新东方在线雅思网为大家带来了雅思阅读练习题：Can a robot replace us?。正文都做了贴心的注解，文章包含雅思词汇、例句讲解。希望以下内容能够为同学们的雅思备考提供帮助。新东方在线雅思网将第一时间为大家发布最新、最全、最专业的雅思报名官网消息和雅思考试真题及解析，供大家参考。

　　Robots. They can already clean our floors, build our cars, review legal documents, check us in at hotels and serve us drinks, but will we see them sitting around the boardroom table in place of people? Are my fellow board directors about to be made obsolete, replaced by robots overseeing companies? Will the discussion of diversity around the board table begin to include talk of non-humans?

　　It might sound farfetched, but 45% of 800 executives surveyed by the World Economic Forum’s Global Agenda Council on the Future of Software and Society said they expected an artificial intelligence machine will sit on a company’s board of directors by the year 2025.

　　This isn't the first time this has come up. Last year an investment group drummedup(招徕) headlines by announcing that it had appointed an AI to its board of directors. The firm said it would analyse data to help them make decisions about biotech investments. But, since that isn’t the full extent of the role of a genuine board member, the algorithm clearly was not really going to function as a full voting member of the firm’s board.

　　So do we need to set a place for robots at the boardroom table? There are a couple of reasons why I’m in the 55% who don't believe that are our jobs are at risk, or at least not from robots.

　　I believe data in the boardroom is growing in importance. Data can help us make decisions of all kinds. When developing strategy, it informs our thinking on marketplace trends, on what people are buying, selling, saying and doing.

　　On the remunerations and compensation committee, we use data to see what people are earning in the company and in the industry more broadly, and to examine overall compensation trends. In the audit committee, and also when doing any sort of financial analysis, we use data to see where spending and saving is and isn’t happening. And risk committees use data to analyse the myriad factors associated with risk of any kind, be it financial, infrastructure, strategy, legal and more.

　　In fact, there are few, if any areas, where we don't depend on data in some shape or form.

　　But it’s how we use the data to inform our decisions that differentiates us from the robots.We weigh the information to make decisions that are specific to the company, its employees and its competitiveness. It is the data mixed with creativity and intuitive, non-linear thinking that makes a company successful.

　　Indeed, if everyone is using the same sort of data and simply making automatic, calculated decisions from it, then differentiation is lost. The competitive advantage,in many ways, comes from the ingenuity and creativity of people.

　　I've often said that the boardroom is the most “human” place I've ever been. People come with their own knowledge, feelings, emotions and agendas. And, yes, that can colour the conversation on the day and sometimes hinder efficiency or easy decision making. But there is also a healthy friction that comes into play as well, which results in more robust results.

　　It is true that humans are fallible, and board directors are no exception. For example, pay packets(工资待遇) for CEOs can be too high, perhaps because they’ve been driven by human greed or judgement of real value. But would it be any different with a robot on the board? They would analyse the pay of other CEOs, and come up with calculations, just as is done now. But would they be able to bring about change to the compensation structure? Would they force a right sizing or apply a moral or ethical dimension to whether the compensation was correct? I think it would still take a human, or at least a human programming it, to calculate that.

　　Another important part to the human boardroom is the ability to judge people. Not what is on paper, but rather the people who are actually in front of you. Anyone can come up with an idea and even present it well. But as any investor, and particularly venture capitalists, will tell you, quantitative calculations can only take you so far when judging whether the idea is likely to be a success. Bringing those ideas to fruition, be it a new venture or a new direction for a company, requires the right people to execute on it. Judging whether things are going well or poorly, whether a strategy will work or not comes down to the ability to size someone up. The board must decide they are going to trust a CEO or an executive, and that has a lot to do with whether they are credible leaders.That can't be a judgement solely based on numbers.

　　Some of the fallibility in boardrooms comes from the fact that as a diverse group of board members we are,individually, often called to make decisions on matters where we don’t have expertise. In those cases, we depend on data and analysis and good briefings to help us to make those decisions, but that is still not a substitute for good judgement.

　　Also, data is not necessarily completely objective, nor is it always correct. Polling has proven recently that the data we have is only as good as the questions asked, and the veracity of the answers given.

　　Using data as a tool is great, and there is definitely a place for all kinds of AI as an enabling tool in the boardroom. But successful boardrooms are characterized by nuance and judgement. The boardroom, like most of life, is not a 0-or-1 situation. We must depend on human intuition and human understanding and combine that with data.

　　As board directors, we must draw on as much information and analysis as possible, and big data has a real role to play in enabling the boardroom, but I don't think I'll be sitting next to a robot in the boardroom any time soon.

　　Vocabulary

　　Obsolete 过时的

　　Oversee 监管

　　Farfetched 牵强附会的

　　Algorithm 运算法则

　　Remuneration 回报

　　Compensation 补偿

　　Audit 审计

　　Myriad 很多的;大量的

　　Differentiate 区分;区别

　　Intuitive 直觉的

　　Ingenuity 精巧;独创

　　Hinder 阻碍

　　Friction 摩擦

　　Robust 坚固的;有力的

　　Fallible 可能犯错的

　　Come down to… 归结于

　　Fallibility 可错性

　　Briefing 简报

　　Veracity 真实性

　　Nuance 细微之处

　　Draw on 利用

　　本文长难句

　　It might sound farfetched,but 45% of 800 executives surveyed by the World Economic Forum’s Global Agenda Council on the Future of Software and Society said they expected an artificial intelligence machine will sit on a company’s board of directors by the year 2025.

　　这听起来似乎牵强，但是在“软件与社会的未来”这一调查中，接受世界经济论坛全球事务协会调查的800名高管里，有45%的人表示期待在2025年前将看到人工智能机器参与公司董事会。

　　But, since that isn’t the full extent of the role of a genuine board member, the algorithm clearly was not really going to function as a full voting member of the firm’s board.

　　但是，由于这并不是真正的董事成员的全部职能，所以显而易见，(机器人的)运算法则并不能在公司董事会上像有投票权的成员那样履行职责。

　　And risk committees use data to analyse the myriad factors associated with risk of any kind, be it financial, infrastructure, strategy, legal and more.

　　风险委员会用数据来分析与各类风险相关的诸多因素，不管是财务、基础设施、策略、法律还是其他。

　　Indeed, if everyone is using the same sort of data and simply making automatic,calculated decisions from it, then differentiation is lost.

　　的确，如果每个人都利用同样的数据，并由此得出自动的、计算出来的结论，那么差别就消失了。

　　Bringing those ideas to fruition, be it a new venture or a new direction for a company, requires the right people to execute on it.

　　要让这些想法开花结果，无论是开一家新公司，或是为公司找一个新的方向，需要恰当的人来执行才可以。

　　Some of the fallibility in boardrooms comes from the fact that as a diverse group of board members we are, individually, often called to make decisions on matters where we don’t have expertise.

　　董事会可能犯错，是因为如下事实：董事会成员虽然多种多样，但我们经常被单个叫去，就一些我们没有专业知识的事情做决定。