剑桥雅思13Test1Passage3阅读原文翻译 Artificial artists 人工智能艺术家
剑桥雅思13Test1Passage3阅读答案解析 Artificial artists 人工智能艺术家
雅思真题阅读词汇 剑桥雅思13 Test 1 Passage 3 人工智能是否可以进行艺术创作
剑桥雅思13 Test1 Passage3阅读原文翻译
The Painting Fool is one of a growing number of computer programs which, so their makers claim, possess creative talents. Classical music by an artificial composer has had audiences enraptured, and even tricked them into believing a human was behind the score. Artworks painted by a robot have sold for thousands of dollars and been hung in prestigious galleries. And software has been built which creates art that could not have been imagined by the programmer.
Human beings are the only species to perform sophisticated creative acts regularly. If we can break this process down into computer code, where does that leave human creativity? ‘This is a question at the very core of humanity,’ says Geraint Wiggins, a computational creativity researcher at Goldsmiths, University of London. ‘It scares a lot of people. They are worried that it is taking something special away from what it means to be human.’
To some extent, we are all familiar with computerised art. The question is: where does the work of the artist stop and the creativity of the computer begin? Consider one of the oldest machine artists, Aaron, a robot that has had paintings exhibited in London’s Tate Modern and the San Francisco Museum of Modern Art. Aaron can pick up a paintbrush and paint on canvas on its own. Impressive perhaps, but it is still little more than a tool to realise the programmer’s own creative ideas.
Simon Colton, the designer of the Painting Fool, is keen to make sure his creation doesn’t attract the same criticism. Unlike earlier ‘artists’ such as Aaron, the Painting Fool only needs minimal direction and can come up with its own concepts by going online for material. The software runs its own web searches and trawls through social media sites. It is now beginning to display a kind of imagination too, creating pictures from scratch. One of its original works is a series of fuzzy landscapes, depicting trees and sky. While some might say they have a mechanical look, Colton argues that such reactions arise from people’s double standards towards software-produced and human-produced art. After all, he says, consider that the Painting Fool painted the landscapes without referring to a photo. ‘If a child painted a new scene from its head, you’d say it has a certain level of imagination,’ he points out. ‘The same should be true of a machine.’ Software bugs can also lead to unexpected results. Some of the Painting Fool’s paintings of a chair came out in black and white, thanks to a technical glitch. This gives the work an eerie, ghostlike quality. Human artists like the renowned Ellsworth Kelly are lauded for limiting their colour palette – so why should computers be any different?
“绘画愚人”的设计者Simon Colton渴望确保他的作品不会引来同样的批评。不像诸如Aaron这样的早期艺术家，“绘画愚人”只需要极少的指示，并且能够通过在互联网上寻找材料提出其自己的想法。该软件运行自己的网络搜索功能，浏览社交媒体的各个页面。它现在也开始展示出某种想象力，从零创作图片。其原创作品之一是一系列描绘树木和天空的朦胧风景画。虽然一些人可能会说它们看起来有些机械，但Colton认为这种反应源自人们对于软件创作和人类创作的艺术品的双重标准。毕竟，他说，要考虑到“绘画愚人”在描绘风景的时候并没有参考照片。“如果一个孩子从自己的头脑中描绘出一副崭新的景象，你会说它有一定程度的想象力”，他指出。”同样的标准也应该适用于机器“。软件错误也能造成一些出乎意料的结果。由于技术故障，一些“绘画愚人”的作品将椅子画成了黑白色。这赋予画作一种怪诞、诡异的感觉。诸如Ellsworth Kelly这样著名的人类艺术家就因为尽量少的使用颜色而受到传颂-所以为什么计算机就应该有所不同呢？
Researchers like Colton don’t believe it is right to measure machine creativity directly to that of humans who ‘have had millennia to develop our skills’. Others, though, are fascinated by the prospect that a computer might create something as original and subtle as our best artists. So far, only one has come close. Composer David Cope invented a program called Experiments in Musical Intelligence, or EMI. Not only did EMI create compositions in Cope’s style, but also that of the most revered classical composers, including Bach, Chopin and Mozart. Audiences were moved to tears, and EMI even fooled classical music experts into thinking they were hearing genuine Bach. Not everyone was impressed however. Some, such as Wiggins, have blasted Cope’s work as pseudoscience, and condemned him for his deliberately vague explanation of how the software worked. Meanwhile, Douglas Hofstadter of Indiana University said EMI created replicas which still rely completely on the original artist’s creative impulses. When audiences found out the truth they were often outraged with Cope, and one music lover even tried to punch him. Amid such controversy, Cope destroyed EMI’s vital databases.
