《经济学人》双语：人工智能是如何改变科学研究的？

原文标题：
When robots do research
How artificial intelligence can revolutionise science
Consider the historical precedents
当机器人做研究
人工智能如何彻底改变科学
参考历史先例

[Paragraph 1]
DEBATE ABOUT artificial intelligence (AI) tends to focus on its potential dangers: algorithmic bias and discrimination, the mass destruction of jobs and even, some say, the extinction of humanity.
关于人工智能 (AI) 的争论往往都集中在潜在危险上：算法偏见与歧视、大规模失业，甚至有人担心人类灭绝。

As some observers fret about these dystopian scenarios, however, others are focusing on the potential rewards.
然而，一些人担心这些反乌托邦的场景，而另一些人关注的是潜在的回报。

AI could, they claim, help humanity solve some of its biggest and thorniest problems.
他们称，人工智能可以帮助人类解决一些最大最棘手的问题。

And, they say, AI will do this in a very specific way: by radically accelerating the pace of scientific discovery, especially in areas such as medicine, climate science and green technology.
他们称，人工智能将以特定的方式实现这一目标：从根本上加快科学研究的步伐，尤其对医学、气候科学和绿色技术等领域有帮助。

Luminaries in the field such as Demis Hassabis and Yann LeCun believe that AI can turbocharge scientific progress and lead to a golden age of discovery.
戴密斯·哈萨比斯和杨立昆等该领域的杰出人士认为，人工智能可以加速科学进步，并引领研究发现的黄金时代。

Could they be right?
他们是对的吗？

[Paragraph 2]
Such claims are worth examining, and may provide a useful counterbalance to fears about large-scale unemployment and killer robots.
这种说法值得研究，并且可能抵消掉人们对大规模失业和机器人杀手的担忧。

Many previous technologies have, of course, been falsely hailed as panaceas.
当然，历史上许多技术也曾被错误地誉为灵丹妙药。

The electric telegraph was lauded in the 1850s as a herald of world peace, as were aircraft in the 1900s; pundits in the 1990s said the internet would reduce inequality and eradicate nationalism.
1850年代，电报被誉为世界和平的先驱，1900年代的飞机也是如此。1990年代的专家称互联网将减少不平等并消除民族主义。

But the mechanism by which AI will supposedly solve the world’s problems has a stronger historical basis, because there have been several periods in history when new approaches and new tools did indeed help bring about bursts of world-changing scientific discovery and innovation.
但人工智能解决世界问题的机制有着坚实的历史基础，因为历史上有几个时期，新方法和新工具确确实实帮助推动了世界性的科学发现和创新爆发。

[Paragraph 3]
In the 17th century microscopes and telescopes opened up new vistas of discovery and encouraged researchers to favour their own observations over the received wisdom of antiquity, while the introduction of scientific journals gave them new ways to share and publicise their findings.
17世纪的显微镜和望远镜开辟了研究新视野，促使研究者更加重视自己的观察结果，而非古代的传统智慧。科学期刊的出现则为科学家们提供了分享和宣传研究成果的新途径。

The result was rapid progress in astronomy, physics and other fields, and new inventions from the pendulum clock to the steam engine—the prime mover of the Industrial Revolution.
因此，天文学、物理学以及其他领域都迅速发展，同时，摆钟、蒸汽机等新发明也应运而生——蒸汽机推动了工业革命。

[Paragraph 4]
Then, starting in the late 19th century, the establishment of research laboratories, which brought together ideas, people and materials on an industrial scale, gave rise to further innovations such as artificial fertiliser, pharmaceuticals and the transistor, the building block of the computer.
然后，从 19 世纪末开始，研究实验室的建立将思想、人员和材料以工业化的规模聚集在一起，催生了更多创新，如人工肥料、药品和晶体管（计算机的组成部分）。

From the mid-20th century, computers in turn enabled new forms of science based on simulation and modelling, from the design of weapons and aircraft to more accurate weather forecasting.
从 20 世纪中叶开始，计算机反过来又带来了基于模拟和模型的新型科学，如武器和飞机设计、更准确的天气预报等等。

[Paragraph 5]
And the computer revolution may not be finished yet. AI is being employed in many ways.
计算机革命可能还没有结束。人工智能应用于许多领域。

