The jobs we'll lose to machines — and theones we won't
In 2013, researchers at Oxford Universitydid a study on the future of work. They can conclude
that almost on in every two jobs have ahigh risk of being automated by machines. Machine learning is the technologythat’s responsible for most of this disruption. It’s the most powerful branchof artificial intelligence. It allows machines to learn from data and mimicsome of the things that humans can do. This gives us a unique perspective onwhat machines can do, what they can’t do and what jobs they might automate orthreaten. We have no chance of competing against machines on frequent,high-volume tasks. But there are things we can do that machines can’t do. Wheremachines have made very little progress is in tackling novel situations. Theycan’t handle things they haven’t seen many times before. The fundamentallimitations of machine learning is that it needs to learn from large volumes ofpast data. Now, humans don’t. We have the ability to connect seeminglydisparate threads to solve problems we’ve never seen before. Machines cannotcompete with us when it comes to tackling novel situations, and this puts afundamental limit on the human tasks that machines will automate. So what doesthis mean for the future of work? The future state of any single job lies inthe answer to a single question: To what extent is that job reducible tofrequent, high-volume tasks, and to what extent does it involve tackling novelsituations? On frequent, high-volume tasks, machines are getting smarter andsmarter. Now as mentioned, machines are not making progress on novelsituations. The copy behind a marketing campaign needs to grab consumers’attention. It has to stand out from the crowd. Business strategy means findinggaps in the market things that nobody else is doing. It will be humans that arecreating the copy behind our marketing campaigns, and it will be humans thatare developing our business strategy.
2013年，牛津大學的研究人員做了一項關於未來就業的研究。他們得出結論：差不多將近一半的工作都有被機器自動化取代的危險。而機器學習應對這種顛覆負主要責任。它是人工智能最強大的分支。允許機器從現有數據中學習，並模仿人類的所作所爲。因此我們可以從獨特的視角來觀察，機器可以做什麼，不可以做什麼，哪些工作可以被自動化或受到威脅。對於頻繁，大批量的任務，我們無法與機器抗衡。但有些事情機器卻無能爲力。機器在解決新情況方面進展甚微。它們還不能處理未曾反覆接觸的事情。機器學習致命的侷限在於它需要從大量已知的數據中總結經驗，人類則不然。我們有一種能把看似毫不相關的事務聯繫起來的能力，從而解決從未見過的問題。在創新方面，機器無法與我們抗衡。這將使機器自動化取代人工受到限制。那麼這對未來的工作意味着什麼呢？未來工作的狀態完全取決於一個問題：這種工作在多大程度上可以簡化爲頻繁，大批量任務，又涉及多少對創新能力的要求？對於前者，機器變得越來越智能。綜上所述，在創新方面機器沒有取得太大進展，營銷文案需要抓住消費者的心理，脫穎而出是關鍵。商業策略需要找到市場上還無人問津的空白。人類將是營銷文案的創造者，人類才能推動商業戰略發展。