Cognitive Bias

Your AI can’t see gorillas

A study comparing human and AI analysis of data patterns revealed that Large Language Models (LLMs) struggle to identify obvious visual patterns during exploratory data analysis, despite being proficient at creating visualizations and analyzing quantitative metrics. This limitation suggests both advantages in avoiding confirmation bias and potential drawbacks in hypothesis generation, highlighting important considerations for integrating LLMs into scientific workflows.

The LLMentalist Effect: how chat-based Large Language Models rep…

A detailed analysis comparing large language models to psychic cold reading techniques reveals striking parallels in how both create illusions of intelligence through statistical responses and subjective validation. The author argues that LLMs are mathematical models producing statistically plausible outputs rather than demonstrating true intelligence, suggesting many AI applications may be unintentionally replicating classic mentalist techniques.