有没有AI艺术家?

Opinion - 16 Jul 2018

Could There Ever Be an AI Artist?

If artificial intelligence were ever to achieve sentience, could it feasibly produce art? (And would it be good?)

By Mike Pepi

When is an image artificial? The answer has never been simple. When Renaissance artist, theorist and writer Leon Battista Alberti codified the linear perspective of his contemporaries, it could be seen as a sort of Quattrocento machine intelligence. Since then, our concept of what an image can reveal, and how it should depict reality, has been firmly under the Albertian spell. Under this paradigm, truth in an image is always something of a faith in measurement. In his classic essay ‘What Is an Image’, W.J.T. Mitchell scolds his predecessors for viewing the revolution of linear perspective through the lens of Scientism – the misguided notion that something like vision is an objective phenomenon that could be ‘discovered’ outside of our own experience. Linear, three-point perspective was merely a toolset that confirmed our way of seeing, a match that arrived in a ‘world already clothed in our systems of representation.’ Vision itself is a product of the tools we make, Mitchell warns, not a discovery of ‘natural’ facts outside our senses: ‘What is natural is, evidently, what we can build a machine to do for us.’

Today, the debate over what we might call art’s ‘tool problem’ has been reanimated by the rise of artificial intelligence (AI). Recent innovations in computer vision – the field that studies how computers process images ­­– and deep learning allow machines to discriminate, judge and find patterns that humans might not know exist. Much of this research was spawned by a quantum leap in AI research in which ‘artificial neural networks’ became adept at perception and categorization of images. Think of Google’s infamous ‘DeepDream’, which uses neural networks to create images seemingly on their own. AI evangelists have gone a step further and have taken to art as an earnest proving ground for their technology’s capabilities. One example is the Artists and Machine Intelligence group (AMI), started at Google in 2015, that supports artists and engineers committed to ‘new ways of thinking about and working with intelligent systems.’

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Could There Ever Be an AI Artist? - 有没有AI艺术家?

Tom White, Binoculars, 2018, risograph on paper, 30 × 30 cm. Courtesy: the artist

In a recent AMI-supported project, Tom White created ‘The Treachery of ImageNet’ (2017–ongoing), a series of semi-abstract representations of objects using what he calls ‘Perception Engines’. White fed a neural network with thousands of images that computer vision had classified as electric fans. He then programmed the system to draw a series of marks that are continually optimized towards a ‘target concept’, effectively reverse-engineering computer vision to guide automated outputs towards a representation of a fan. The prints that result are certainly fan-like, though end up looking like Kandinsky knockoffs: short black strokes punctuate globular blue forms that radiate from the centre. Instead of the artist’s hand, it is, in White’s words ‘several neural networks [that] simultaneously nudge and push a drawing toward the objective.’ The machine built the image for him, but it’s not exactly clear how.

In his essay ‘Art in the Age of Machine Intelligence’ (2017), Google AMI leader Blaise Aguera y Arcas pre-emptively addresses sceptics of the role that AI might play in the production of art. In Aguera y Arcas’s view, artists have always adopted new technical tools for expression, and AI is just the latest such advancement that will afford artists new expressive possibilities. He predicts that ‘philistine’ criticism of AI in art will one day seem as wrongheaded as the early doubters of the camera.

The end goal of artificial intelligence, however, is to not simply to aid in the execution of tasks, but to replace cognition with non-human facilities; those who study the brain caution that AI’s claim to ‘think’ are specious at best. Yet once AI claims to design, arrange, or edit for reasons unknown to the artist, it places the faculty of creativity outside of the human mind and into the machine. As White himself notes, ‘as the human artist, my main creative contribution is the design of a programming design system that allows the neural network to express itself effectively and with a distinct style. AI cannot simultaneously be both ‘just another artistic tool’ and also, as White describes, be the ‘ultimate arbiter of the content.’

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Could There Ever Be an AI Artist? - 有没有AI艺术家?

Tom White, Fan, 2018, risograph on paper, 30 × 30 cm. Courtesy: the artist

Even in the case that self-sentient AI achieves what the singularitarian fringe calls ‘general intelligence’, its production can’t be called art or creativity in any real sense. A machine can’t make art any more than a machine can understand its concept. Art, after all, is little more than institutionalized agreement among one or more subjects to call something as such. It’s the tautology that keeps on giving. Its only unifying property, then, are its human subjects. While computation can render objects by learning which measurable data correlate with things we presently refer to as art, its chief innovation is precisely the removal of the human from the critical role of the consenting subject. AI evangelists insist that AI is just another tool because the risk of the alternative is so great – that its singular claim to think might replace the very subjective apparatus through which we recognize art as such.

