生物人工智能模型的双重用途能力令人担忧
Jaspreet Pannu1,2, Doni Bloomfield3, Robert MacKnight4
1Center for Health Security, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland.
PLoS computational biology
|May 8, 2025
概括
政府正在解决人工智能 (AI) 的风险,尤其是对生物数据进行训练的AI模型. 来自生命科学双重用途研究的教训可以为人工智能安全评估提供信息,以防止对流行病等威胁的滥用.
科学领域:
- 生命科学 生命科学
- 人工智能的人工智能
- 生物安全是生物安全.
背景情况:
- 各国和国际机构正在解决人工智能安全,安全和道德问题,这是由于快速的进步.
- 一个关键的问题是减轻AI滥用发展化学,生物,核或放射性 (CBRN) 威胁.
- 生命科学研究长期以来一直在管理意外或故意滥用的风险,特别是在工程生物中.
研究的目的:
- 以生命科学双重用途研究的见解为基础,对经过生物数据培训的AI模型进行评估.
- 优先考虑带来高后果风险的AI能力,例如流行病级疾病爆发.
- 倡导进行部署前评估,以实施生物安全和生物安全措施.
主要方法:
- 利用历史经验和对生命科学中双重用途研究的研究.
- 分析在生物数据上训练的人工智能模型的潜力,以实现高后果风险.
- 检查识别人工智能能力的必要性,以最大的生物安全和生物安全问题.
主要成果:
- 人工智能支持的生命科学研究存在类似于传统生物研究的双重使用风险.
- 优先考虑可能使大规模的公共危害 (例如,流行病) 成为可能的AI模型至关重要.
- 在部署人工智能模型之前评估风险对于实施安全措施至关重要.
结论:
- 管理双重用途生物风险的经验为评估生物人工智能模型提供了一个框架.
- 需要有针对性的AI安全评估方法来解决特定的生物安全和生物安全问题.
- 积极的风险评估和缓解对于利用人工智能的好处至关重要,同时防止滥用.
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