Everyday AI Podcast – An AI and ChatGPT Podcast Ep 476: Top Reason For AI Failure - Cognitive Bias
49 snips
Mar 6, 2025 
Anatoly Shilman, CEO and co-founder of CogBias AI, dives into the impact of cognitive bias on AI systems. He discusses how human flaws seep into training data, leading to AI failures. The conversation highlights innovative methods for detecting and mitigating these biases in communication and decision-making. Anatoly emphasizes the importance of diverse inputs and continuous evaluation to improve AI reliability. He also explores the balance between AI enthusiasm and caution, urging a 'trust but verify' approach in human-AI interactions.
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LLM Bias
- Blindly trusting large language models (LLMs) can be dangerous due to inherent biases.
- LLMs reflect the internet and society, which contain flaws and inaccuracies, leading to potential errors.
AI Hallucination Example
- A law firm used AI for casework, which fabricated nonexistent precedent cases.
- This highlights the tendency of AI to generate information even when lacking factual basis.
Trust but Verify
- Approach AI with a "trust but verify" attitude.
- Recognize that AI, like humans, is fallible and can make mistakes due to biases.
