解释和预测的科学价值
Hause Lin1,2
1Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA hauselin@gmail.com https://www.hauselin.com.
The Behavioral and brain sciences
|December 6, 2023
概括
深度神经网络 (DNN) 是科学进步的核心,引发了关于解释与预测的辩论. 批评可能会刺激新的研究来整合这两种方法,重新定义科学知识的价值.
科学领域:
- 人工智能的人工智能
- 科学哲学的哲学科学哲学
- 计算科学 计算科学
背景情况:
- 深度神经网络 (DNN) 越来越多地被用于科学研究.
- 它们的预测能力导致了关于它们在科学中的解释价值的辩论.
- 尔斯和其他人. 已经批判性地检查了DNN在科学发现中的作用.
研究的目的:
- 在DNN的背景下,分析围绕解释与预测的持续辩论.
- 评估批评对DNN在科学中的未来发展和应用的影响.
- 探索如何调和解释和预测模型可以重新定义科学知识.
主要方法:
- 文献综述和对科学中DNN现有研究的批判性分析.
- 考察有关预测和解释的哲学论点.
- 对不同建模方法价值的观点的综合.
主要成果:
- 对DNN的批评不太可能阻止它们的科学应用.
- 预计这场辩论将刺激旨在整合解释和预测能力的研究.
- 预计有价值的科学知识的标准可能会发生转变.
结论:
- 在科学研究中,DNN将继续发挥影响力.
- 未来的研究很可能会专注于开发提供解释和预测的混合模型.
- 有价值的科学知识的定义可能会发展到包括更广泛的模型属性.
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