The development of computer programs that can beat humans at games has a long history — from the mastery of noughts and crosses in the 1950s to Deep Blue’s celebrated defeat of world chess champion Garry Kasparov in 1997.

能够在游戏中击败人类高手的计算机程序有着悠久的发展历史——从上世纪50年代掌握“井字棋”制胜之道，到1997年“深蓝”(Deep Blue；IBM研发的计算机——译者注）击败国际象棋世界冠军加里•卡斯帕罗夫(Garry Kasparov)。

In recent years, however, the pace of advance has quickened. Data-crunching devices routinely notch up previously unthinkable victories. Computers can triumph in quiz games, as IBM’s Watson proved when it won the TV show Jeopardy in 2011. They also mimic human aptitudes with ever greater facility. For instance, machines play arcade games simply by observing the movement of objects on the screen.

然而，近年来进步速度加快了。能够运算海量数据的设备经常取得以往不可想象的胜利。计算机能够在智力竞赛中取胜，IBM的“沃森”(Watson)在2011年赢得电视节目《危险边缘》(Jeopardy)就是例证。它们还能以越来越强大的“悟性”模仿人的天赋。例如，机器通过观察屏幕上物体的运动，就能学会玩街机游戏。

Even so, the triumph of the AlphaGo computer over the South Korean world champion Lee Se-dol in the first of a five-match series in the ancient Chinese board game of Go marks more than just a new notch on the computerised honours board. Mr Lee had been confident of victory and proclaimed himself “shocked” by his defeat.

即便如此，AlphaGo电脑在古老的中国棋盘游戏——围棋的对垒中击败韩国九段棋手李世石(Lee Sedol)，在五局“人机对战”中首战告捷，不仅标志着电脑荣誉板上的一个新档次。赛前对胜利信心满满的李世石，在落败后坦承“震惊”。

Go is a little like a version of chess, only vastly more complicated. Indeed the possible moves within a game exceed the number of atoms within the universe. This is a challenge that would defeat traditional programmes. Indeed it can only be mastered by computers assembled into neural networks that teach themselves through observation and practice — abilities that remain at the frontiers of computer science.

围棋有点像国际象棋的变体，只是复杂程度高得多。的确，其棋局的变数比宇宙中的原子数量还要多。这个挑战会挫败传统的程序。事实上，只有多台计算机组成神经网络，通过观察和实践来“自学”（这些能力仍处于计算机科学的前沿），才能驾驭这种高难度挑战。

Demis Hassabis and his team at DeepMind, the UK-based artificial intelligence (AI) arm of Alphabet, deserve credit for the speed at which they have mastered this undertaking. True, AlphaGo, a formidable piece of IT, could be described as a computerised sledgehammer aimed at a recreational nut. Its victory, however, is a reminder of how fast the world is overcoming the obstacles in the way of AI, and its deployment in the world about us.

杰米斯•哈萨比斯(Demis Hassabis)以及他在DeepMind（Alphabet旗下英国人工智能部门）的团队以如此快的速度掌握围棋制胜之道，这一点值得赞赏。没错，作为一件具有强大能力的信息技术设备，AlphaGo可以被形容为一把计算机化的大锤，其用途是敲开一个消遣的坚果。然而，它的胜利提醒世人，世界正在快速攻克人工智能及其实际部署所面临的障碍。

That is largely due to the huge amount of cash being poured into AI research by US and Chinese companies. These are poaching some of the brightest computer scientists from universities, giving them the capacity and tools to pursue their heart’s desire.

这在很大程度上归功于美国和中国企业对人工智能研究的巨大投入。这些企业从高校挖走一些最优秀的计算机科学家，并提供资源和工具，让这些科学家从事内心渴望的研究。

According to a recent survey, half of the world’s AI experts believe human level machine intelligence will be achieved by 2040. This opens up huge possibilities for the enrichment of mankind, from tackling climate change and treating disease to labour-saving devices. It also raises ethical questions every bit as profound as those posed by genetics. AI experts talk about the possibility of the human brain being reverse-engineered. Physicist Stephen Hawking last year warned that unless we take care, board games might be the least of it: AI could ultimately “outsmart us all”.

根据最近的一项调查，全球半数人工智能专家相信，人类水平的机器智能到2040年就能成为现实。这为增进人类福祉开启巨大可能性——从应对气候变化、治疗疾病，到节省劳动力的设备。这也引发种种道德问题，其深刻性丝毫不亚于遗传学所构成的道德问题。人工智能专家谈到人脑被“逆向工程”的可能性。物理学家史蒂芬•霍金(Stephen Hawking)去年曾警告，除非我们小心，否则棋盘游戏可能是最无关紧要的问题：人工智能最终可能“比我们所有人更聪明”。

One does not have to believe in some future tech dystopia to believe that governments and wider society should take the implications of these developments seriously. Google, Facebook and other companies rushing into AI point out that they are establishing ethics panels to consider appropriate uses for these technologies. These are unlikely to be immune from commercial interests or indeed from the gung-ho enthusiasm of the researchers.

人们不一定非要相信未来将出现某种科技“敌托邦”才会认为，政府和整个社会应该认真对待这些发展的潜在影响。竞相进军人工智能领域的谷歌(Google)、Facebook等公司指出，他们正在成立伦理小组以考量这些技术的适当用途。这些小组不太可能对商业利益以及研究人员的热忱无动于衷。

Some external scrutiny akin to that supplied in the case of genetics by the UK’s Human Fertilisation and Embryology Authority is needed to protect the public from developments that may threaten more than the amour-propre of a South Korean Go champion. Granted, there may yet be no evidence that computers will ever shrug off their human masters but we should still treat these developments with the humility and caution they deserve.

需要进行一些外部监督，类似于遗传学领域的英国人类受精和胚胎学管理局(HFEA)，以保护公众免受相关发展的威胁，这些威胁所牵涉的不只是韩国围棋高手的自尊。当然，目前也许还没有证据表明计算机有朝一日将踢开他们的人类主人，但我们仍应该对这些发展给予应有的谦卑和审慎。