如图，在▱ABCD中，E是BC的中点，且∠AEC=∠DCE，则下列结论不正确的是（　　）

    夜深了，一位巴格达商人走在黑漆漆的山路上。突然，有个神（秘 密）的声音传来：“弯下腰，请多捡些小石子，明天会有用的！”商人决定执行这一指令，便弯腰捡起几（棵 颗）石子。到了第二天，当商人从袋中掏出“石子”看时，才发现那所谓的“石子”原来是一块块亮晶晶的宝石！自然，也正是这些宝石，使他立（既 即）变得后悔不迭：天！昨晚怎么就没有多捡些呢？

    这是科学家巴甫洛夫讲的一个故事。尤其发人深省的是，他在讲完故事后说：“教育就是这么回事——当我们长大成人之后，才会发现以前学的科学知识是珍贵的宝石，但同时，我们也会觉得可惜，因为我们学的毕竟太少了！”

    不是吗？教育送给别人的明明是瑰丽的“宝石”，可总有人因为弯腰太累视而不见，结果白白地错过了许多机会。

    还有个故事更意味深（常 长），是歌德在他的叙事歌谣里讲的。耶稣带着他的门徒彼得远行，途中发现一块破烂的马蹄铁，耶稣就让彼得把它捡起来。不料彼得懒得弯腰假装没听见，耶稣没说什么就自己弯腰捡起马蹄铁，用它从铁匠那儿换来三文钱，用这钱买了十八颗樱桃。出了城，二人继续前进，经过的全是茫茫的荒野。耶稣猜到彼得渴得够呛，就让藏于袖中的樱桃悄悄地掉出一颗，彼得一见，赶紧捡起来吃。耶稣边走边丢，彼得也就狼狈地弯了十八次腰。于是琊稣笑着对他说：“要是你刚才弯一次腰，就不会在后来没完没了地弯腰。小事不干，将来就会在更小的事情上操劳。”

    不去弯腰或疏于弯腰，是糊涂；而耻于弯腰者，肯定是傻子！

    Artificial intelligence (AI) is rushing into business. Firms of all types are using AI to forecast demand, hire workers and deal with customers. The McKinsey Global Institute, a think-tank within a consultancy, forecasts that just applying AI to marketing, sales and supply chains could create economic value of $2.7trn over the next 20 years.

    Such grand forecasts fuel anxiety as well as hope. Less familiar, but just as important, is how AI will transform the workplace.

    Start with the benefits.AI ought to improve productivity. Humanyze, a people analytics software provider, combines data from its badges（工牌）with employees' calendars and e-mails to work out, say, whether office layouts favour teamwork .Slack, a workplace messaging app, helps managers assess how quickly employees accomplish tasks. Companies will see when workers are not just dozing off but also misbehaving.

    Employees will gain, too. Thanks to advance in computer vision, AI can check that workers are wearing safety equipment and that no one has been harmed on the factory floor. Some will appreciate more feedback on their work and welcome a sense of how to do better.

    Machines can help ensure that pay rises and promotions go to those who deserve them. That starts with hiring. People often have biases but algorithms（算法）, if designed correctly, can be more unprejudiced. Software can flag patterns that people might miss.

    Yet AI^'s benefits will come with many potential drawbacks. Algorithms may not be free of the biases of their programmers, which can have unintended consequences. The length of a travel may predict whether an employee will quit a job, but this focus may harm poorer applicants. Older staff might work more slowly than younger ones and could risk losing their positions if all AI looks for is productivity. And surveillance（监控）may feel Orwellian—a sensitive matter now that people have begun to question how much Facebook and other tech giants know about their private lives.

    As regulators and employers weigh the pros and cons of AI in the workplace, three principles ought to guide its spread. First, data should be anonymized where possible. Microsoft, for example, has a product that shows individuals how they manage their time in the office, but gives managers information only in aggregated（整合）form. Second, the use of AI ought to be transparent. Employees should be told what technologies are being used in their workplaces and which data are being gathered. As a matter of routine, algorithms used by firms to hire, fire and promote should be tested for bias and unintended consequences. Last, countries should let individuals request their own data, whether they are ex-workers wishing to contest a dismissal or jobseekers hoping to demonstrate their ability to prospective employers.

    The march of Al into the workplace calls for trade-offs between privacy and performance. A fairer, more productive workforce is a prize worth having, but not if it chains employees. Striking a balance will require thought, a willingness for both employers and employees to adapt and a strong dose of humanity.