Our Machine Masters
警惕人工智能的美麗新世界
Some days I think nobody knows me as well as Pandora. I create a new music channel around some band or song and Pandora feeds me a series of songs I like just as well. In fact, it often feeds me songs I’d already downloaded onto my phone from iTunes. Either my musical taste is extremely conventional or Pandora is really good at knowing what I like.
有時候我覺得,世上沒有人能比Pandora更了解我。我根據(jù)幾支樂隊和歌曲新建了一個音樂頻道,它就會提供一系列同樣能讓我喜歡的歌。事實上,它經(jīng)常給我一些已經(jīng)從iTunes下載到手機上的歌。不是我的音樂品味太普通,就是Pandora真的很擅長揣摩我的喜好。
In the current issue of Wired, the technology writer Kevin Kelly says that we had all better get used to this level of predictive prowess. Kelly argues that the age of artificial intelligence is finally at hand.
在最新一期的《連線》雜志(Wired)里,科技作家凱文·凱利(Kevin Kelly)說,我們大家要去適應(yīng)這種高超的預(yù)測技能。凱利認(rèn)為,人工智能的時代終于近在眼前了。
He writes that the smart machines of the future won’t be humanlike geniuses like HAL 9000 in the movie “2001: A Space Odyssey.” They will be more modest machines that will drive your car, translate foreign languages, organize your photos, recommend entertainment options and maybe diagnose your illnesses. “Everything that we formerly electrified we will now cognitize,” Kelly writes. Even more than today, we’ll lead our lives enmeshed with machines that do some of our thinking tasks for us.
他說未來的智能機器不會像《2001太空漫游》(2001: A Space Odyssey)中的HAL 9000那樣,是個類人的天才。它們將是一些比較不起眼的機器,幫你開車,翻譯外語,整理你的照片,推薦娛樂選項,也許還能診斷你的疾病。“所有我們之前電氣化的東西,現(xiàn)在都要認(rèn)知化,”凱利寫道。我們的生活和機器的關(guān)系,要比今天更加糾纏不清,機器會代替我們完成一部分動腦子的工作。
This artificial intelligence breakthrough, he argues, is being driven by cheap parallel computation technologies, big data collection and better algorithms. The upshot is clear, “The business plans of the next 10,000 start-ups are easy to forecast: Take X and add A.I.”
他認(rèn)為,這種人工智能的突破進(jìn)展,是由廉價的并行計算技術(shù)、大數(shù)據(jù)收集和更好的算法推動的。結(jié)果已經(jīng)很清晰,“接下來10000家創(chuàng)業(yè)公司的商業(yè)計劃很好預(yù)測:選擇X,添加AI。”
Two big implications flow from this. The first is sociological. If knowledge is power, we’re about to see an even greater concentration of power.
這會產(chǎn)生兩種巨大的影響。首先是社會學(xué)上。如果說知識就是力量,那么我們將看到一股比以往更加集中的力量。
The Internet is already heralding a new era of centralization. As Astra Taylor points out in her book, “The People’s Platform,” in 2001, the top 10 websites accounted for 31 percent of all U.S. page views, but, by 2010, they accounted for 75 percent of them. Gigantic companies like Google swallow up smaller ones. The Internet has created a long tail, but almost all the revenue and power is among the small elite at the head.
互聯(lián)網(wǎng)已經(jīng)預(yù)示了一個全新的中心化時代即將到來。正如阿斯特拉·泰勒(Astra Taylor)在《人民平臺》(The People’s Platform)一書中所寫,在2001年,排名前10的網(wǎng)站占據(jù)了全美31%的頁面瀏覽量,但是到2010年,這個比例已經(jīng)達(dá)到75%。像谷歌 (Google)這樣的巨無霸會吞噬小公司。互聯(lián)網(wǎng)創(chuàng)造了長尾,但幾乎所有的收入和力量都掌握在頭部為數(shù)不多的精英手上。
Advances in artificial intelligence will accelerate this centralizing trend. That’s because A.I. companies will be able to reap the rewards of network effects. The bigger their network and the more data they collect, the more effective and attractive they become.
