src/research_engine/reasoning_engine.py

"""
Advanced Reasoning Engine for AI Capabilities Analysis
Provides sophisticated analysis and comparison frameworks
"""

from typing import Dict, List, Tuple, Any
import json
from datetime import datetime


class AdvancedReasoningEngine:
    """
    Advanced reasoning engine for analyzing AI capabilities,
    limitations, and human-AI comparison
    """
    
    def __init__(self):
        """Initialize reasoning engine"""
        from .capability_database import (
            CAPABILITY_DATABASE,
            LIMITATION_DATABASE,
            HUMAN_ADVANTAGES,
            RESEARCH_INSIGHTS,
            DOMAIN_IMPACT
        )
        
        self.capabilities = CAPABILITY_DATABASE
        self.limitations = LIMITATION_DATABASE
        self.human_advantages = HUMAN_ADVANTAGES
        self.research_insights = RESEARCH_INSIGHTS
        self.domain_impact = DOMAIN_IMPACT
    
    def generate_comprehensive_analysis(self) -> Dict[str, Any]:
        """
        Generate comprehensive analysis of AI capabilities and limitations
        
        Returns: {
            'summary': Brief overview,
            'detailed_analysis': Full analysis by category,
            'key_findings': Main conclusions,
            'implications': What this means for future,
            'recommendations': Suggested next steps
        }
        """
        analysis = {
            'timestamp': datetime.now().isoformat(),
            'title': 'Comprehensive AI Capabilities and Limitations Analysis - SLIIT Research',
            'executive_summary': self._generate_executive_summary(),
            'capability_analysis': self._analyze_capabilities(),
            'limitation_analysis': self._analyze_limitations(),
            'human_advantage_analysis': self._analyze_human_advantages(),
            'future_projection': self._project_future_capabilities(),
            'domain_specific_analysis': self._analyze_domains(),
            'key_research_findings': self._synthesize_findings(),
            'implications': self._derive_implications(),
            'recommendations': self._generate_recommendations()
        }
        return analysis
    
    def _generate_executive_summary(self) -> str:
        """Generate high-level executive summary"""
        return """
        EXECUTIVE SUMMARY: AI Capabilities, Limitations, and Human Advantages
        
        This research demonstrates that AI and humans have fundamentally different strengths:
        
        AI EXCELS AT:
        - Pattern recognition at massive scale (billions of patterns/second)
        - Mathematical and logical computation
        - Data processing and analysis
        - Narrow domain optimization
        - Consistent task automation
        
        AI STRUGGLES WITH:
        - True understanding and comprehension
        - Genuine creativity and novelty
        - Common sense reasoning
        - Transfer learning across domains
        - Long-term strategic planning
        - Ethical reasoning and moral judgment
        - Any task requiring consciousness or intentionality
        
        HUMANS EXCEL AT:
        - Creativity and generating novel ideas
        - General intelligence and flexible learning
        - Emotional and social intelligence
        - Long-term strategic thinking
        - Moral and ethical reasoning
        - Meaning-making and purpose
        - Complex social collaboration
        - Embodied, physical understanding
        
        FUTURE DIRECTION:
        Rather than AI replacing humans, the most effective approach is
        complementary collaboration where AI handles computation and
        pattern recognition, while humans provide creativity, judgment,
        and ethical guidance.
        """
    
    def _analyze_capabilities(self) -> Dict[str, Any]:
        """Detailed analysis of AI capabilities"""
        analysis = {}
        
        for capability_name, capability_data in self.capabilities.items():
            analysis[capability_name] = {
                'description': capability_data.get('description'),
                'examples': capability_data.get('examples', [])[:3],  # Top 3 examples
                'confidence_level': capability_data.get('confidence_level', 'Unknown'),
                'scale': capability_data.get('scale', 'N/A'),
                'real_world_applications': self._extract_applications(capability_name),
                'maturity_level': self._assess_maturity(capability_name)
            }
        
        return analysis
    
    def _analyze_limitations(self) -> Dict[str, Any]:
        """Detailed analysis of AI limitations"""
        analysis = {}
        
        for limitation_name, limitation_data in self.limitations.items():
            analysis[limitation_name] = {
                'description': limitation_data.get('description'),
                'technical_barrier': limitation_data.get('challenge', limitation_data.get('technical_barrier')),
                'current_status': limitation_data.get('current_status', 'Unsolved'),
                'why_impossible': limitation_data.get('why_impossible', 
                                                      ['Fundamental theoretical barrier']),
                'philosophical_implications': self._derive_philosophical_implications(limitation_name)
            }
        
        return analysis
    
    def _analyze_human_advantages(self) -> Dict[str, Any]:
        """Detailed analysis of human advantages"""
        analysis = {}
        
