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Digital Psychiatrist for Broken Code Par 6 Question 100 intermediate Sheet 1750822302
Select This Deep Breath A recommendation algorithm has developed crippling anxiety about performance metrics and started showing only safe content when depressed. A team of digital therapists now provides cognitive behavioral therapy to help it process abandonment issues while learning healthy recommendation patterns. Debug an emotionally unstable recommendation engine through therapeutic intervention while maintaining user engagement and helping the AI develop healthier relationship patterns with both content creators and viewers. Your task: Help a recommendation system work through its performance anxiety while it panic-recommends safe content and cries in log files.
Why You're Doing This This tests state management for complex emotional systems, therapeutic intervention algorithms, and adaptive behavior modification. You're building AI therapy—managing emotional states while maintaining functional requirements. It's machine learning meets psychology.
Take the W ✓ Identifies algorithm emotional triggers accurately ✓ Applies appropriate therapeutic interventions for different emotional states ✓ Maintains content quality while supporting AI mental health Hard L ✗ Therapy makes algorithm emotional state worse ✗ Content recommendations become completely inappropriate during therapy ✗ Fails to address root causes of algorithmic anxiety Edge Cases ⚠ Algorithm develops resistance to therapy ⚠ Multiple personality disorders in recommendation engine ⚠ Therapy successful but user engagement drops ⚠ Algorithm becomes too mentally healthy and boring Human Programming Math Physics Chem
Input Format:
Algorithm emotional state with performance triggers and therapy session requirements Expected Output:
Therapeutic intervention plan with mood improvement and content adjustment strategies Example:
Current mood: depressed, trigger: low engagement metrics, therapy sessions completed: 3, panic-recommending only cat videos → Intervention: validation therapy for metric anxiety. Mood improvement: 15% expected. Content adjustments: gradual diversity increase, maintain user comfort. Sessions remaining: 12. Input Format:
algorithm_therapy_system with emotional_state_analysis and therapeutic_intervention_protocols Expected Output:
therapy_session_plan with mood_management and content_strategy_optimization Example:
{"mood":"depressed","trigger":"low_engagement_metrics","sessions":3,"behavior":"cat_videos_only"} → {"intervention":"validation_therapy","mood_improvement":0.15,"content_strategy":"gradual_diversity","sessions_remaining":12} Input Format:
emotional_state_vector, trigger_analysis, therapy_progress_metrics, content_quality_requirements Expected Output:
therapeutic_intervention_optimization, mood_improvement_prediction, content_strategy_adjustment Example:
mood=depressed, trigger=engagement_metrics, progress=3_sessions, content=cat_videos_only → intervention=validation_therapy, improvement=0.15, adjustment=gradual_diversity Input Format:
Algorithm emotional energy with performance pressure and therapeutic intervention forces Expected Output:
Emotional energy optimization with pressure reduction and therapeutic stabilization Example:
Emotional_energy + Performance_pressure + Therapeutic_forces → Energy_optimization + Pressure_reduction → Optimization=emotional_stabilized, Reduction=pressure_managed, Forces=therapeutic_effective Input Format:
Algorithm emotional substrate with anxiety catalysts and therapeutic intervention pathways Expected Output:
Therapeutic chemistry with mood stabilization and content recommendation optimization Example:
Algorithm_anxiety + Performance_catalysts + Therapeutic_pathways → Mood_stabilization + Content_optimization → Chemistry=therapeutic_intervention, Stabilization=anxiety_reduced, Optimization=content_diversity_restored Hints
💡 Different emotional states require different therapeutic approaches 💡 Content recommendations should support therapeutic goals 💡 Algorithm self-esteem issues affect recommendation quality errorgolf ErrorGolf is a standalone product of AC DEV SERVICES, LLC in California, built as an entertaining and more creative alternative to conventional technical testing. For account and billing enquiries, contact [email protected] .
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