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，牛津大学的研究人员做了一项关于未来就业的研究。他们得出结论：差不多将近一半的工作都有被机器自动化取代的危险。而机器学习应对这种颠覆负主要责任。它是人工智能最强大的分支。允许机器从现有数据中学习，并模仿人类的所作所为。因此我们可以从独特的视角来观察，机器可以做什么，不可以做什么，哪些工作可以被自动化或受到威胁。对于频繁，大批量的任务，我们无法与机器抗衡。但有些事情机器却无能为力。机器在解决新情况方面进展甚微。它们还不能处理未曾反复接触的事情。机器学习致命的局限在于它需要从大量已知的数据中总结经验，人类则不然。我们有一种能把看似毫不相关的事务联系起来的能力，从而解决从未见过的问题。在创新方面，机器无法与我们抗衡。这将使机器自动化取代人工受到限制。那么这对未来的工作意味着什么呢？未来工作的状态完全取决于一个问题：这种工作在多大程度上可以简化为频繁，大批量任务，又涉及多少对创新能力的要求？对于前者，机器变得越来越智能。综上所述，在创新方面机器没有取得太大进展，营销文案需要抓住消费者的心理，脱颖而出是关键。商业策略需要找到市场上还无人问津的空白。人类将是营销文案的创造者，人类才能推动商业战略发展。