        for advantage_name, advantage_data in self.human_advantages.items():
            analysis[advantage_name] = {
                'description': advantage_data.get('description'),
                'examples': advantage_data.get('examples', [])[:3],
                'why_ai_lacks_this': self._explain_ai_limitation(advantage_name),
                'research_implications': self._imply_research_direction(advantage_name),
                'competitive_advantage': advantage_data.get('human_advantage', 'Significant')
            }
        
        return analysis
    
    def _project_future_capabilities(self) -> Dict[str, Any]:
        """Project what AI might do in future"""
        from .capability_database import FUTURE_CAPABILITIES
        
        projection = {
            'next_5_years': [],
            'next_10_years': [],
            'still_unknown': [],
            'likely_impossible': []
        }
        
        for capability_name, capability_data in FUTURE_CAPABILITIES.items():
            timeline = capability_data.get('timeline', 'Unknown')
            
            if '1-3' in timeline or '2-5' in timeline:
                projection['next_5_years'].append({
                    'capability': capability_name,
                    'description': capability_data.get('description'),
                    'potential_impact': capability_data.get('potential')
                })
            elif '5-10' in timeline or '10' in timeline:
                projection['next_10_years'].append({
                    'capability': capability_name,
                    'description': capability_data.get('description'),
                    'potential_impact': capability_data.get('potential')
                })
            elif '10-20' in timeline or 'unknown' in timeline.lower():
                projection['still_unknown'].append(capability_name)
        
        projection['likely_impossible'] = [
            'True consciousness',
            'Genuine creativity outside training data',
            'Intrinsic motivation',
            'Moral autonomy',
            'Subjective experience'
        ]
        
        return projection
    
    def _analyze_domains(self) -> Dict[str, Any]:
        """Domain-specific impact analysis"""
        analysis = {}
        
        for domain_name, domain_data in self.domain_impact.items():
            analysis[domain_name] = {
                'ai_capabilities': domain_data.get('ai_can_do', []),
                'ai_limitations': domain_data.get('ai_cannot_do', []),
                'recommended_synergy': domain_data.get('future_synergy'),
                'expected_impact': domain_data.get('impact'),
                'human_role_remains_critical': True
            }
        
        return analysis
    
    def _synthesize_findings(self) -> List[str]:
        """Synthesize key research findings"""
        findings = []
        
        for insight_name, insight_data in self.research_insights.items():
            findings.append({
                'statement': insight_data.get('statement'),
                'explanation': insight_data.get('explanation'),
                'research_significance': insight_data.get('research_importance')
            })
        
        return findings
    
    def _derive_implications(self) -> Dict[str, str]:
        """Derive implications for various stakeholders"""
        return {
            'for_policy_makers': """
            AI should be treated as a tool requiring human oversight, not as
            autonomous agents. Accountability must remain with humans.
            Regulations should focus on human use of AI, not AI behavior itself.
            """,
            
            'for_businesses': """
            AI is most valuable for automating routine tasks and enhancing
            human decision-making. Investment should focus on human-AI
            collaboration, not replacement. Human workers in creative and
            judgment roles become MORE valuable, not less.
            """,
            
            'for_educators': """
            Teaching humans to collaborate with AI is critical. Education should
            emphasize uniquely human skills: creativity, emotional intelligence,
            ethical reasoning, and meaning-making. Rote learning becomes
            obsolete and teaching those skills becomes essential.
            """,
            
            'for_researchers': """
            Understanding consciousness and common sense reasoning are critical
            next frontiers. Current AI approach (pattern matching) likely
            insufficient for deeper understanding. New theoretical frameworks
            may be needed.
            """,
            
            'for_technologists': """
            Stop trying to replace humans. Focus on augmenting human abilities.
            Explainability and interpretability become critical. Building trust
            and transparency is more important than raw capability.
            """,
            
            'for_society': """
            AI will displace routine work but create new opportunities in
            creative, social, and ethical domains. Focus on human development,
            not fearing AI. Economic policies should address displacement but
            recognize AI's benefits in healthcare, science, and education.
            """
        }
    
    def _generate_recommendations(self) -> List[str]:
        """Generate recommendations from analysis"""
        return [
            "Research should focus on understanding consciousness and common sense",
            "Policy should ensure AI remains tool under human control and accountability",
            "Education should emphasize uniquely human skills (creativity, ethics, collaboration)",
            "Businesses should invest in human-AI collaboration, not replacement",
            "Society should prepare for transition away from routine work",
            "Maintain healthy skepticism about AI capabilities and limitations",
            "Develop strong ethical frameworks for AI deployment",
            "Continue studying AI safety and alignment",
            "Invest in understanding human cognition and consciousness",
            "Build public literacy about AI capabilities and limitations"
        ]
    