像Colton这样的研究者认为，将机器的创造力直接与人类相比并不正确，因为人类已经用了上千年来提升我们的技巧。然而，另一些人则痴迷于这样的前景，即计算机可能创造出与我们最好的艺术家同样富有创造力、同样巧妙的作品。到目前为止，只有一位接近这一目标。作曲家David Cope发明了一个叫做“音乐智能实验”的程序，简称为EMI。EMI不仅可以创作Cope风格的乐曲，而且还能模仿最受尊崇的古典音乐作曲家的作品，包括巴赫、肖邦和莫扎特。观众被感动至流泪。EMI甚至让古典音乐专家误以为他们听到的是真正的巴赫作品。然而，并非每个人都为此惊叹。一些人，比如Wiggins，就猛烈抨击Cope的作品是伪科学，并谴责他对于该软件的工作方式故意含糊其辞。与此同时，印第安纳大学的Douglas Hofstadter认为，EMI所创作的仿制品仍然完全依赖于原本艺术家的创作冲动。当听众发现真相时，他们经常会对Cope感到异常地愤怒。一名音乐爱好者甚至想要揍他。在这些争议之中，Cope销毁了EMI至关重要的数据库。
But why did so many people love the music, yet recoil when they discovered how it was composed? A study by computer scientist David Moffat of Glasgow Caledonian University provides a clue. He asked both expert musicians and non-experts to assess six compositions. The participants weren’t told beforehand whether the tunes were composed by humans or computers, but were asked to guess, and then rate how much they liked each one. People who thought the composer was a computer tended to dislike the piece more than those who believed it was human. This was true even among the experts, who might have been expected to be more objective in their analyses.
Where does this prejudice come from? Paul Bloom of Yale University has a suggestion: he reckons part of the pleasure we get from art stems from the creative process behind the work. This can give it an ‘irresistible essence’, says Bloom. Meanwhile, experiments by Justin Kruger of New York University have shown that people’s enjoyment of an artwork increases if they think more time and effort was needed to create it. Similarly, Colton thinks that when people experience art, they wonder what the artist might have been thinking or what the artist is trying to tell them. It seems obvious, therefore, that with computers producing art, this speculation is cut short – there’s nothing to explore. But as technology becomes increasingly complex, finding those greater depths in computer art could become possible. This is precisely why Colton asks the Painting Fool to tap into online social networks for its inspiration: hopefully this way it will choose themes that will already be meaningful to us.
这种偏见来自何处呢？耶鲁大学的Paul Bloom提出如下见解：他认为我们从艺术中获得的部分乐趣来源于其背后的创作过程。这能够赋予它一种“无法抗拒的本质”，Bloom说。与此同时，纽约大学Justin Kruger所进行的实验表明，如果人们认为创作一件艺术品所需要的时间和努力更多，那么他们就会更加欣赏它。相似的，Colton认为当人们体验艺术时，他们会好奇艺术家当时在想什么，或者尝试告诉他们什么。因此，原因似乎很明显，如果是计算机所创作的艺术，这一推测过程被缩短了-没有什么东西可供探索。但随着技术变得越来越复杂，在计算机艺术品中探索更为深入的内涵也许会成为可能。这也正是Colton让“绘画愚人”搜索社交媒体以获取灵感的原因：希望通过这种方式，它可以选择那些对我们来说已经具有意义的主题。
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