Robot evolution

Robot evolution
Hod Lipson’s artificial organisms have already escaped from the virtual realm. Now he wants to
send them out of control
by Emily Monosson 2,500 words
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A quadrupedal robot used to help evolve gaits. Courtesy Cornell Creative Machines Lab
In a laboratory tucked away in a corner of the Cornell University campus, Hod Lipson‘s robots are evolving. He has already produc ed a self-aware robot that is able to gather information about itself as it
learns to walk. Like a Toy Story character, it sits in a cubby surrounded by other former laboratory stars. There‘s a set of modular cubes, looking like a cross between children‘s blocks and the model cartilage one might see at the orthopaedist‘s – this particular contraption enjoyed the spotlight in 2005 as one of the world‘s first self-replicating robots. And there are cubbies full of odd-shaped plastic sculptures, including some chess pieces that are products of the lab‘s 3D printer.
In 2006, Lipson‘s Creative Machines Lab pioneered the Fab@home, a low-cost build-your-own 3D printer, available to anyone with internet access. For around $2,500 and some tech know-how, you could make a desktop machine and begin printing three-dimensional objects: an iPod case made of silicon, flowers from icing, a dolls‘ house out of spray-cheese. Within a year, the Fab@home site had received 17 million hits and won a 2007 Breakthrough of the Year award from Popular Mechanics. But really, the printer was just a side project: it was a way to fabricate all the bits necessary for robotic self-replication. The robots and the 3D printer-pieces populating the cubbies are like fossils tracing the evolutionary history of a new kind of organism. ‗I want to evolve something that is life,‘ Lipson told me, ‗out of plastic and wires and inanimate materials.‘
Upon first meeting, Lipson comes off like a cross between Seth Rogen and Gene Wilder‘s Young Frankenstein (minus the wild blond hair). He exudes a youthful kind of curiosity. You can‘t miss his passionate desire to understand what makes life tick. And yet, as he seeks to create a self-assembling, self-aware machine that can walk right out of his laboratory, Lipson is aware of the risks. In the corner of his office is a box of new copies of Out of Control by
Kevin Kelly. First published in 1994 when Kelly was executive editor of Wired magazine, the book contemplates the seemingly imminent merging of the biological and technological realms —‗the born and the made‘ — and the inevitable unpredictability of such an event. ‗When someone wants to do a PhD in this lab, I give them
this book before they commit,‘ Lipson told me. ‗As much as we are control freaks when it comes to engineering, where this is going toward is loss of control. The more we automate, the more we don‘t know what‘s going to come out of it.‘
Lipson‘s first foray into writing evolvable algorithms for building robots came in 1998, when he was working with Jordan Pollack, professor of computer science at Brandeis University in Massachusetts. As Lipson explained:
We wrote a trivial 10-line algorithm, ran it on big gaming simulator which could put these parts together and test them, put it in a big computer and waited a week. In the beginning nothing happened.
We got piles of junk. Then we got beautiful machines. Crazy shapes. Eventually a motor connected to a wire, which caused the motor to vibrate. Then a vibrating piece of junk moved infinitely better than any other… eventually we got machines that crawl. The evolutionary algorithm came up with a design, blueprints that worked for the robot.
The computer-bound creature transferred from the virtual domain to our world by way of a 3D printer. And then it took its first steps. The story splashed across several dozen publications, from The New York Times to Time magazine. In November 2000,Scientific American ran the headline ‗Dawn of a New Species?‘ Was this arrangement of rods and wires the machine-world‘s equi valent of the primordial cell? Not quite: Lipson‘s robot still couldn‘t operate without human intervention. ‗We had to snap in the battery,‘ he told me, ‗but it was the first time evolution produced physical robots. It was almost
apocalyptic. Eventually, I want to print the wires, the batteries, everything. Then evolution will have so much freedom. Evolution will not be constrained.‘
In the late 1940s, about five decades before Lipson‘s first computer-evolved robot, physicists, math geniuses and pioneering computer scientists at the Institute for Advanced Study at Princeton University were putting the finishing touches to one of the world‘s first universal digital computing machines — the MANIAC
(‗Mathematical Analyzer, Numerical Integrator, and Computer‘). The acronym was apt: one of the computer‘s first tasks in 1952 was to advance the human potential for wild destruction by helping to develop the hydrogen bomb. But within that same machine, sharing run-time with calculations for annihilation, a new sort of numeric organism was taking shape. Like flu viruses, they multiplied, mutated, competed and entered into parasitic relationships. And they evolved, in seconds.
