Deep Learning Opacity in Scientific Discovery
Deep Learning Opacity in Scientific Discovery
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DOI：
10.1017/psa.2023.8
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发表时间：
2022-06
影响因子：
1.7
通讯作者：
Eamon Duede
中科院分区：
文献类型：
--
作者：
Eamon Duede
摘要：哲学家关注在科学中使用人工智能（AI）所面临的认识论和伦理挑战，而科学家则主要关注机遇。我认为，哲学上的悲观主义与科学上的乐观主义之间的这种脱节是由于未能批判性地审视融入人工智能的科学实践所导致的。要理解人工智能驱动的突破在认识论上的合理性，哲学家必须分析人工智能作为更广泛的发现过程的一部分所起的作用。我通过科学文献中的两个案例证明了这一点的重要性，并表明认识上的不透明性不一定会削弱人工智能引导科学家取得重大且合理的突破的能力。
Abstract While philosophers have focused on epistemological and ethical challenges of using artificial intelligence (AI) in science, scientists have focused largely on opportunities. I argue that this disconnect between philosophical pessimism and scientific optimism is driven by failures to critically examine the practice of AI-infused science. To appreciate the epistemic justification for AI-powered breakthroughs, philosophers must analyze the role of AI as part of a wider process of discovery. I demonstrate the importance of this with two cases from the scientific literature, and show that epistemic opacity need not diminish AI’s capacity to lead scientists to significant and justifiable breakthroughs.