人类幻觉比AI要严重多了

Group 1 - The article discusses the phenomenon of AI hallucinations, where AI models provide seemingly accurate but fabricated information due to issues with training data quality and completeness [2][3] - Google's official explanation attributes AI hallucinations to two main reasons: the quality of training data and the model's difficulty in accurately understanding real-world knowledge [2] - A study by Vectara in March 2025 found that leading AI models have low hallucination rates, with Gemini-2.0-Flash-001 achieving a 0.7% hallucination rate, indicating high accuracy in document processing [3] Group 2 - The article compares the hallucination rates of AI models to human error rates, noting that top AI models outperform human experts in knowledge-intensive tasks but still lag in open-ended creative tasks [7] - In the medical field, the World Health Organization reported an average misdiagnosis rate of 30%, highlighting that human cognitive biases lead to more significant errors than AI hallucinations [8] - Human cognitive biases, such as confirmation bias and anchoring effects, contribute to a higher incidence of misjudgment compared to AI, as illustrated by historical examples like the Titanic disaster and the Chernobyl accident [9][10]