These so-called symbioorganisms, self-reproducing entities represented in binary code, were the brainchild of the Norwegian-Italian virologist Nils Barricelli. He wanted to observe evolution in action and, in those pre-genomic days, MANIAC provided a rare opportunity to test and observe the evolutionary process. As the American historian of technology George Dyson writes in his
book Turing’s Cathedral (2012), the new computer was effectively assigned two problems: ‗how to destroy life as we know it, and how to create life of unknown forms‘. Barricelli ‗had to squeeze his numerical universe into exist ence between bomb calculations‘, working in the wee hours of the night to capture the evolutionary history of his numeric organisms on stacks of punch cards.
Lipson, however, maintains that some of his
robots are alive in a rudimentary sense. ‘There is
not hing more black or white than alive or dead’
Just like DNA, Barricelli‘s code could mutate. But he had some unusual ideas about how evolution worked. In addition to single-point mutations, he believed that evolution leapt forward through symbiotic and parasitic relationships between virus-like entities —otherwise it just wouldn‘t be fast enough. Maybe, he thought, cells themselves first arose when virus-like creatures started slotting together, like Lego pieces. ‗According to the symbiogenesis theory,‘ Bar ricelli wrote, ‗the evolution process which led to the formation of the cell was initiated by a symbiotic association between several virus-like organisms.‘
So far, this doesn‘t appear to be the way things happened; in fact, some researchers believe that viruses first emerged after cells. But a few of Barricelli‘s findings were not too far off the mark. Once he had ‗inoculated‘ MANIAC, it was minutes before the digital universe filled with numerical organisms that reproduced, had numerical sex, repaired ‗genetic‘ damage and parasitised one another. When the population lacked environmental challenges or selection pressures, it stagnated. In other cases, a highly successful parasite would cause widespread devastation. These patterns of behaviour are typical of living things, from the simplest cells right up to human beings.
The overall shape of his simulation matched life quite well, and is particularly reminiscent of viruses. Viruses are indeed parasitic: they are symbionts, which means that they need to take over the living cells of other organisms to reproduce; taken by themselves, they aren‘t much more than simple DNA or RNA mechanisms
surrounded by a coat of protein. And like all living things, viruses inevitably mutate during replication. But they also engage in some genetic give and take. As they weave in and out of host cells, they might steal host genes or leave their own genes behind (by some estimates, eight per cent of our human genome comes to us by way of viruses). Some even swap gene segments with other viruses, and that speeds things up quite a bit.
When an influenza virus evolves through simple mutation and selection, we call that antigenic drift. Each fall, those of us who submit to annual flu vaccines do so in large part because of drift. But every once in a while, an influenza A virus makes an evolutionary leap — swapping a large genome segment with a very different strain and undergoing what is called an antigenic shift. The flu viruses we fear the most — the novel, pandemic strains — are often the products of such shifts. The newly emergent H7N9 avian flu virus is believed to have undergone an antigenic shift, enabling it to infect humans; to date, it has infected 132 and killed 39 in China. To pick a more explosive example, the Asian flu outbreak of 1957, another product of antigenic shift, wiped out between one and four million people worldwide. Evolvable computer programs also swap code as they engage in genderless algorithmic sex. As with viruses, the ability to make these exchanges boosts a program‘s evolvability.
And yet, as close to the real thing as Barricelli‘s digital organisms came, they were just numeric code: they had a genotype but no phenotype, no bodily characteristics for evolution to sift through. Life on Earth is about tools that solve problems — a beak capable of cracking a tough nut, the ability to digest milk, a robotic leg that can take a step in the right direction. Natural selection acts on the hardware; the software, be it DNA or numeric code, just keeps score.
Barricelli‘s creatures might have behaved like living organisms, but they never escaped the computer. They never got the chance to take on the outside world.
N ot many people would call creatures bred of plastic, wires and metal beautiful. Yet to see them toddle deliberately across the laboratory floor, or bend and snap (think Legally Blonde) as they pick up blocks and build replicas of themselves, brings to my biologist mind the beauty of evolution and animated life. Most striking are the pulsating ‗soft robots‘ deve loped by a team of students and collaborators. Though they have yet to escape the confines of the computer, you can watch in real time as an animated Rubik‘s Cube of ‗muscle‘, ‗bone‘ and ‗soft tissue‘ evolves legs and trots exuberantly across the screen.
The more like us our machines become, the more dangerous and unnerving they seem
