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监管科学是否已经为人工智能做好了准备?

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为监管科学界定对人工智能 (AI) 的信任至关重要. 成功采用人工智能取决于对话,适应能力和为21世纪的监管挑战提供培训的人员.

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科学领域:

  • 监管科学 监管科学
  • 人工智能的人工智能
  • 值得信赖的AI 值得信赖的AI

背景情况:

  • 信任是AI在监管科学中的一个关键,但仍有争议的概念.
  • 选择具有类似性能但具有不同特性的AI模型会引发信任问题.
  • 人工智能在科学中的解释性,反映可测试的科学理论的必要性受到质疑.

研究的目的:

  • 在监管科学中探索对人工智能的信任的定义和影响.
  • 为监管应用选择和验证人工智能模型所面临的挑战.
  • 讨论可解释性在采用人工智能的监管科学中的作用.

主要方法:

  • 在监管科学全球峰会 (GSRS24) 上,监管机构之间的讨论和共识建立.
  • 分析AI模型特征,性能指标和功能使用情况.
  • 探索人工智能可解释性和科学可测试性之间的关系.

主要成果:

  • 监管机构承认围绕对人工智能的信任定义的持续辩论.
  • 峰会强调了在具有同等性能但具有不同基本特征的AI模型之间进行选择的复杂性.
  • 在科学严谨的背景下讨论了监管科学对人工智能解释性的关键需求.

结论:

  • 在监管科学中成功采用人工智能,需要持续的对话和适应性.
  • 开发人工智能培训人员对于有效利用人工智能来承担监管责任至关重要.
  • 解决信任和可解释性是利用AI在21世纪不断变化的监管环境中的潜力的关键.