人工智能的進(jìn)步會加速中心化的趨勢。因為人工智能公司能從網(wǎng)絡(luò)效應(yīng)中獲益。網(wǎng)絡(luò)越大,收集的數(shù)據(jù)越多,就越有效率,越能吸引人。
As Kelly puts it, “Once a company enters this virtuous cycle, it tends to grow so big, so fast, that it overwhelms any upstart competitors. As a result, our A.I. future is likely to be ruled by an oligarchy of two or three large, general-purpose cloud-based commercial intelligences.”
如凱利所說,“一旦公司進(jìn)入這種良性循環(huán),往往會以很快的速度,變得越來越龐大,把一切剛剛冒頭的競爭者壓倒。其結(jié)果是,人工智能的未來,可能會被兩三個龐大的、多功能的、基于云計算的商業(yè)智能寡頭所統(tǒng)治。”
To put it more menacingly, engineers at a few gigantic companies will have vast-though-hidden power to shape how data are collected and framed, to harvest huge amounts of information, to build the frameworks through which the rest of us make decisions and to steer our choices. If you think this power will be used for entirely benign ends, then you have not read enough history.
說得更嚇人一些,幾家巨型公司的工程師會擁有巨大卻又不為人知的力量,他們能影響數(shù)據(jù)的收集和構(gòu)建方式,能收集規(guī)模巨大的信息,能建起一種框架,讓我們這些人在框架中做決策,引導(dǎo)我們的選擇。如果你認(rèn)為這種力量全都會用在正道上,那你該再多讀些歷史。
The second implication is philosophical. A.I. will redefine what it means to be human. Our identity as humans is shaped by what machines and other animals can’t do. For the last few centuries, reason was seen as the ultimate human faculty. But now machines are better at many of the tasks we associate with thinking — like playing chess, winning at Jeopardy, and doing math.
第二個影響是哲學(xué)層面的。人工智能會重新定義它對人類的意義。我們作為人類的身份,取決于機器和其他動物所不能做到的東西。過去幾百年來里,理性被認(rèn)為是終極的人類官能。但是現(xiàn)在有很多我們認(rèn)為和思考有關(guān)的工作,機器可以完成得比我們更好——比如下象棋、在《危險邊緣》(Jeopardy)中獲勝,或者做數(shù)學(xué)運算。
On the other hand, machines cannot beat us at the things we do without conscious thinking: developing tastes and affections, mimicking each other and building emotional attachments, experiencing imaginative breakthroughs, forming moral sentiments.
另一方面,在一些不需要我們有意識地思考的事情上,機器是無法戰(zhàn)勝我們的:培養(yǎng)品味和感情,相互模仿,建立情感聯(lián)結(jié),體驗想象力的飛躍,形成道德情感。
In the age of smart machines, we’re not human because we have big brains. We’re human because we have social skills, emotional capacities and moral intuitions. I could paint two divergent A.I. futures, one deeply humanistic, and one soullessly utilitarian.
在智能機器的時代,我們之為人類并非因為有顆厲害的大腦,而是因為我們有社交技巧、情感能力和道德直覺。我能展望到兩種截然不同的人工智能未來,一種有著深沉的人文主義,另一種是毫無靈魂的功利主義。
In the humanistic one, machines liberate us from mental drudgery so we can focus on higher and happier things. In this future, differences in innate I.Q. are less important. Everybody has Google on their phones so having a great memory or the ability to calculate with big numbers doesn’t help as much.
在人文主義的未來里,機器讓我們從心智的苦力中解脫出來,把精力放在更高、更幸福的事上。在這個未來里,先天的智商差距已經(jīng)沒那么要緊。每個人的手機上都有谷歌,有個好記性,或者可以進(jìn)行復(fù)雜的計算,用處已經(jīng)沒那么大。
In this future, there is increasing emphasis on personal and moral faculties: being likable, industrious, trustworthy and affectionate. People are evaluated more on these traits, which supplement machine thinking, and not the rote ones that duplicate it.
在這個未來里,個人和道德官能越來越重要:要有親和力、勤奮、可靠、有愛心。人的價值會更多地取決于這些特征,它們會彌補機器思考的不足。評價人的方式不會再是死記硬背的本事,因為那只是在復(fù)制機器的思考。