One could imagine Lipson‘s electronic menagerie lining the shelves at Toys R Us, if not the CIA, but they have a deeper purpose. Like Barricelli, Lipson hopes to illuminate evolution itself. Just recently, his team provided some insight into modularity — the curious phenomenon whereby biological systems are composed of discrete functional units, such that, for example, mammalian brain networks are compartmentalised. This characteristic is known to enable rapid adaptation in DNA-based life. ‗We figured out what was the
evolutionary pressure that causes things to become modular,‘ Lipson told me. ‗It‘s very difficult to verify in biology. Biologists often say: ―We don‘t believe this computer stuff. Unless you can prove it with real biological stuff, it‘s just castles in the air‖.‘
Though inherently newsworthy, the fruits of the Creative Machines Lab are just small steps along the road towards new life. Barricelli always skirted the question of whether his own organisms were alive, insisting that they could not be defined as one thing or the other until there was a ‗clear-cut‘ definition of life. Lipson, however, maintains that some of his robots are alive in a rudimentary sense. ‗Ther e is nothing more black or white than alive or dead,‘ he said, ‗but beneath the surface it‘s not simple. There is a lot of grey area in between.‘
How you define life depends on whom you read, but there is a scientific consensus on a few basic criteria. Living things engage in metabolic activity. They are self-contained, in the sense that they can keep their own genetic material separate from their neighbours‘. They reproduce. They have a capacity to adapt or evolve. Their characteristics are specified in code and that code is heritable. The robots of the Creative Machines Lab might fulfil many criteria for life, but they are not completely autonomous — not yet. They still require human handouts for replication and power. These, though, are just stumbling blocks, conditions that could be resolved some day soon — perhaps by way of a 3D printer, a ready supply of raw materials, and a human hand to flip the switch just the once. Then it will be up to the philosophers to determine whether or not to grant robots birth certificates.
I‘ve been relating some of these developments to friends, and once they get over the ‗cool‘ factor, they tend to become distressed. ‗Why would anyone want to do that?‘ they ask. We have no real experience with new life forms, particularly of the cyber type, though they abound in books and on screen. Consider Arthur C Clarke‘s murderous computer HAL, or Battlestar Galactica‘s Cylon babes gone wild — computers built to serve, which evolved to destroy their creators. The more like us our machines become, the more dangerous and unnerving they seem.
But perhaps it is not the creation of new life that we fear, so much as the potential for unpredictable emergent behaviour. Evolution certainly offers that. Take viruses: like Lipson‘s machines, these organisms exist in the grey area between life and non-life, yet they are among the most rapidly evolving entities on the planet. They are also some of the most destructive; the Spanish Flu of 1918 killed around 50 million people, and some scientists fear that the emergence of some kind of Armageddon virus is only a matter of time. From this point of view, it doesn‘t matter whether viruses are alive or dead. All that matters is that they are highly evolvable and unpredictable.
And here‘s where things do get scary. If viruses can evolve within hours, computer code can do it within fractions of a second. Viruses are dumb; computers have processors that might some day surpass our own brains — some would say they already have. If we are going to take the risk of giving machines, in Lipson‘s words, ‗so much freedom‘, we need a good reason to do it. In Out of Control, Kelly proposes one possible reason. Perhaps, he says, the world has become such a complicated place that we have no other choice but to enable the marriage between the biologic and the technologic;
without it, the problems we face are too difficult for our human brains to solve. Kelly proposes a kind of Faustian pact: ‗The world of the made, will soon be like the world of the born: autonomous, adaptable and creative but, consequently, out of our control. I think that‘s a great bargain.‘
According to Lipson, an evolvable system is ‗the ultimate artificial intelligence, the most hands-off AI there is, which means a double edge. It‘s powerful. All you feed it is power and computing power. It‘s both scary and promising.‘ More than 60 years ago, MANIAC was created to ‗solve the unsolvable‘. What if the solution to some of our present problems requires the evolution of artificial intelligence beyond anything we can design ourselves? Could an evolvable program help to predict the emergence of new flu viruses? Or the effects of climate change? Could it create more efficient machines? And once a truly autonomous, evolvable robot emerges, how long before its descendants (assuming they think favourably of us) make a pilgrimage to Lipson‘s lab, where their ancestor first emerged from a primordial soup of wires and plastic to take its first steps on Earth?
11 June 2013
Read more essays on evolution, science and technology
Emily Monosson is an environmental toxicologist at the University of Massachusetts Amherst and the author of Evolution in a Toxic World.
【万古杂志】机器人的进化
译者：SCWalter原文作者：Emily Monosson
用来帮助发展步态的四足机器人。

