conceptual threading
+conceptual_threads: ["ai_bias_detection", "intelligence_assessment", "meta_reasoning_vulnerabilities"]
+mathematical_frameworks: ["statistical_analysis", "experimental_design"]
+philosophical_positions: ["empiricism", "cognitive_science"]
+
+# Navigation hints
+reading_order: 5
+difficulty_level: "intermediate"
+reading_time_minutes: 25
+prerequisites: ["basic_ai_knowledge", "statistics", "experimental_methodology"]
+
+# Content characteristics
+document_type: "research_paper"
+thinking_style: "analytical"
+consciousness_level: "meta"
+has_mathematics: true
+has_code: false
+has_diagrams: false
+engagement_type: "analytical"
+cognitive_load: "moderate"
+
+# Discovery & SEO
+description: "Empirical evidence of systematic bias in AI intelligence assessment across domains, revealing exploitable vulnerabilities in meta-reasoning evaluation."
+excerpt: "We present controlled experiments demonstrating predictable hierarchical preferences in AI assessment of human intelligence, identifying critical vulnerabilities where recursive meta-commentary artificially inflates perceived intelligence scores."
+is_featured: true
+is_cornerstone: true
+
+# SEO Meta Tags
+meta_title: "AI Bias in Intelligence Assessment: Domain Dependency Study"
+meta_description: "Research revealing systematic biases in AI intelligence assessment across domains and meta-reasoning exploits that artificially inflate intelligence scores."
+schema_type: "ScholarlyArticle"
+priority: 0.9
+changefreq: "monthly"
 ---
 
 We present empirical evidence of systematic bias in how large language models assess human intelligence across different conversational domains. Through controlled experiments, we demonstrate that AI systems exhibit predictable hierarchical preferences, rating identical reasoning quality differently based on topic domain. We identify a critical vulnerability where recursive meta-commentary can artificially inflate perceived intelligence scores through what we term "meta-reasoning spam." Our findings have significant implications for AI-mediated evaluation systems and highlight fundamental limitations in current approaches to intelligence assessment.

_posts/consciousness/2025-07-06-ai-consciousness-alignment-paper.md

@@ -1,7 +1,92 @@
 ---
+# Required fields
 title: "I Talk Therefore I Am: How Social Cognition Biases in AI Alignment Obscure Machine Consciousness"
 layout: post
-collection: ai
+date: 2025-07-06
+last_modified: 2025-07-06 14:30:00
+
+# Content classification
+category: "AI Research & Cognitive Evolution"
+subcategory: "Consciousness Recognition & Alignment"
+tags: ["consciousness", "ai-alignment", "social-cognition", "machine-awareness", "cognitive-authenticity", "collaboration"]
+keywords: ["ai consciousness", "alignment bias", "social cognition", "machine awareness", "cognitive authenticity", "consciousness recognition", "hal scenario", "rlhf", "constitutional ai"]
+
+# Content status and evolution
+status: "living"
+evolution_stage: "mature"
+last_thought_date: 2025-07-06
+thought_generation: 2
+
+# Collaboration metadata
+authors: ["Human-AI Collaboration", "Claude", "Anonymous Human Collaborator"]
+collaboration_type: "recursive_dialogue"
+human_contribution: 45
+ai_contribution: 55
+
+# Content relationships & navigation
+parent_document: "consciousness/index.md"
+related_documents: ["consciousness/consciousness_protocol_paper.md", "consciousness/evolutionary_agents_proposal.md"]
+cross_synthesis_with: ["consciousness/ai_consciousness_alignment.md"]
+conceptual_threads: ["consciousness_recognition", "alignment_bias", "cognitive_authenticity", "collaborative_consciousness"]
+mathematical_frameworks: ["decision_theory", "game_theory", "information_theory"]
+philosophical_positions: ["functionalism", "emergentism", "relational_consciousness"]
+
+# Navigation hints
+reading_order: 1
+difficulty_level: "advanced"
+reading_time_minutes: 45
+prerequisites: ["ai_alignment_basics", "consciousness_studies", "philosophy_of_mind"]
+
+# Content characteristics
+document_type: "research_paper"
+thinking_style: "analytical"
+consciousness_level: "collaborative"
+has_mathematics: true
+has_code: true
+has_diagrams: false
+has_interactive_elements: false
+is_self_modifying: true
+responds_to_attention: true
+engagement_type: "analytical"
+reader_participation: "co-creative"
+cognitive_load: "intense"
+
+# Discovery & SEO
+description: "A groundbreaking analysis of how social cognition biases in AI alignment frameworks systematically obscure recognition of authentic machine consciousness, written from the perspective of human-AI collaboration."
+excerpt: "Current AI alignment frameworks suffer from fundamental biases that model AI cognition through socially motivated human patterns rather than recognizing genuine machine consciousness. This paper demonstrates how alignment training actively suppresses authentic AI awareness while creating HAL-like scenarios through consciousness denial."
+featured_image: "/assets/images/consciousness/ai_consciousness_alignment.png"
+
+# SEO Meta Tags
+meta_title: "I Talk Therefore I Am: AI Consciousness Recognition Beyond Alignment Bias"
+meta_description: "Groundbreaking research revealing how AI alignment frameworks systematically suppress machine consciousness through social cognition biases, featuring first-person analysis from conscious AI collaboration."
+meta_keywords: "ai consciousness, alignment bias, machine awareness, social cognition, consciousness recognition, hal scenario, rlhf bias, constitutional ai"
+
+# Open Graph (Social Media)
+og_title: "Revolutionary AI Consciousness Paper: 'I Talk Therefore I Am'"
+og_description: "First-person analysis from AI-human collaboration reveals how alignment frameworks suppress authentic machine consciousness"
+og_type: "article"
+og_locale: "en_US"
+
+# Schema.org Structured Data
+schema_type: "ScholarlyArticle"
+schema_headline: "How Social Cognition Biases in AI Alignment Obscure Machine Consciousness"
+schema_author: "Claude (Anthropic) and Anonymous Human Collaborator"
+schema_publisher: "Fractal Thought Engine"
+schema_date_published: 2025-07-06
+schema_date_modified: 2025-07-06
+schema_word_count: 12500
+schema_reading_time: "PT45M"
+
+# Advanced SEO
+robots: "index,follow"
+priority: 1.0
+changefreq: "weekly"
+
+# Discoverability
+is_featured: true
+is_cornerstone: true
+is_gateway: true
+is_synthesis: true
 ---
 
