人工智能將如何改變就業市場大綱

Artificial intelligence, which is the ability of machines to react intelligently to their environment, has been undergoing tremendous progress in the last decade. An AI program can mimic human functions such as problem solving and learning. While it's true that AI offers much promise for the development of smarter and more useful machines, it also fills many with fear of a dystopian future where millions are thrown out of work, replaced by robots and smart machines.

人工智能是機器對周遭環境作出智能反應的能力，過去10年來，人工智能已取得了巨大進展。一個人工智能程序能模仿人類的功能，例如：解決問題和學習。儘管，我們承認人工智能讓我們更有希望，發展出更智能、更有用的機器，但很多人也會擔心未來的世界是反烏托邦的：幾百萬人將會丟掉飯碗，被機器人和智能機器取代。

It's perhaps possible that humans will one day be reduced to servants of our machine overlords, but a sober appraisal predicts a mixed impact of AI on the job market. History teaches us that machines do displace humans, but somehow there are still plenty of jobs available today. The reason is that automation can substitute for labor on certain jobs, but also complements labor for other jobs that are not easily automated, making labor more productive and actually increasing the demand for workers.

也許有一天，人類會淪落爲機器霸主的僕人，但更爲清醒的評估則預測出了人工智能對就業市場的混合影響。歷史教會我們：機器是會取代我們的，但現今在某種程度上，我們還是有很多的工作選擇。原因是：自動化可以替代某些工作，但也爲其它不那麼容易自動化的工作補充了勞動力，這樣就會更加多產，實則也會增加對工人的需求。

Jobs that are composed of repetitive tasks are the ones most vulnerable to automation. Examples including automated weaving machines, ATMs, production-line welders and phone answering systems. It might seem that these advances would simply throw people out of work. But look at the example of the weaving machines. They increased productivity 50-fold and dropped the price of cloth by 98 percent. The demand for cloth exploded as the price fell, thereby creating more weaver jobs. In the years between 1830 and 1900, the number of weaver jobs increased 4-fold despite automation. Automation increased demand for weavers, but also changed the nature of the weaver's job. A similar process happened with ATMs, which did not remove the need for human tellers, whose numbers actually have risen since ATMs were introduced in the 1970s.

那些不斷重複做任務的工作是最容易被自動化的。例如：自動編織機、自動取款機、生產線焊工和電話應答系統。看起來，這些進步會讓人們丟了工作。但讓我們以編織機爲例，看看情況。編織機使生產率提高了50倍，衣服的價格也相應下降了98%。隨着價格下滑，人們對衣服的需求量爆增，因此就創造出更多的編織工作。在1830-1900年間，儘管工廠實行了自動化，紡織工作卻翻了兩番。自動化增加了對織工的需求，但也改變了織工的工作性質。自動取款機也遇到了相似狀況，自動取款機的出現並沒有減少人們對出納員的需求，實際上，自20世紀70年代引入取款機以來，出納員人數有增無減。

The intelligent response is for the public and private sectors to create worker training programs to teach new skills that will be required despite the spread of automation. This will require an investment in on-the-job training and lifelong learning. Some experts point to the social policies adopted by Denmark that make hiring and firing easy, yet support out-of-work employees as they receive retraining and search for a new job.

儘管實施自動化的部門越來越多，智能響應卻爲公立和私營部門創造工人訓練計劃、教授他們必需的新技能。這就需要對在職培訓和終身學習進行投資。有些專家指向了丹麥採取的政策，該政策使僱傭和解僱簡單方便，但又對接受再訓練和尋找新工作的失業人員表示支持。