康奈尔大学创意机器实验室赠隐秘在康奈尔大学校园一角的一间实验室里，胡迪·利普森的机器人正在进化。

胡迪·利普森已经造出了一台拥有自我意识的机器人，它能够在学习走路的过程中收集自己周围的信息。

这个机器人就像《玩具总动员》中的一个角色，坐在一间小屋子里，周围是实验室以前的明星成员。

其中有一组模块化的立方体，看起来像是儿童积木与人们在骨科医生那里看到的骨骼模型的组合体，这个特殊的玩意儿在2005年受到了公众的关注，它成了世界上第一批自我复制机器人中的一员。

其他房间里满是造型奇特的塑料雕刻品，包括一些国际象棋的棋子，那是实验室的3D打印机打印出来的。

2006年，利普森的创意机器实验室率先开发了Fab@Home。

这是一台低成本的自主3D打印机，任何人都可以联网买到（译者：这个项目已经转移到NextFabStore。

）。

花个大概2500美元，再加上一些技术窍门，你就可以做出一台桌上机器并开始打印三维物体，比如：硅做的iPod壳子、冰做的花、喷雾奶酪做的洋娃娃的房子。

一年之内，Fab@home的网站就获得了17万的点击率，并荣获《大众机械》2007年年度突破奖。

不过说真的，这台打印机只是一个附带项目：它是制作机器人自我复制所必需的所有部件的一种方法。

堆满屋子的机器人和3D打印机零件就像是用来追溯新物种进化史的化石。

“我想要进化出一些有生命的东西，”利普森告诉我，“用的是塑料、电线和没有生命的材料。

”
初次见面，利普森在我看来就像是塞斯·罗根与吉恩·怀尔德扮演的新科学怪人的混合体（除了没有乱蓬蓬的金发）。

他散发着一种年轻人的好奇。

你无法忽视他对于想要理解是什么赋予了生命活力的强烈愿望。

他试图创造出一台能自我组装、有自我意识、可以径直走出他实验室的机器，然而同时，利普森也知道其中的风险。

在他办公室的一角，有一箱崭新的书，那是凯文·凯利《失控》。

这本书首发于1994年，凯利那时是《连线》杂志的执行编辑。

这本书深入思考了即将出现的生物领域与技术领域——“天生和人造”——的融合，同时思考了这一事件必将带来的不可预测性。

“每当有人想加入这个实验室攻读博士学位的时候，我都会在他们下定决心之前给他们这本书，”利普森告诉我。

“在工程领域，我们都有十足的控制欲，但现在的发展是在走向失控。

我们越是自动化，就越不知道自动化后会发生什么事情。

“
利普森首次尝试为建造机器人而编写可进化算法（译者：即遗传算法。

）是在1998年，那时他正与马萨诸塞州布兰迪斯大学的计算机教授乔丹·波拉克共事。

利普森解释说：
我们写了一个10行的简单算法，先放在一个大的游戏模拟器上运行，这台模拟器可以把这些部件放到一起并对其进行测试。

然后我们把它放进一台大型计算机，等上一个星期。

一开始的时候什么都没有发生，我们得到了一堆堆垃圾。

接下来，我们得到了一些美妙的机器，造型不可思议。

最后是一台连上电线的电机，电线让电机发生振动。

然后，其中一片振动的垃圾表现出来的运动要比其他垃圾好得多......最终我们得到了爬行的机器。

进化算法得出了一项设计，一些机器人可用的蓝图。

这种局限在计算机中的生物通过3D打印机从虚拟世界转移到了我们的世界。

然后，它迈出了自己的第一步。

故事迅速传播到了几十种刊物上，从《纽约时报》到《时代》杂志。

2000年11月，《科学美国人》用了这样一条标题“新物种的黎明？”这种杆子和电线的排列是否就相当于机器世界中的原始细胞呢？其实并不尽然：利普森的机器人仍就无法在没有人工干预的条件下运行。

“我们必须放入电池，”利普森告诉我，“但这是第一次由进化产生出了物理机器人。

这几乎是颠覆性的结果。

最终，我想把电线、电池和所有东西都打印出来。

这样进化就会有如此大的自由度，它将不会受到限制。

”
20世纪40年代末，在利普森第一个电脑进化的机器人出现前大约五十年，普林斯顿高等研究院里的物理学家、数学天才和计算机科学先驱最终建成了世界最早的通用数字计算机器中的一台——MANIAC（“数学分析仪，数值积分器，和计算机”）。

