法医学遗传学人工智能的伦理和安全挑战:从偏见到对抗性攻击
Franco Marsico1, Martin Amigo2
1Faculty of Exact and Natural Sciences, Buenos Aires, Argentina.
Forensic science international. Genetics
|January 28, 2025
概括
法医科学中的人工智能 (AI) 为特征预测和亲属关系分析提供了新的方法. 然而",黑子"人工智能模型存在偏见和错误的风险,需要严格的评估和道德监督,以确保可靠的法医解释.
科学领域:
- 法医科学 法医科学 法医科学
- 计算生物学 计算生物学
- 遗传学 遗传学 是一个
背景情况:
- 法医科学家使用概率比 (LRs) 来量化竞争假设下的证据强度.
- 传统的LR模型依赖于累积的科学知识,需要透明度才能获得信任.
- 人工智能 (AI),包括深度和机器学习,提供了新的法医应用.
研究的目的:
- 批判性地检查AI方法在法医科学中的应用.
- 为了说明"黑子"人工智能模型在法医解释中的潜在陷和道德挑战.
- 突出需要严格评估和监督AI在法医遗传学.
主要方法:
- 利用模拟场景进行概念验证演示.
- 将人工智能方法应用于两个常见的法医任务:生物地理祖先预测和亲属推断.
- 从AI模型中批判性地分析了潜在的误导性结果.
主要成果:
- 演示了人工智能模型如何在模拟案件中潜在地误导法医解释.
- 识别了与法医学中的"黑子"人工智能相关的伦理和安全挑战.
- 强调了开发透明和严格的AI驱动的法医工具的复杂性.
结论:
- 法医学的AI方法虽然有希望,但由于它们的"黑子"性质,需要仔细验证.
- 人工智能模型中的潜在偏见和错误可以显著影响法律背景.
- 强调了在法医科学中采用人工智能的道德准则和严格监督的必要性.
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