人工智能开始写歌了，不过人类无需惊慌

“这是作弊。”标榜纯粹主义的音乐人谈及歌曲创作中的技术创新时，一定会给出这样的答案。他们对采样器、合成器、电子鼓、自动调音都表示不屑，认为这些不过是制作排行榜热门歌曲的捷径，却抹去了人的元素。[向香草冰（Vanilla Ice）、盖瑞·纽曼、Prince、提潘（T-Pain）致歉。]

人工智能写歌将是下一个引起粉丝和音乐人争议的话题。若干预测均得出结论，未来十年的40佳歌曲中，将有20%-30%是部分或完全由机器学习软件写的。如今录音师可以用AI程序进行各类编曲（无论是进行完整的管弦乐编排还是加入嘻哈节拍），然后根据情绪、节奏、题材加以调整（从重金属到蓝草音乐）。

“人工智能写歌的前景和自动驾驶汽车类似。”创业家、Creative Labs的联合创始人莱昂纳多·布洛迪说，Creative Labs是和Creative Artists Agency共同创建的合资企业，主营业务是向帮助音频创作者把作品呈现给公众的项目进行投资。“第一级是艺术家使用机器作为辅助。第二级是机器编写音乐，人来演奏。第三级是自始自终都由机器完成。”

前40名单曲中将有1/3将由人工智能编写，这个数字可能会让普通听众大吃一惊，但Amper公司的CEO德鲁·西尔弗斯坦却觉得这个数字并不高。Amper是纽约一家人工智能作曲软件公司，音乐人可以使用该公司的软件创作或下载stems并进行再创作，所谓stems是一段有特色的音轨，比如一节用吉他即兴演奏的重复乐段或脚踏钹音轨。西尔弗斯坦认为预测工具不过是音乐创作发展过程中的一种进化。“从多年前的羽毛笔和羊皮纸发展到后来的模拟信号、磁带和移动设备，人工智能不过是下一步。”他说。

西尔弗斯坦并非唯一的一个持这种观点的人。大型科技公司也推出了以AI为基础的音乐创作工具和服务，包括IBM的Watson Beat、谷歌Magenta项目的NSynth、索尼的Flow Machines、Spotify的Creator Technology Research Lab等。这些产品服务的目标客户是艺术家和唱片公司，它们利用算法对歌曲库和销售排行榜加以分析，预测哪些歌曲（在什么时候）最有可能上榜。

尽管人工智能的最新发展大大提升了它在流行音乐中的应用，但这并不是个新生想法。早在20多年前，大卫·鲍伊就帮人创作了苹果电脑程序Verbasizer，通过把预录的鲍伊作品进行随机重组，创作出富有新意义和新情绪的新句子；这是他曾经用过的一种拼贴技术的高级版本——先将想法写下来，再进行物理切割和重排，从中选取最震撼的版本。鲍伊在1995年的《Outside》专辑中使用了Verbasizer，“你最后得到的是一个真正包含了不同意义、不同话题、各种名词动词彼此猛烈撞击的文本。”这位引领时代的潮流巨星1997年在介绍Verbasizer的一个纪录片中说。

持相近看法的艺术家认为人工智能辅助写歌是福利而非威胁。歌手、美国偶像参赛选手塔瑞安·萨顿去年发行了首张专辑《I Am AI》，专辑中八首歌的编写都是用Amper、Watson Beat以及其它软件辅以人工制作完成的。

“如果一个人从8岁开始学吉他，那他能达到精通。”萨顿说。“他们需要一小时能做出一首歌。不具备这种技能的人可能得花几个星期。”人们在合成器和采样器之争中也有类似的顾虑，“并不是要让谁失业，只是改变了大家的工作方式。”她说。

制作人、作曲家、黑眼豆豆成员Will.i.am有不同的看法：人工智能创造的音乐里毫无人工可言。“你说‘人工智能’编曲的时候，它的哪一部分在帮助这些有创意的作曲家？人工智能是帮你写曲了么？还是帮你发行？谁在听？它能挣多少钱？别逗了，哥们，这就是个新的机器学习工具”——仅此而已。

对于艺术家和他们的公司而言，无论是制作经费还是版权、版税，钱永远是个重要问题。比如说，萨伦专辑里的歌是她用Amper写的。得益于Amper，原本要支付给作曲人、乐手、工作室租金的费用可以付给管理团队、宣传人员和摄像团队，这些也是现代专业化娱乐产业的关键组成部分。

或者像Will.i.am说的那样：“想想迈克尔·杰克逊、昆西·琼斯、卢瑟·范德鲁斯，想想这些伟大的作曲家。麦克风、工程师、磁带都要花钱。”换言之，人工智能无法复制这些作曲家的才华，更无法复制他们在创作这些传世之作时历经的复杂录制过程。