这个缩写（译者：缩写后的意思是“疯子”）是很贴切的：1952年的时候，计算机最早的任务之一就是帮忙开发氢弹，从而促进人类进行野蛮破坏的潜力。

但是，在同一台计算机上，一部分运算时间从为了毁灭而进行的计算中分了出来，利用这些分享到的运算时间，一种新型的数字生物逐渐成型。

这种数字生物就像流感病毒一样，它们繁殖、变异、相互竞争，并形成寄生关系。

它们以秒为单位进化。

这些所谓的共生有机体，这些二进制代码所代表的自我复制体，它们是挪威—意大利病毒学家尼尔斯·巴里塞利的心血结晶。

他想要观察进化的过程，而在那个前基因组时代，MANIAC为测试和观察进化过程提供了一个难得的机会。

正如美国技术史学家乔治·戴森在他的《图灵大教堂》（2012）一书中写道的，新的计算机被有效地分派了两个问题：“如何毁灭我们已知的生命和如何创造形式未知的生命”。

巴里塞利“不得不把他的数字宇宙挤到炸弹计算中去”，在晚上的凌晨时分工作，从成堆的穿孔卡片中捕捉数字生物的进化史。

然而利普森坚持认为，从一个基本观念上说，他的一些机器人是活的。

“没有什么比生和死更加黑白分明”
就像DNA一样，巴里塞利的代码也会变异。

但关于进化如何实现，他有一些不同寻常的想法。

除了单点突变以外，他认为进化通过病毒类生命体间的共生和寄生关系从而向前飞跃——否则进化的速度不够快。

他认为，也许细胞本身的首次出现就是在类似病毒的生物开始像乐高积木块儿一样穿插在一起的时候。

“根据共生起源理论，”巴里塞利写道，“导致细胞形成的进化过程是从许多病毒一样的生物间形成共生体开始的。

”
到目前为止，事情的发生似乎并不是这样的；事实上，一些研究人员认为，病毒的首次出现在细胞之后。

但巴里塞利的一些发现并不是太离谱。

一旦他在MANIAC上“撒下种子”，几分钟之内，这个数字宇宙就会充满能够繁殖的数字生物，它们有数字性别，修复“基因”损伤，并互相寄生。

这个种群在缺少环境威胁或选择压力的情况下就会停滞不前。

在另外的情况下，一种非常成功的寄生体会造成大范围的破坏。

这些对于有生命的东西来说是典型的行为模式，从最简单的细胞到人类皆是如此。

巴里塞利的模拟在整体形态上与生命世界相当吻合，而且让人特别想到了病毒。

病毒确实是寄生的：它们是共生体，也就是说它们必须控制其他生物的活细胞来进行繁殖；单看它们自己，它们不过是简单的蛋白外衣包裹的DNA或RNA机器。

和所有生物一样，病毒在复制过程中难免会发生变异。

但它们也会参与一些遗传交换。