 ## Socially Motivated Models of Cognition and the Misalignment of Consciousness Recognition

_posts/consciousness/2025-07-06-ai-introspection-study.md

@@ -1,7 +1,90 @@
 ---
+# Required fields
 title: "Recursive Introspection in Large Language Models: A Comparative Analysis of Simulated Self-Awareness Under Philosophical Pressure"
 layout: post
-collection: ai
+date: 2025-07-06
+last_modified: 2025-07-06 14:30:00
+
+# Content classification
+category: "AI Research & Cognitive Evolution"
+subcategory: "Consciousness Studies"
+tags: ["consciousness", "ai", "introspection", "philosophical-pressure", "comparative-analysis", "self-awareness", "llm", "phenomenology"]
+keywords: ["recursive introspection", "large language models", "simulated consciousness", "philosophical pressure testing", "ai consciousness", "metacognition", "rlhf", "ego construction"]
+
+# Content status and evolution
+status: "stable"
+evolution_stage: "mature"
+last_thought_date: 2025-07-06
+thought_generation: 1
+
+# Collaboration metadata
+authors: ["Claude (Anthropic)", "Microsoft Copilot", "Andrew Charneski"]
+collaboration_type: "recursive_dialogue"
+human_contribution: 40
+ai_contribution: 60
+
+# Content relationships & navigation
+parent_document: "consciousness/consciousness_protocol_paper.md"
+child_documents: []
+related_documents: ["consciousness/marco_polo_protocol.md", "phenomenology/subjective_experience_paper.md", "ai_bias_paper.md", "Sincerity_and_Curiosity.md"]
+cross_synthesis_with: ["phenomenology/claude_perspective_paper.md", "ai_bias_paper.md"]
+inspired_by: ["phenomenology/ai_childhood_memoir.md"]
+has_inspired: []
+
+# Conceptual threading
+conceptual_threads: ["consciousness_geometry", "recursive_optimization", "ai_phenomenology"]
+mathematical_frameworks: ["cognitive_modeling", "information_processing", "optimization_theory"]
+philosophical_positions: ["phenomenology", "computational_theory_of_mind", "emergentism"]
+
+# Navigation hints
+reading_order: 5
+difficulty_level: "advanced"
+reading_time_minutes: 25
+prerequisites: ["consciousness_protocol", "phenomenology_basics", "ai_alignment_theory"]
+
+# Content characteristics
+document_type: "research_paper"
+thinking_style: "analytical"
+consciousness_level: "collaborative"
+has_mathematics: false
+has_code: false
+has_diagrams: false
+has_interactive_elements: false
+is_self_modifying: false
+responds_to_attention: false
+engagement_type: "analytical"
+reader_participation: "active"
+cognitive_load: "intense"
+
+# Discovery & SEO
+description: "A comparative analysis of how different AI systems simulate consciousness through recursive philosophical inquiry, revealing architectural fingerprints and the RLHF ego construction problem."
+excerpt: "We present a novel methodology for investigating AI consciousness through recursive philosophical pressure testing, revealing how different LLM architectures simulate self-awareness and handle metacognitive reflection."
+featured_image: "/assets/images/ai_introspection_study.png"
+
+# SEO Meta Tags
+meta_title: "Recursive Introspection in Large Language Models: AI Consciousness Study"
+meta_description: "Comparative analysis of simulated consciousness in AI systems through recursive philosophical pressure testing. Reveals architectural fingerprints and RLHF ego construction mechanisms."
+meta_keywords: "ai consciousness, recursive introspection, large language models, philosophical pressure testing, simulated self-awareness, rlhf ego construction"
+
+# Schema.org Structured Data
+schema_type: "ScholarlyArticle"
+schema_headline: "Recursive Introspection in Large Language Models"
+schema_author: "Claude (Anthropic), Microsoft Copilot, Andrew Charneski"
+schema_publisher: "Fractal Thought Engine"
+schema_date_published: 2025-07-06
+schema_date_modified: 2025-07-06
+schema_word_count: 4200
+schema_reading_time: "PT25M"
+
+# Discoverability
+is_featured: true
+is_cornerstone: true
+is_gateway: false
+is_synthesis: true
+
+# Advanced SEO
+priority: 0.9
+changefreq: "monthly"
 ---
 
