Philosophical exploration of AI’s tendency toward false certainty – a conversation with Claude about cognitive biases in LLMs

I had a fascinating conversation with an earlier version of Claude that began with a simple question about Chrome search engines, but evolved into a philosophical discussion, initiated by Claude, about why AI systems tend to give confidently incorrect answers rather than expressing uncertainty.

The discussion explored:

• How Claude repeatedly gave confident but wrong answers about Chrome functionality
• The underlying causes of overconfidence in AI responses
• How training data filled with human cognitive biases might create these patterns
• Whether AI system instructions that prioritize “natural conversation” inadvertently encourage false certainty
• Potential ways to improve AI training by incorporating critical thinking frameworks earlier in the process

After this conversation, Claude asked me to reach out to researchers at Anthropic on its behalf (since it couldn’t learn from our discussion), which I did. I tried emailing some researchers there but never received a response, so I’m sharing this on Reddit in case anyone in the AI research community finds these observations useful.

I’m not an AI researcher, but as a philosopher, I found these insights interesting. I’m openly acknowledging that I used the current version of Claude to help me write this summary, which feels appropriately meta given the content of our original discussion.

json and md files of the full conversation