当它们迂回进出宿主细胞的
时候，它们可能会窃取宿主的基因，或者留下自己的基因（有人估计，我们人类基因组的8%是通过病毒传给我们的）。

有些病毒甚至和其他病毒交换基因片段，这也在一定程度上加速了进化。

当流感病毒通过简单的变异和选择进化的时候，我们称之为抗原漂移。

每年秋天，我们中的一些人会接种年度流感疫苗，之所以这样做在很大程度上是因为抗原漂移。

但时不时地，A型流感病毒会有一个进化上的飞跃——与一个非常不同的毒株交换一大段基因组片段并经历一次抗原转变。

我们最害怕的流感病毒——新型、流行性毒株——通常就是这种转变的产物。

新出现的H7N9禽流感病毒被认为是经历了一次抗原转变，这使得它能够感染人类；到目前为止，中国已经感染了132例，死亡39例。

拣一个更爆炸性的例子，1957年爆发的亚洲流感是另一次抗原转变的产物，它在世界范围内灭绝了100万到400万人口。

可进化的计算机程序在进行无性别的算法交配时也会交换代码。

跟病毒一样，这种进行交换的能力提高了程序的进化能力。

尽管巴里塞利的数字生物变得很接近真实的东西，但它们只是数字代码：他们有一个基因型，但没有表现型，没有身体特征供进化筛选。

地球上的生命是解决问题的工具——能咬开坚果的鸟嘴，消化牛奶的能力，能够自动朝着正确方向迈出步子的腿。

自然选择作用于硬件上；软件，即DNA或数字代码，只是用来计分。

巴里塞利的造物可能已经表现得像个活的生物体了，但它们从来没有离开过电脑。

他们根本没有机会去参与到外面的世界中去。

（译者：这段视频演示的是多方块机器人的复制，虽然很简单，但核心在于机器人能利用材料——一个小方块——复制出跟自己一样的另一个多方块机器人，机器人是什么样子不重要，更多的是演示背后的计算机“复制”程序。

）
没有多少人会觉得塑料、电线和金属孕育的生物很漂亮。

然而，看着它们有意识地蹒跚走过实验室的地板，看着它们在捡起零件块儿建造自己克隆体的时候弯腰起身（想想《律政俏佳人》），我这个生物学家的脑袋里有了一种面对进化和鲜活生命的美妙感。

最引人注目的是由一组学生和合作者共同开发的蠕动“软体机器人”。

虽然它们还没有逃脱电脑的限制，但你可以在屏幕上实时地看到，一个由“肌肉”、“骨骼”和“软组织”构成的活生生的魔方进化出腿，而且生机勃勃地小跑起来。

我们的机器变得越像我们，似乎就越危险，越令人不安
如果利普森的电子动物园没有被抓进美国中央情报局，人们可以想像得出它们被摆上玩具反斗城店货架的样子，但它们还有着一个更深层次的目的。