It can identify promising candidates for analysis, such as molecules with particular properties in drug discovery, or materials with the characteristics needed in batteries or solar cells.
它可以识别出潜在的分析候选物，例如识别药物发现中具有特殊性质的分子，或识别具有电池或太阳能电池所需特性的材料。

It can sift through piles of data such as those produced by particle colliders or robotic telescopes, looking for patterns.
它可以筛选大量数据，例如粒子对撞机或机器人望远镜产生的数据，寻找其中的规律。

And AI can model and analyse even more complex systems, such as the folding of proteins and the formation of galaxies.
人工智能可以建模和分析更复杂的系统，例如蛋白质折叠和星系形成。

AI tools have been used to identify new antibiotics, reveal the Higgs boson and spot regional accents in wolves, among other things.
人工智能工具已被用来识别新的抗生素、揭示希格斯玻色子、识别狼的地方口音等。

[Paragraph 6]
All this is to be welcomed. But the journal and the laboratory went further still: they altered scientific practice itself and unlocked more powerful means of making discoveries, by allowing people and ideas to mingle in new ways and on a larger scale.
所有这些都是值得欢迎的。但期刊和实验室产生了更深远的影响：它们改变了科学实践本身，通过让人和思想以新的方式和更大的规模相互融合，解锁了更强大的科研手段。

AI, too, has the potential to set off such a transformation.
人工智能也有潜在的能力引起这样的变革。

[Paragraph 7]
Two areas in particular look promising.
有两个领域特别有前景。

The first is “literature-based discovery” (LBD), which involves analysing existing scientific literature, using ChatGPT-style language analysis, to look for new hypotheses, connections or ideas that humans may have missed.
第一个领域是“基于文献的发现”（LBD），即利用 ChatGPT 式的语言分析来分析现有的科学文献，寻找人类可能忽略的新假设、联系或观点。

LBD is showing promise in identifying new experiments to try—and even suggesting potential research collaborators.
LBD 在确定要尝试的新实验方面大有可为，甚至还能推荐潜在的研究合作者。

This could stimulate interdisciplinary work and foster innovation at the boundaries between fields.
这可以激励跨学科研究，促进各领域之间的创新。

LBD systems can also identify “blind spots” in a given field, and even predict future discoveries and who will make them.
LBD 系统还能识别特定领域的 "盲点"，甚至可以预测未来的科学成果及其发现者。

[Paragraph 8]
The second area is “robot scientists”, also known as “self-driving labs”.
第二个领域是“机器人科学家”，也称为“自动驾驶实验室”。

These are robotic systems that use AI to form new hypotheses, based on analysis of existing data and literature, and then test those hypotheses by performing hundreds or thousands of experiments, in fields including systems biology and materials science.
这些机器人系统利用人工智能，在分析现有数据和文献的基础上形成新的假设，然后进行数百次或数千次实验来测试这些假设，可应用于系统生物学和材料科学等领域。

Unlike human scientists, robots are less attached to previous results, less driven by bias—and, crucially, easy to replicate.
与人类科学家不同，机器人不那么执着于先前的结果，也不太会受到偏见的影响--而且最关键的是，它很容易复制。

They could scale up experimental research, develop unexpected theories and explore avenues that human investigators might not have considered.
机器人可以扩大实验研究的规模，发展出意想不到的理论，探索人类研究者可能未曾考虑过的途径。

[Paragraph 9]
The idea that AI might transform scientific practice is therefore feasible.
因此，人工智能可能改变科学实践的想法是可行的。

But the main barrier is sociological: it can happen only if human scientists are willing and able to use such tools.
但主要障碍在于社会学方面：只有人类科学家愿意并且能够使用这些AI工具，以上设想情况才可能发生。

Many lack skills and training; some worry about being put out of a job.
有些人缺乏技能和培训；有些人担心自己会失业。

Fortunately, there are hopeful signs. AI tools are now moving from being pushed by AI researchers to being embraced by specialists in other fields.
幸运的是，出现了一些令人振奋的迹象。由于AI研究人员的推动，现在AI工具逐渐被其他领域的专家所接受。

[Paragraph 10]
Governments and funding bodies could help by pressing for greater use of common standards to allow AI systems to exchange and interpret laboratory results and other data.
各国政府和资助机构可以通过推动使用通用标准，为AI系统之间交流和解释实验室结果和其他数据方面提供帮助。