所以别指望人工智能短期内能写出第二首《太空怪人》（Space Oddity）。但借助人工智能，有才华有技巧的艺术家可以早日实现成功，虽然地球上再也不会有第二个大卫·鲍伊了——路德派和未来主义一定同意这种说法。（财富中文网）

原文发表于2018年11月1日刊的《财富》杂志。

译者：Agatha

“IT’S CHEATING.” That’s the response you’ll hear from self-proclaimed music purists talking about technological innovation in song creation. Sampling, synthesizers, drum machines, Auto-Tune—all have been derided as lazy ways to make chart-topping hits because they take away the human element. (With apologies to Vanilla Ice, Gary Numan, Prince, and T-Pain.)

The new argument among fans and musicians will be about the use of artificial intelligence in songwriting. According to several estimates, in the next decade, between 20% and 30% of the top 40 singles will be written partially or totally with machine-learning software. Today, recording pros can use A.I.-powered programs to cue an array of instrumentation (from full orchestral arrangements to hip-hop beats), then alter it by mood, tempo, or genre (from heavy metal to bluegrass). (See more ways A.I. is changing how people work on page 96.)

“It’s like the future of self-driving cars,” says Leonard Brody, entrepreneur and cofounder of Creative Labs, a joint venture with Creative Artists Agency that invests in programs to help audio creators get their works delivered to the public. “Level 1 is an artist using a machine to assist them. Level 2 is where the music is crafted by a machine but performed by a human. Level 3 is where the whole thing is machines.”

A.I. claiming ownership of a third of the top 40 may be surprising to the casual listener, but it’s a low bar for Drew Silverstein, CEO of Amper, an A.I.-based music composition software company in New York City. Amper’s product allows musicians to create and download “stems”—unique portions of a track like a guitar riff or a hi-hat cymbal pattern—and rework them. Silverstein sees predictive tools as an evolution in the process of music creation. “Starting from quill and parchment centuries ago, then moving into analog and tape and mobile [devices]—A.I. is really just the next step,” he says.

Silverstein isn’t the only one with that view. Large technology companies also offer A.I.- powered tools and services for music-making. Among them: IBM Watson Beat, Google Magenta’s NSynth, Sony’s Flow Machines, and Spotify’s Creator Technology Research Lab. The resources, intended for use by artists and labels, use algorithms to analyze libraries of songs and sales charts to predict what may have the best chance of charting (and when).

Though the latest developments in A.I. are helping fuel its use in popular music, it’s not really a new idea. More than two decades ago, David Bowie helped create the Verbasizer, a program for Apple’s Mac that randomized portions of his inputted text sentences to create new ones with new meanings and moods—an advanced version of a cut-up technique he used, writing out ideas, then physically slicing and rearranging them to see what stuck. Bowie made use of the Verbasizer for his 1995 album Outside. “What you end up with is a real kaleidoscope of meanings and topic and nouns and verbs all sort of slamming into each other,” said the influential pop star in a 1997 documentary featuring the tool.

Like-minded artists insist A.I.-assisted songwriting is a boon, not a threat. Taryn Southern, a singer and former American Idol contestant who released her debut album, I Am AI, last year, composed the eight-song work with Amper, Watson Beat, and other software, plus human help.

“A person who’s been trained on guitar since they were 8 years old is going to be masterful,” says Southern. “It would take them an hour to bang out a song. For people who don’t have that skill set, it could take weeks.” As with arguments against synths and samples, “It’s not putting anyone out of work, just making them work differently,” she says.

Producer, songwriter, and Black Eyed Peas member Will.i.am has another take: There’s nothing artificial about music created by A.I. “When you say ‘artificial intelligence’ to compose music, what part of it is helping creative songwriters? Is the A.I. helping you compose? Distribute? Who’s listening? How much money will it make? No, bro. That’s a new machine-learning tool”—and nothing more.

For artists and their reps, money—for everything from production costs to copyright and royalties—is a key issue. Southern, for example, shares writing credits on her album with Amper. But the software allowed her to use funds that would have been conventionally spent on human songwriters, session musicians, and studio time for a management team, publicists, and videographers—other essential components for the modern professional entertainer.

Or, as Will.i.am puts it: “Michael Jackson, Quincy Jones, Luther Vandross—think about all of those composers. Microphones, engineers, and tape cost money.” In other words, A.I. can’t replicate the innate talent of those songwriters, let alone the complicated recording processes they used to create their bes-known works.

So don’t expect artificial intelligence to write the next “Space Oddity” anytime soon. But an artist with the right chops and ingenuity might get there faster with A.I.—even if, as Luddites and futurists surely agree, this universe will never see another David Bowie.

This article originally appeared in the November 1, 2018 issue of Fortune.