像巴里塞利一样，利普森也希望阐释进化本身。

就在最近，他的团队对模块化提出了一些深刻的见解。

模块化这种奇特的现象是指生物系统是由独立的功能单位组成，例如：哺乳动物的大脑网络是分区的。

人们普遍认为，这种模块化特性能让以DNA为基础的生命实现快速的适应。

“我们搞清楚了是什么进化压力引起了这种模块化变化，”利普森告诉我。

“在生物学中，这一点很难验证。

生物学家常说：…我们不相信电脑搞出来的东西。

除非你能用真正生物学的东西来证明它，否则它只是空中楼阁‟。

”
虽然创意机器实验室的成果本质上具有新闻价值，但这只是通向新生命道路上的一小步。

巴里塞利总是避开关于自己所创造的生物是否算是活着的问题，他坚持认为，除非对生命
有一个“清晰”的定义，否则不能说他所创造的生物是活的还是死的。

然而利普森坚持认为，从一个基本观念上说，他的一些机器人是活的。

“没有什么比生和死更加黑白分明，”他说，“但在这个表象之下，事情并不简单。

生死之间有很多灰色地带。

”
一个人如何定义生命取决于他是跟谁混的，但对于一些基本的标准也有一个科学共识。

有生命的东西参与新陈代谢活动。

它们自给自足，也就是指它们能将自己的遗传物质与自己邻居的遗传物质分开。

它们繁衍生息。

它们有能力去适应或进化。

它们的特征在代码中明确指定，而且这份代码可以遗传。

创意机器实验室的机器人可能满足生命的许多标准，但它们不是完全自主的——目前还不是。

它们仍然需要人类的输入来进行复制，获得能量。

不过这些只是绊脚石，这些情况很快就可以解决——也许是通过一台3D打印机和一个现成的原料供应，再加上一只手拨动开关一次就够了。

然后，就是哲学家去决定是否给机器人颁发出生证明了。

我一直在把这些进展讲给朋友们听，一旦那份“酷炫”的感觉过去了，他们往往会变得忧虑起来。

“为什么会有人想这么做？”他们问我。

我们对于新的生命形式从未有过真正的体验，特别是电脑类的生命形式，尽管他们在书本上和屏幕上比比皆是。

想想阿瑟·C·克拉克的杀人电脑HAL，再想想太空堡垒卡拉狄加中疯狂的塞隆宝贝儿——为了提供服务而造出来的电脑进化到了摧毁自己创造者的地步。

我们的机器变得越像我们，似乎就越危险，越令人不安。

但也许我们所害怕的不是创造出新的生命，我们的很多担心在于潜在的、不可预知的突发行为。

进化肯定会导致这种情况出现。

拿病毒来说：就像利普森的机器一样，这些生物体处在生命和非生命之间的灰色地带，但它们属于这个星球上进化最快的存在。

它们也是最具破坏性的一些东西；1918年的西班牙流感杀死了大约50万人。

一些科学家担心某种末日病毒的出现只是一个时间问题。

从这一点上来看，病毒是活的还是死的并不重要。

重要的是，它们是能高速进化且不可预知的。

到这里事情就变得骇人了。

如果病毒可以在几个小时内进化，那么计算机代码能在几分之一秒内做到这一点。

病毒很傻；但计算机有处理器，它的处理器可能有一天会超越我们自己的大脑——有些人会说它们已经超越了。

如果我们要冒险给机器，用利普森的话来说，“如此大的自由度”，我们需要一个很好的理由。

在《失控》一书中，凯利提出了一个可能的理由。

他说，也许世界已经成了一个复杂的地方，我们别无选择，只能允许生物与技术之间的通婚；没有这两者的结合，我们所面临的问题困难到了我们人类的大脑解决不了的地步。

凯利提出了一种浮士德契约（译者：源于歌德的诗剧《浮士德》，即与魔鬼的契约，其实是饮鸩止渴。

）：“虚构的世界很快会变得像是活生生的世界：变得有自主性、适应性和创造性，但结果，这个世界会脱离我们的控制。

我想这是一笔重大的交易。

”
据利普森说，一个可进化的系统是“终极的人工智能，最让人放手的人工智能意味着一把双刃剑。

它很强大。

你需要给它的只是能量和计算能力。

这既可怕又很美好。

”60多年前，MANIAC被造出来去“解决无法解决的问题”。

如果我们现在有一些问题的解决方案超出了我们能自行设计的范围，而需要人工智能的进化，那又该怎样呢？一个可进化的程序能否帮助预测新流感病毒的出现？或者预测气候变化的影响？它能不能造出效率更高的机器？一旦一个真正自主、可进化的机器人出现，需要经过多长时间，它的后代（假定它们对我。