The Relationship between AI and Humans
题材：科技类
出处：The Economist《经济学人》
字数：786 words
[1] If you ask something of ChatGPT, an artificial-intelligence (AI) tool that is all the rage, the responses you get back are almost instantaneous, utterly certain and often wrong. It is a bit like talking to an economist. The questions raised by technologies like ChatGPT yield much more tentative answers. But they are ones that managers ought to start asking.
【假如你向眼下爆红的人工智能(AI)工具ChatGPT提问，得到的是几乎即时、十分有底气但常常是错误的答复。有点像跟经济学家对话。相比之下，关于ChatGPT这类技术引发的疑问，答案却模糊犹疑得多。但是这类问题才是管理者应该开始提出的。】
【重点词汇】
artificial-intelligence (AI) 人工智能
be all the rage 十分流行;风靡一时
instantaneous /ˌɪnstənˈteɪniəs/ adj. 立即的;立刻的
utterly /ˈʌtəlɪ/ adv. 完全地;彻底地
yield /jiːld/ v. 出产(作物);产生(收益、效益等);提供 n. 产量;产出
tentative /ˈtentətɪv/ adj. 不确定的;不肯定的;犹豫不定的
ought to modal verb.(情态动词)应该
[2] One issue is how to deal with employees’ concerns about job security. Worries are natural. An AI that makes it easier to process your expenses is one thing; an AI that people would prefer to sit next to at a dinner party quite another. Being clear about how workers would redirect time and energy that is freed up by an AI helps foster acceptance. So does creating a sense of agency: research conducted by MIT Sloan Management Review and the Boston Consulting Group found that an ability to override an AI makes employees more likely to use it.
【一个问题是如何处理员工对饭碗的担忧。担心是自然的。让你处理报销时更省力的AI是一回事，在晚宴上你愿意坐在它身边的AI又是另一回事。如果向员工讲清楚可以怎样把AI帮助释放的时间和精力改用在其他方面，员工的接受度就会上升。赋予员工主导感也有同样的效果：《麻省理工斯隆管理评论》(MIT Sloan Management Review)和波士顿咨询公司的研究发现，如果员工觉得自己有能力推翻AI的指令，就更有可能使用AI。】
【重点词汇】
redirect /ˌriːdəˈrekt/ v. 重新使用;使转向
override /ˌəʊvəˈraɪd/ v. 否决，推翻;比…更重要;凌驾
[3] Whether people really need to understand what is going on inside an AI is less clear. Intuitively, being able to follow an algorithm’s reasoning should trump being unable to. But a piece of research by academics at Harvard University, the Massachusetts Institute of Technology and the Polytechnic University of Milan suggests that too much explanation can be a problem.
【至于人们是否真的需要了解一个AI系统的内部原理，答案就没那么清晰了。直觉反应会是，能弄懂算法背后的推理逻辑应该比不懂要好。但哈佛大学、麻省理工学院和米兰理工大学的学者的一项研究表明，解释太多可能也是个问题。】
【重点词汇】
intuitively /ɪnˈtjuːɪtɪvli/ adv. 凭直觉地
algorithm /ˈælɡərɪðəm/ n. 算法;计算程序
trump /trʌmp/ v. (因说或做得更好而) 胜过 n.王牌
【长难句分析】
Whether people really need to understand what is going on inside an AI is less clear.
主句：… is less clear.
主语从句：whether people really need to understand…
宾语从句：what is going on inside an AI
[4] Employees at Tapestry, a portfolio of luxury brands, were given access to a forecasting model that told them how to allocate stock to stores. Some used a model whose logic could be interpreted; others used a model that was more of a black box. Workers turned out to be likelier to overrule models they could understand because they were, mistakenly, sure of their own intuitions. Workers were willing to accept the decisions of a model they could not fathom, however, because of their confidence in the expertise of people who had built it. The credentials of those behind an AI matter.
【他们给拥有多个奢侈品牌的Tapestry集团的员工提供了一个预测模型，可以指导他们在店铺之间调配库存。一组人用的是逻辑可被解释的模型，另一组使用的是更像个黑箱的模型。结果显示，员工往往会因为确信自己的直觉(尽管是错误的)而推翻他们能理解的模型所做的决定。但他们更愿意接受自己无法理解的模型所做的决定。但他们更愿意接受自己无法理解的模型所做的决定，因为信任模型建构者的专业性。AI开发人员的资历很重要。】
【重点词汇】
portfolio /pɔːtˈfəʊliəʊ/ n. (产品或设计的) 系列;文件夹
allocate /ˈæləkeɪt/ v. 分配
interpret /ɪnˈtɜːprɪt/ n. 诠释;说明
fathom /ˈfæðəm/ v. 理解;彻底了解
expertise /ˌekspɜːˈtiːz/ n. 专业技能;专门知识
credential /krəˈdenʃl/ v. 给……提供证书;资质
【长难句分析】
Workers turned out to be likelier to overrule models they could understand because they were, mistakenly, sure of their own intuitions.
主句：workers turned out to be likelier to overrule models
定语从句：(that)they could understand
原因状语从句：because they were sure of their own intuitions
[5] The different ways that people respond to humans and to algorithms is a burgeoning area of research. In a recent paper Gizem Yalcin of the University of Texas at Austin and her co-authors looked at whether consumers responded differently to decisions—to approve someone for a loan, for example, or a country-club membership—when they were made by a machine or a person. They found that people reacted the same when they were being rejected. But they felt less positively about an organisation when they were approved by an algorithm rather than a human. The reason? People are good at explaining away unfavourable decisions, whoever makes them. It is harder for them to attribute a successful application to their own charming, delightful selves when assessed by a machine. People want to feel special, not reduced to a data point.
