LLM Themes Are Not Observations

📰 Towards Data Science

Learn why LLM themes should not be treated as observations in causal analysis and how to avoid common pitfalls

intermediate Published 21 May 2026

Action Steps

Identify the differences between generated variables and observations in causal analysis
Avoid using LLM themes as direct observations in statistical models
Use LLM themes as inspiration for hypothesis generation and exploration
Validate findings using traditional observational data and statistical methods
Consider the limitations and potential biases of LLM-generated variables

Who Needs to Know This

Data scientists and analysts working with LLMs and causal analysis will benefit from understanding the distinction between generated themes and observations to ensure accurate conclusions

Key Insight

💡 LLM themes are generated variables that require careful consideration and validation before being used in causal analysis