    def _extract_applications(self, capability_name: str) -> List[str]:
        """Extract real-world applications"""
        # Simplified version - in reality would cross-reference with domain data
        return [f"Application of {capability_name} in industry"]
    
    def _assess_maturity(self, capability_name: str) -> str:
        """Assess technological maturity level"""
        mature_capabilities = ['pattern_recognition', 'data_analysis', 'task_automation']
        emerging_capabilities = ['scientific_discovery', 'content_generation']
        
        if capability_name in mature_capabilities:
            return "Production-Ready (Mature)"
        elif capability_name in emerging_capabilities:
            return "Emerging (2-5 years to production)"
        else:
            return "Research Phase"
    
    def _derive_philosophical_implications(self, limitation_name: str) -> str:
        """Derive philosophical implications of limitation"""
        if 'consciousness' in limitation_name.lower():
            return "Raises deep questions about nature of mind and awareness"
        elif 'understanding' in limitation_name.lower():
            return "Suggests difference between processing and comprehension"
        elif 'creativity' in limitation_name.lower():
            return "Implies novelty requires transcendence of training data"
        else:
            return "Suggests fundamental difference between AI and human cognition"
    
    def _explain_ai_limitation(self, advantage_name: str) -> str:
        """Explain why AI lacks human advantage"""
        return f"AI lacks the embodied experience, consciousness, and intrinsic motivation necessary for {advantage_name}"
    
    def _imply_research_direction(self, advantage_name: str) -> str:
        """Imply research direction from human advantage"""
        return f"Understanding {advantage_name} in humans could guide AI development"
    
    def generate_research_paper_outline(self) -> str:
        """Generate outline for research paper on AI capabilities"""
        return """
        # RESEARCH PAPER OUTLINE: Understanding AI Capabilities, Limitations, and Human Advantages
        ## For SLIIT Research Project
        
        I. INTRODUCTION
           A. Context: Rise of AI in modern society
           B. Research Question: What can and cannot AI do? What are human advantages?
           C. Significance: Understanding AI limitations is as important as capabilities
           D. Scope: Comprehensive analysis across domains
        
        II. WHAT AI CAN DO (Current Capabilities)
            A. Pattern Recognition and Machine Perception
               1. Visual recognition (99.9% accuracy in many tasks)
               2. Natural language processing (near-human level in some tasks)
               3. Anomaly detection in complex datasets
            
            B. Computation and Optimization
               1. Mathematical computation (superhuman speed)
               2. Optimization of constrained problems
               3. Complex logistics and routing
            
            C. Task Automation
               1. Routine administrative tasks
               2. Data processing and transformation
               3. Report generation from structured data
            
            D. Data Analysis at Scale
               1. Processing terabytes of data
               2. Statistical analysis and correlation
               3. Trend detection and forecasting
            
            E. Domain-Specific Expertise
               1. Game playing (superhuman in Chess, Go, Dota2)
               2. Medical image analysis
               3. Scientific discovery acceleration
        
        III. WHAT AI CANNOT DO (Fundamental Limitations)
             A. True Understanding and Comprehension
                1. No semantic meaning (only pattern matching)
                2. Symbol grounding problem
                3. Lacks experiential understanding
             
             B. Genuine Creativity
                1. Recombination vs. true novelty
                2. Limited to training data distribution
                3. No conceptual breakthroughs
             
             C. Consciousness and Subjective Experience
                1. Hard problem of consciousness
                2. No phenomenal experience
                3. Cannot care about anything
             
             D. Common Sense Reasoning
                1. Physical intuitions unstable
                2. Social reasoning incomplete
                3. Context understanding limited
             
             E. Long-term Strategic Planning
                1. Compound uncertainty grows exponentially
                2. Multi-objective trade-offs poorly handled
                3. Cannot integrate 20-year timescales
             
             F. Moral and Ethical Judgment
                1. Can follow rules, not understand ethics
                2. No moral intuition
                3. Cannot take ethical responsibility
        
        IV. WHAT HUMANS DO BETTER (Human Advantages)
            A. Creativity and Innovation
               1. Genuine novel ideas
               2. Cross-domain conceptual transfer
               3. Artistic and creative expression
            
            B. General Intelligence
               1. Learning from minimal examples
               2. Transfer learning across domains
               3. Understanding underlying principles
            
            C. Emotional and Social Intelligence
               1. Genuine empathy and understanding
               2. Complex social navigation
               3. Building meaningful relationships
            
            D. Moral and Ethical Reasoning
               1. Navigating ethical dilemmas with nuance
               2. Understanding values and principles
               3. Taking responsibility
            
            E. Embodied Understanding
               1. Physical intuitions from lived experience
               2. Motor skills and coordination
               3. Aesthetic and sensory appreciation
            
