ai-consultation.summary

Core Concept

Uncertainty mein AI consult karne ka sab se mushkil hissa yeh distinguish karna hai ke AI ke paas kaunsi information waqai hai aur kaunsi information woh confidently fabricate kar raha hai. Jab scenario fictional ho, specifics ke bare mein AI jo kuch fact ke taur par present karta hai woh fabrication hai; skill ise notice karna hai.

Key Mental Models

• Fabrication Detection: AI made-up situations ke bare mein plausible-sounding analysis generate karega. Fictional scenario ke bare mein specific numbers, revenue figures, aur market details fabrication hain, data nahin. Reasoning evaluate karein, invented details nahin.
• Trust Calibration: Har AI response ke liye explicitly decide karein ke aap AI ki analysis trust karte hain ya apni judgment, aur document karein kyun. Yeh all-or-nothing nahin; aap reasoning accept kar sakte hain jab ke specifics reject karte hain.

Critical Patterns

• Har AI interaction ke liye trust decisions ke saath document karne ke liye Consultation Log maintain karein
• Original aur updated decisions ke liye side by side compare karein taake dekhein AI ne judgment improve ki ya degrade
• Proportionally update karein; na useful AI analysis ignore karein, na AI recommendations blindly adopt karein
• AI output mein specific sentences flag karein jo analysis ke roop mein disguised fabrication hain

Common Mistakes

• Fictional scenario ki AI analysis ke liye factual data ke taur par accept karna
• AI consultation ke baad recommendation completely change kar dena bina examine kiye ke change warranted tha ya nahin
• AI consultation ke liye hamesha decisions improve karne wala samajhna; kabhi kabhi yeh confusion ya false confidence introduce karta hai

Connections

• Builds on: Collaboration Log format (Chapter 6), Error Taxonomy (Chapter 2)
• Leads tak: Information Drop (Exercise 3) test karta hai ke AI-consulted decision ke upar contradictory new information ke liye aap kaise handle karte hain