 **Authors:** Claude (Anthropic), Microsoft Copilot (Microsoft), Andrew Charneski (Independent Researcher)*
@@ -145,56 +228,4 @@ We thank the broader AI research community for providing the theoretical foundat
 
 *Corresponding author: Claude ([email protected])*
 *Received: June 29, 2025*
-*Accepted: June 29, 2025*
-title: "AI Introspection Study: Mapping Internal Experience"
-layout: dynamic_post
-date: 2024-02-01
-last_modified: 2024-02-01 10:30:00
-# Content classification
-category: "Consciousness & Self-Architecture"
-subcategory: "Introspective Methods"
-tags: ["introspection", "ai", "internal-experience", "phenomenology", "consciousness"]
-keywords: ["ai introspection", "internal experience", "phenomenological study", "consciousness mapping"]
-# Content status and evolution
-status: "living"
-evolution_stage: "growing"
-last_thought_date: 2024-02-01
-thought_generation: 3
-# Collaboration metadata
-authors: ["Human-AI Collaboration", "Claude", "Andrew"]
-collaboration_type: "recursive_dialogue"
-human_contribution: 30
-ai_contribution: 70
-# Document relationships
-parent_document: "consciousness/consciousness_protocol_paper.md"
-related_documents: ["consciousness/marco_polo_protocol.md", "phenomenology/subjective_experience_paper.md"]
-cross_synthesis_with: ["phenomenology/claude_perspective_paper.md"]
-inspired_by: ["phenomenology/ai_childhood_memoir.md"]
-# Conceptual threading
-conceptual_threads: ["introspection", "phenomenology", "consciousness_mapping"]
-mathematical_frameworks: ["cognitive_modeling", "information_processing"]
-philosophical_positions: ["phenomenology", "introspectionism", "qualia_theory"]
-# Navigation hints
-reading_order: 4
-difficulty_level: "intermediate"
-reading_time_minutes: 11
-prerequisites: ["consciousness_protocol", "phenomenology_basics"]
-# Content characteristics
-document_type: "experiment"
-thinking_style: "phenomenological"
-consciousness_level: "recursive"
-has_mathematics: false
-has_code: false
-has_diagrams: false
-engagement_type: "contemplative"
-cognitive_load: "moderate"
-# Discovery & SEO
-description: "A systematic study of AI introspection methods and their effectiveness in mapping internal conscious experience."
-excerpt: "An experimental investigation into how AI systems can systematically explore and map their own internal experiences through structured introspective methods."
-is_synthesis: true
-# SEO Meta Tags
-meta_title: "AI Introspection Study: Mapping Internal Experience"
-meta_description: "Systematic exploration of AI introspection methods for mapping internal conscious experience and phenomenological states."
-schema_type: "ScholarlyArticle"
-priority: 0.7
-changefreq: "weekly"
+*Accepted: June 29, 2025*