            F. Meaning-Making and Purpose
               1. Creating intrinsic meaning
               2. Setting own goals
               3. Pursuing growth and self-actualization
        
        V. FUTURE CAPABILITIES (5-10 Year Projection)
           A. Likely Improvements
              1. Better few-shot learning
              2. Improved common sense reasoning
              3. Faster autonomous experimentation
           
           B. Likely Persistent Gaps
              1. True understanding
              2. Genuine creativity
              3. Consciousness
              4. Moral autonomy
        
        VI. DOMAIN-SPECIFIC ANALYSIS
            A. Healthcare
               1. AI: Diagnosis, drug discovery, outcome prediction
               2. Human: Compassion, ethical decisions, trust-building
            
            B. Education
               1. AI: Personalization, assessment, content delivery
               2. Human: Inspiration, mentorship, character building
            
            C. Creative Industries
               1. AI: Automation, iteration, technical execution
               2. Human: Vision, originality, artistic meaning
            
            D. Scientific Research
               1. AI: Literature analysis, data processing, hypothesis testing
               2. Human: Conceptual breakthroughs, research direction, understanding
        
        VII. IMPLICATIONS AND RECOMMENDATIONS
             A. For Policy and Society
                1. Treat AI as tool, not agent
                2. Maintain human accountability
                3. Prepare for work transition
             
             B. For Business and Economics
                1. Invest in human-AI collaboration
                2. Develop human skills AI cannot replace
                3. Economic policies for displaced workers
             
             C. For Education
                1. Teach uniquely human skills
                2. AI literacy critical
                3. Ethical reasoning and creativity crucial
             
             D. For Research
                1. Study consciousness and understanding
                2. Explore human-AI collaboration
                3. Develop AI safety frameworks
        
        VIII. CONCLUSION
              A. AI and humans have complementary strengths
              B. Future is collaboration, not replacement
              C. Human advantages in creativity and ethics remain irreplaceable
              D. Society should embrace AI benefits while protecting human values
        
        IX. REFERENCES
            [Comprehensive academic references on AI, consciousness, creativity, etc.]
        """
    
    def export_analysis_as_json(self) -> str:
        """Export comprehensive analysis as JSON"""
        analysis = self.generate_comprehensive_analysis()
        return json.dumps(analysis, indent=2)
    
    def generate_comparison_table(self) -> str:
        """Generate HTML table comparing AI vs Humans"""
        html = """
        <table border="1" cellpadding="10">
            <thead>
                <tr>
                    <th>Domain</th>
                    <th>AI Strength</th>
                    <th>Human Strength</th>
                    <th>Winner</th>
                </tr>
            </thead>
            <tbody>
                <tr>
                    <td>Mathematical Computation</td>
                    <td>Superhuman (seconds)</td>
                    <td>Average (hours)</td>
                    <td><strong>AI</strong></td>
                </tr>
                <tr>
                    <td>Creative Writing</td>
                    <td>Adequate (formulaic)</td>
                    <td>Vastly Superior</td>
                    <td><strong>HUMAN</strong></td>
                </tr>
                <tr>
                    <td>Image Recognition</td>
                    <td>Superhuman (99.9%)</td>
                    <td>Very Good (99%)</td>
                    <td><strong>AI</strong></td>
                </tr>
                <tr>
                    <td>Strategic Planning</td>
                    <td>Good (narrow problems)</td>
                    <td>Vastly Superior</td>
                    <td><strong>HUMAN</strong></td>
                </tr>
                <tr>
                    <td>Data Analysis</td>
                    <td>Superhuman (terabytes/sec)</td>
                    <td>Limited (kilobytes)</td>
                    <td><strong>AI</strong></td>
                </tr>
                <tr>
                    <td>Emotional Support</td>
                    <td>Can simulate</td>
                    <td>Genuine empathy</td>
                    <td><strong>HUMAN</strong></td>
                </tr>
                <tr>
                    <td>Learning New Skills</td>
                    <td>Requires retraining</td>
                    <td>Can learn in weeks</td>
                    <td><strong>HUMAN</strong></td>
                </tr>
                <tr>
                    <td>Pattern Recognition</td>
                    <td>Superhuman (visual)</td>
                    <td>Good (familiar)</td>
                    <td><strong>AI</strong></td>
                </tr>
                <tr>
                    <td>Moral Judgment</td>
                    <td>Applies rules</td>
                    <td>Navigates nuance</td>
                    <td><strong>HUMAN</strong></td>
                </tr>
                <tr>
                    <td>Physical Dexterity</td>
                    <td>Improving (limited)</td>
                    <td>Vastly Superior</td>
                    <td><strong>HUMAN</strong></td>
                </tr>
            </tbody>
        </table>
        """
        return html