In the meantime, what AI evangelists call AI art will be limited to accidental offshoots of their otherwise utilitarian attempts to solve a problem of image recognition or categorization. Work by machine intelligence will only ever retroactively approximate the conventions of art decided by the very humans whose cognition they are attempting to automate. White’s ‘The Treachery of ImageNet’ is only art because its human author trained the machine to target the form of mid-century abstraction. Along the way White made hundreds of decisions to tune the outcome to his (very human) sense of what might pass for art. This leads to an awkward middle ground for aesthetics. Can we automate the production of beautiful objects whose inner workings are so innumerable that their cognitive processes are beyond the scope of human cognition? Yes, perhaps. But why? Who asked for this? Who is so eager to prove that machines, which already mediate our lives in silent and often nefarious ways, are capable of more efficiently produced art objects? The goals of such art and tech collaborations have little to do with advancing any humanist project and everything to do with humanizing the work of AI.

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Could There Ever Be an AI Artist? - 有没有AI艺术家?

Tom White, Tick, 2018, risograph on paper, 30 × 30 cm. Courtesy: the artist

Such cultural aspirations remind us of a central point: artificial intelligence needs art more than art needs artificial intelligence. Indeed, when someone says that a computer can make images, they smuggle in a much larger viewpoint about the role of machines in society. For all its utopian prognostication, the pursuit of AI boils down to a very simple business case: AI holds the promise that it can approximate the labour of a human, and if successful, perform it faster, cheaper and beyond the reach of those pesky labour laws. With human factory labour in the rear-view mirror, companies like Google, Amazon and Facebook have the automation of white collar jobs directly within their sights. But to outperform today’s fleshy writers and lawyers, AI must also prove its mastery of one of the most critical human faculties: creativity. If machine intelligence can conquer this uniquely human realm, the march to artificial general intelligence must be nigh, and the profits unimaginable.

It is no surprise that the idea of creative machines is coterminous with the ascent of platform capitalism. Art is among the last problems for which a human is still the best solution. No ruling class can exist without an appeal to the aesthetic, as almost any page from art history will show. To administer the aesthetic – to control the terms of what counts as an image, or what constitutes art – is to rule both the mind and the body, to influence the whole sensate world of human emotion and expression. For centuries, this power has sat with art and artists. For the engineer, the institution of art is both a playground and a menace. As Mitchell warned, there is much at stake in the debate over what constitutes an image. At different historical junctures, the answer will change. Given the power already held by those who build and deploy artificial intelligence, it’s not a question we should take lightly. Before we cede the making of art to machines, we should ask: cui bono?

Main image: Tom White, Cello, 2018, risograph on paper, 30 × 30 cm. Courtesy: the artist

Mike Pepi

Mike Pepi is a New York-based writer on art, culture, and technology. Find him at @mikepepi

