What is science for? The Lighthill report on artificial intelligence reinterpreted
What is science for? The Lighthill report on artificial intelligence reinterpreted
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DOI：
10.1017/s0007087420000230
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发表时间：
2020-09-01
影响因子：
0.8
通讯作者：
Agar, Jon
中科院分区：
文献类型：
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作者：
Agar, Jon
本文以 20 世纪 70 年代人工智能 (AI) 研究中的一场争议为案例，探讨科学家如何理解研究与实际应用之间的关系。它是一个项目的一部分，该项目旨在绘制这种关系，以便通过历史证据以经验为基础提出更好的政策建议。 1972 年，数学家詹姆斯·莱特希尔 (James Lighthill) 提交了一份关于英国人工智能研究现状的报告，该报告于 1973 年发表。报告中提出的批评被认为是此类研究急剧放缓（随后被称为“人工智能冬天”）的主要原因。本文有两个目标，一是狭义的，一是广义的。狭隘的目的是探究莱特希尔报告的原因、动机和内容。我认为詹姆斯·莱特希尔对人工智能核心部分的批评背后是他在整个职业生涯中坚持的原则——最好的研究与实际问题的解决紧密结合。我还表明，科学研究委员会为这份明显独立的报告的方向提供了初步指导。本文更广泛的目标是描绘科学家（在莱特希尔的例子中，是一位数学家）阐明和论证研究与实际、现实世界问题之间关系的一些方式，这个问题之前被认为是现代科学历史分析的核心问题。因此，本文对琼脂“工作世界”模型中确定的过程提供了一些深入的历史案例研究。
This paper uses a case study of a 1970s controversy in artificial-intelligence (AI) research to explore how scientists understand the relationships between research and practical applications. It is part of a project that seeks to map such relationships in order to enable better policy recommendations to be grounded empirically through historical evidence. In 1972 the mathematician James Lighthill submitted a report, published in 1973, on the state of artificial-intelligence research under way in the United Kingdom. The criticisms made in the report have been held to be a major cause behind the dramatic slowing down (subsequently called an 'AI winter') of such research. This paper has two aims, one narrow and one broad. The narrow aim is to inquire into the causes, motivations and content of the Lighthill report. I argue that behind James Lighthill's criticisms of a central part of artificial intelligence was a principle he held throughout his career - that the best research was tightly coupled to practical problem solving. I also show that the Science Research Council provided a preliminary steer to the direction of this apparently independent report. The broader aim of the paper is to map some of the ways that scientists (and in Lighthill's case, a mathematician) have articulated and justified relationships between research and practical, real-world problems, an issue previously identified as central to historical analysis of modern science. The paper therefore offers some deepened historical case studies of the processes identified in Agar's 'working-worlds' model.