This blog post discusses a presentation by Professor George Gui from Columbia Business School on the challenges of using large language models (LLMs) for simulating counterfactual human behavior in experimental designs. It highlights issues with traditional methodologies and advocates for a rethinking of experimental practices when applying LLMs, suggesting that unblinding experimental designs may help address confounding issues.