Opinion
Mike Pepi
Artificial Intelligence
Tom White
Google

意见16 - 2018可能会有一个人工智能艺术家吗?如果人工智能曾经达到感知能力,它是否能够产生艺术?(这样会好吗?)Mike Pepi是什么时候人工塑造的?答案从来就不简单。文艺复兴时期的艺术家、理论家和作家莱昂·巴蒂斯塔·阿尔伯蒂编纂了他同时代人的线性视角,可以看作是对机器智慧的一种解读。从那时起,我们的形象可以揭示的概念,以及它应该如何描绘现实,一直坚定地在阿尔贝特法术下。在这种范式下,图像中的真理总是一种测量的信念。在他的经典散文《什么是图像》中,W.J.T. Mitchell斥责他的前任通过科学主义的视角看待线性视角的革命——误导的观念:像视觉之类的东西是一种客观现象,可以在我们自己的发明之外被发现。我知道。线性,三点透视仅仅是一个工具集,它证实了我们的观察方式,一个匹配在一个已经存在于我们的系统中的世界。“视觉本身是我们制造的工具的产物,”米切尔警告说,而不是我们感觉之外的“自然”事实的发现:“很自然的是,显然,我们可以为我们制造一台机器。”今天,关于我们所谓的“工具问题”的争论已经被人工智能(AI)的兴起所激发。计算机视觉领域最近的创新——研究计算机如何处理图像和深入学习的领域,允许机器辨别、判断和发现人类可能不知道的模式。这项研究的大部分是由AI研究中的一个量子飞跃产生的,其中“人工神经网络”擅长于对图像的感知和分类。想想谷歌臭名昭著的“深梦”,它使用神经网络来自己创造图像。AI传道者已经迈出了一步,并将艺术视为其技术能力的有力证明。一个例子是艺术家和机器智能小组(AMI),从2015开始在谷歌,支持艺术家和工程师致力于“新的思维方式和工作与智能系统。”双筒望远镜,B12YC8JPG Could There Ever Be an AI Artist? - 有没有AI艺术家?汤姆White,双筒望远镜,2018,纸上的里氏记录仪,30×30厘米。礼貌:艺术家在最近的AMI支持项目中,Tom White创建了“ImageNet的背叛”(2017正在进行),一系列使用他所谓的“感知引擎”的对象的半抽象表示。白色喂养了成千上万个图像的神经网络,计算机视觉被分类为电风扇。然后,他对系统进行编程,绘制一系列标记,这些标记不断地朝向“目标概念”优化,有效地逆向工程计算机视觉,以引导自动输出朝向风扇的表示。打印的结果肯定是扇形的,虽然最终看起来像康定斯基仿制品:短黑色笔划标点着从中心辐射的球状蓝色形式。而不是艺术家的手,在White的话中,这是“几个神经网络”同时向目标推动和推动绘画。“机器为他建造了图像,但还不完全清楚。在他的《机器智能时代的艺术》(2017)中,谷歌AMI领导人布莱斯•阿奎拉·Y·阿卡斯先发制人地提出了AI在艺术生产中可能扮演的角色的怀疑论者。在阿卡拉·阿卡斯的观点中,艺术家们总是采用新的技术工具来表达,而AI则是最新的此类进步,它将为艺术家提供新的表达可能性。他预测,在艺术中对“人工智能”的批评,总有一天会像摄影机的早期怀疑者一样固执。然而,人工智能的最终目标不是简单地帮助执行任务,而是用非人类设施取代认知;那些研究大脑的警告,即AI声称“思考”的想法是最好的。然而,一旦人工智能要求设计、安排或编辑艺术家未知的原因,它将创造力的能力置于人类思维之外,进入机器。正如White自己所说,“作为人类艺术家,我的主要创造性贡献是设计一个程序设计系统,它允许神经网络有效地表达自己,并具有独特的风格。AI不能同时成为“另一种艺术工具”,而且,正如怀特所描述的,是“内容的最终仲裁者”。FANOFLAST。JPG Could There Ever Be an AI Artist? - 有没有AI艺术家? Tom White,范,2018,纸上的里斯图,30×30厘米。礼貌:艺术家即使在自我意识的人工智能达到了奇异主义边缘称为“一般智力”的情况下,它的生产在任何意义上都不能被称为艺术或创造力。机器不能制造艺术,正如机器不能理解它的概念一样。毕竟,艺术不过是一个或多个主体之间的制度化协议,而不是这样称呼。这是不断重复的重言式。它唯一的统一属性是它的人类主体。虽然计算可以通过学习哪些可测量的数据与我们目前称为艺术的事物相关,但它的主要创新正是将人类从同意主体的关键角色中移除。人工智能传教士坚持认为人工智能只是另一种工具,因为另一种选择的风险是如此之大,以至于其独特的思维主张可能取代我们认识艺术的主观工具。同时,AI福音派人士把人工智能艺术称为AI艺术,将其局限于解决图像识别或分类问题的其他功利主义尝试中的偶然分支。机器智能的工作只会追溯到由那些试图自动实现的人类所决定的艺术惯例。怀特的《意象派》的背叛只是艺术,因为它的人类作者把机器训练成以中世纪抽象的形式为目标。一路上,White作出了数百个决定,以调整结果,他(非常人类)的感觉可能会通过艺术。这给美学带来了尴尬的中间立场。我们能自动生产美丽的物体,它们的内部工作是如此之多以至于它们的认知过程超出了人类认知的范围吗?是的,也许。但是为什么呢?谁要求这个?谁是如此渴望证明机器,它已经在沉默和经常邪恶的方式调解我们的生活,能够更有效地生产艺术对象?这样的艺术和技术合作的目标与推进任何人文项目和与AI的人性化有关的一切都没有什么关系。TIKKROCROP1010JPG WPAP6023 602IMG Tom White,蜱,2018,纸上的里氏记录仪,30×30厘米。礼貌:艺术家的这种文化诉求提醒我们一个中心点:人工智能需要艺术,而不仅仅是艺术需要人工智能。事实上,当有人说计算机可以制造图像时,他们会从一个更大的角度来看机器在社会中的作用。尽管所有的乌托邦式的预言,对人工智能的追求都归结为一个非常简单的商业案例:人工智能持有的承诺是它可以近似人类的劳动,如果成功的话,它运行得更快、更便宜,而且超出了那些令人讨厌的劳动法的范围。在后视镜中使用人力工厂,谷歌、亚马逊和脸谱网等公司在他们的视线范围内实现了白领工作的自动化。但是,为了超越今天富有的作家和律师,人工智能也必须证明它掌握了最关键的人类能力之一:创造力。如果机器智能能够征服这个独特的人类领域,就必须接近人造的一般智能,而利润是不可想象的。毫不奇怪,创意机器的理念与平台资本主义的崛起是相辅相成的。艺术是最后一个问题,人类仍然是最好的解决办法。没有一个统治阶级可以不受审美的影响,因为几乎任何一页艺术史都会显示出来。管理美学——控制什么是一个形象,或什么构成艺术——是统治思想和身体,影响整个人类情感和表达的感觉世界。几个世纪以来,这种力量一直伴随着艺术和艺术家。对于工程师来说,艺术机构既是一个运动场,又是一个威胁。正如米切尔所警告的,在什么构成一个形象的辩论中,有很多问题。在不同的历史关头,答案会改变。考虑到那些建造和部署人工智能的人所拥有的力量,这不是我们应该掉以轻心的问题。在我们把艺术制作成机器之前,我们应该问:崔博诺?主要图像:Tom White,大提琴,2018,纸上的里氏记录仪,30×30厘米。礼貌:艺术家迈克佩皮迈克佩皮是一个纽约的作家在艺术,文化和技术。在MikpPei上找到他Mike Pepi人工智能Tom White谷歌

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