【人们对人类和算法的不同反应是个快速发展的研究领域。在近期一篇论文中，得克萨斯大学奥斯汀分校的吉泽姆·亚尔钦(Gizem Yalcin)和合著者研究了消费者对机器和人类所做的决定(例如贷款或乡村俱乐部会员资格的审批)是否有不同反应。他们发现，在被拒绝时，人们对两者的反应是一样的。但当被批准时，如果他们得知决定是由算法而非人类做出的，他们对相关机构的好感会降低。原因何在?人们善于为于己不利的决定找理由自我开解，不管决定是谁做的。但如果是由机器评估，就不容易把申请成功归结为自己有魅力、招人喜欢。人们希望感到自己很特别，而不愿意沦为一个数据点。】
【重点词汇】
burgeon /ˈbɜːdʒən/ v. 迅速生长
loan /ləʊn/ n. 贷款;借款 v. 借出
assess /əˈses/ v. 评估;评定
[6] In a forthcoming paper, meanwhile, Arthur Jago of the University of Washington and Glenn Carroll of the Stanford Graduate School of Business investigate how willing people are to give rather than earn credit—specifically for work that someone did not do on their own. They showed volunteers something attributed to a specific person—an artwork, say, or a business plan—and then revealed that it had been created either with the help of an algorithm or with the help of human assistants. Everyone gave less credit to producers when they were told they had been helped, but this effect was more pronounced for work that involved human assistants. Not only did the participants see the job of overseeing the algorithm as more demanding than supervising humans, but they did not feel it was as fair for someone to take credit for the work of other people.
【与此同时，在即将发表的一篇论文中，华盛顿大学的亚瑟·加哥(Arthur Jago)和斯坦福大学商学院的格伦·卡罗尔(Glenn Carroll)的关注点从人们多想归功于自己转向了有多愿意认可他人的功劳，特别是对于那些并非由某个人独力完成的工作。他们先是向实验志愿者展示某件被归为某人出品的东西，比如一件艺术品或一份商业计划书，然后再告诉他们它是在算法或其他人的帮助下做出来的。得知背后有帮助后，所有志愿者都会认为创作人的功劳没那么大了，而这种效应在有人帮助的作品上更为明显。志愿者不仅认为监督算法运行比指挥人工作更难，还觉得把其他人的工作一并算在自己头上不太公平。】
【重点词汇】
forthcoming /ˌfɔːθˈkʌmɪŋ/ adj. 即将发生的
volunteer /ˌvɒlənˈtɪə(r)/ n. 义务工作者;志愿者 v. 志愿做;义务做
attribute /əˈtrɪbjuːt/ v. 把……归因于
assistant /əˈsɪstənt/ n. 助理;助手 adj. 助理的;副的
participant /pɑːˈtɪsɪpənt/ n. 参与者;参加者
oversee /ˌəʊvəˈsiː/ v. 监督，监视
supervise /ˈsuːpəvaɪz/ v. 监督;管理
[7] Another paper, by Anuj Kapoor of the Indian Institute of Management Ahmedabad and his co-authors, examines whether AIs or humans are more effective at helping people lose weight. The authors looked at the weight loss achieved by subscribers to an Indian mobile app, some of whom used only an AI coach and some of whom used a human coach, too. They found that people who also used a human coach lost more weight, set themselves tougher goals and were more fastidious about logging their activities. But people with a higher body mass index did not do as well with a human coach as those who weighed less. The authors speculate that heavier people might be more embarrassed by interacting with another person.
【印度管理学院艾哈迈达巴德分校的阿努杰·卡普尔(Anuj Kapoor)和他的合著者的另一篇论文研究了AI和人类在帮助人们减肥方面是否更有效。作者观察了一个印度移动App用户实现的减肥效果，其中一些人只使用AI教练，另一些人同时也使用人工教练。他们发现，同时使用人工教练的人减掉了更多的体重，为自己设定了更严格的目标，并且更严谨地记录了他们的活动。但是BMI指数较高的人在人工教练指导下的表现不如体重较轻的人。作者推测，体重较重的人在与他人互动时可能会更加尴尬。】
【重点词汇】
subscribe /səbˈskraɪb/ v. 订阅;持有 (意见或信仰)
coach /kəʊtʃ/ n.(体育运动的)教练
fastidious /fæˈstɪdiəs/ adj. 一丝不苟的;严谨的
speculate /ˈspekjuleɪt/ v. 推测;猜测
embarrass /ɪmˈbærəs/ v. 使尴尬，使窘迫
[8] The picture that emerges from such research is messy. It is also dynamic: just as technologies evolve, so will attitudes. But it is crystal-clear on one thing. The impact of ChatGPT and other AIs will depend not just on what they can do, but also on how they make people feel.
【这些研究呈现的图景很混乱。它也是动态的：技术在演进，人们的态度也会变化。但有一点非常清晰。ChatGPT和其他AI的影响不仅取决于它们本身的能耐，还取决于它们带给人类的感觉。】
【重点词汇】
emerge /iˈmɜːdʒ/ v. 出现;浮现
messy /ˈmesi/ adj. 肮脏的;混乱而复杂的
dynamic /daɪˈnæmɪk/ adj. 充满活力的;精力充沛的
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