AI检测外星生命可能误判非生命样本为生命，存在极高假阳性风险。
Can AI Detect Life? Lessons from Artificial Life
- 用人工生命系统模拟外星样本，测试AI分类器的判别能力。
- AI对非生命样本的误判率接近100%，远超预期。
- 提醒科研人员慎用AI判断地外生命，尤其在数据分布不匹配时。
现代机器学习方法被用于探测地外样本中的生命迹象，通过训练模型区分生物与非生物有机分子混合物。本文利用人工生命系统表明，此类方法极易被欺骗，即使分析样本完全不具备生命特征，仍能以接近100%的置信度误判为有生命。这源于现代机器学习对分布外样本（out-of-distribution）的敏感性。由于地外样本极可能超出地球生物与非生物样本的分布范围，使用AI进行生命探测很可能导致大量假阳性结果。
原文摘要 · Abstract (English)
Modern machine learning methods have been proposed to detect life in extraterrestrial samples, drawing on their ability to distinguish biotic from abiotic samples based on training models using natural and synthetic organic molecular mixtures. Here we show using Artificial Life that such methods are easily fooled into detecting life with near 100% confidence even if the analyzed sample is not capable of life. This is due to modern machine learning methods' propensity to be easily fooled by out-of-distribution samples. Because extra-terrestrial samples are very likely out of the distribution provided by terrestrial biotic and abiotic samples, using AI methods for life detection is likely to yield significant false positives.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。