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人工智能必须变得更加科学.

Peter V Coveney1,2,3,4, Roger Highfield5,6,7

  • 1Centre for Computational Science, Department of Chemistry, University College London, London WC1H 0AJ, U.K.

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此摘要是机器生成的。

人工智能 (AI) 越来越多地用于科学研究. 然而,当前的人工智能往往缺乏可重现性和透明度,阻碍其与科学方法的充分整合.

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科学领域:

  • 科学研究方法论科学研究方法论.
  • 科学中的人工智能.

背景情况:

  • 人工智能 (AI) 在科学研究中的应用正在迅速扩大.
  • 越来越需要评估人工智能工具在科学领域的影响和适用性.

研究的目的:

  • 评估人工智能对科学研究的影响.
  • 确定当前人工智能在遵守科学原则方面的局限性.
  • 为人工智能开发提出与科学方法一致的要求.

主要方法:

  • 在研究中对人工智能应用进行批判性审查.
  • 分析AI与核心科学原则 (如可重现性,透明度和客观性) 的结合.
  • 对AI机械理解能力的评估.

主要成果:

  • 目前在科学领域的人工智能实施经常显示出可复制性的缺陷.
  • 人工智能工具往往缺乏透明度,阻碍人们了解它们的决策过程.
  • 客观性和机械的理解并不是始终实现现有的AI在研究中.

结论:

  • 为了最大限度地发挥人工智能在科学中的好处,其发展必须优先考虑与科学方法的兼容性.
  • 未来用于研究的人工智能应该设计以确保可重现性,透明度和客观性.
  • 提高AI的机械理解对于其在科学发现中的可靠应用至关重要.