What Happens When You Ask an AI the Same Question 100 Times?

2026-06-10 · Source: AI Advances - Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics · Depth: Novice, medium

Summary

An experiment involved asking ChatGPT the same career-switching question 100 times across new, separate sessions over three days. Contrary to expectations of near-consistency, the responses varied significantly. While approximately 60% followed a familiar template, recommending Python, statistics, and projects, 40% offered divergent advice, focusing on psychological challenges, recommending specific individuals, or dismissing entire categories of resources. Key variations included the level of confidence in recommendations, significant omissions of core topics like statistics or Kaggle, and inconsistent specific advice on courses, books, or tools. This revealed that AI outputs are samples from a probability distribution, not a stable, singular viewpoint.

Key takeaway

For professionals relying on AI for critical advice, you should never treat a single AI response as a definitive answer. Instead, query the AI multiple times with the same question, comparing the outputs to identify consistent patterns and significant discrepancies. This approach helps you map the range of possibilities and verify recommendations that could meaningfully impact your decisions.

Key insights

AI responses are samples from a probability distribution, not a consistent, stable point of view.

Principles

• AI lacks a stable, coherent viewpoint.
• Perceived consistency stems from single-session use.
• AI optimizes for coherent text generation.

Method

Query AI multiple times with the same prompt, compare outputs, identify recurring themes, and verify specific recommendations.

In practice

• Repeat prompts, note output differences.
• Directly ask about omitted elements.
• Investigate recommendations appearing consistently.

Topics

• AI Consistency
• ChatGPT
• Large Language Models
• Prompt Engineering
• Data Science Careers
• AI Advice

Best for: AI Engineer, Machine Learning Engineer, NLP Engineer, AI Student, Data Scientist, General Interest

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Editorial summary, takeaway, and curation by AIssential. Original article published by AI Advances - Medium.