Less fashionable forms of AI, such as model-based machine learning, may be better suited to scientific tasks such as forming hypotheses.
不太流行的AI形式（例如基于模型的机器学习）可能更适合进行形成假设等科学任务。

[Paragraph 11]
The adding of the artificial
人工添加

In 1665, during a period of rapid scientific progress, Robert Hooke, an English polymath, described the advent of new scientific instruments such as the microscope and telescope as “the adding of artificial organs to the natural”.
1665年，在科学飞速进步的时期，英国博学者罗伯特·胡克将显微镜和望远镜等新科学仪器的出现描述为“在自然界中添加了人工器官”。

They let researchers explore previously inaccessible realms and discover things in new ways, “with prodigious benefit to all sorts of useful knowledge”.
这些器具使研究人员可以探索以前无法进入的领域，以前所未有的方式发现事物，“对所有实用性知识都有巨大益处”。

For Hooke’s modern-day successors, the adding of artificial intelligence to the scientific toolkit is poised to do the same in the coming years—with similarly world-changing results.
对于胡克的现代继承者来说，将AI添加到科学工具箱中将在未来有同样的效果，并产生类似的改变世界的结果。

（恭喜读完，本篇英语词汇量1036左右）
原文出自：2023年9月16日《The Economist》Leaders版块

精读笔记来源于：自由英语之路

本文翻译整理: Irene本文编辑校对: Irene
仅供个人英语学习交流使用。

【补充资料】（来自于网络）
戴密斯·哈萨比斯（Demis Hassabis），毕业于伦敦大学学院，游戏开发者、神经学家和人工智能企业家，掌握的先进人工智能技术，帮助谷歌展开一场全新的人工智能革命。2010年，哈萨比斯和他的几位合作伙伴共同创立了DeepMind科技公司，该公司的目标是利用人工智能技术解决复杂的现实世界问题。2016年，DeepMind的AlphaGo人工智能系统成功击败了国际象棋冠军李世石，这一事件轰动全球，标志着人工智能技术实现了重大突破。

杨立昆（Yann LeCun）是一位法国的计算机科学家，也是一位在人工智能领域的领军人物。他被广泛认为是深度学习的奠基人之一，并且在计算机视觉和自然语言处理方面的研究领域贡献颇多。担任Facebook首席人工智能科学家和纽约大学教授，2018年图灵奖（Turing Award）得主。

罗伯特·胡克Robert Hooke（1635年-1703年）是一位英国科学家，也是17世纪著名的物理学家、数学家、天文学家、化学家和工程师。他是一位才华横溢的“万事通”，并且在多个领域都有杰出的贡献。他是现代微观世界的奠基人。他通过自己的实验，发现了弹性力学定律，即著名的“胡克定律”，该定律描述了弹簧的伸长程度和加力之间的关系。胡克对万有引力定律的发现起了重要作用，1679年他写信给牛顿，信中认为天体的运动是由于有中心引力拉住的结果，而且认为引力与距离平方应成反比。牛顿对此没有复信，但接受了胡克的观点。胡克希望牛顿能对他的劳动成果“提一下”，但遭到牛顿的断然拒绝。这是后来胡克控告牛顿剽窃他的成果的来由。1703年3月3日，胡克在落寞中去世了。在他死后不久，牛顿就当上了英国皇家学会的主席。随后，英国皇家学会中的胡克实验室和胡克图书馆就被解散，胡克的所有研究成果、研究资料和实验器材或被分散或被销毁，没多久，这些属于胡克的东西就全都消失了。

【重点句子】（3个）
As some observers fret about these dystopian scenarios, however, others are focusing on the potential rewards.
然而，一些人担心这些反乌托邦的场景，而另一些人关注的是潜在的回报。

And the computer revolution may not be finished yet. AI is being employed in many ways.
计算机革命可能还没有结束。人工智能应用于许多领域。

Fortunately, there are hopeful signs. AI tools are now moving from being pushed by AI researchers to being embraced by specialists in other fields.
幸运的是，出现了一些令人振奋的迹象。由于AI研究人员的推动，现在AI工具逐渐被其他领域的专家所接受。