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What is a reason for the author to be in the habit of saying "busy" when asked how he is doing?

Why do we tend to think that busy people are of high status?

What do we learn about the culture of busyness from a recent study?

What do such utterances as "I have limited access to email" sound like according to the author?

Why did the author and his colleagues launch the Out of Office Email Generator?

What did the author's team conclude about the gender difference in airfares from their further investigation?

What did the researchers want to determine by testing a variety of possible explanations?

What happened when the negative reciprocity variable was taken into account?

What did prior research on negative reciprocity among workers find?

What does the author emphasize about their analysis in the last paragraph?

What characterizes Japanese and Chinese foods?

What is typical of Americans in the way of eating?

What characterizes Japanese and Chinese foods?（日本和中国的饮食有什么特点？）

What is typical of Americans in the way of eating?（美国人的饮食习惯有什么典型特征？）

What features in Mediterranean, Nordic and Okinawan diets?（地中海、北欧和冲绳的饮食有什么共同特点？）

What do people in most healthy eating cultures have in common?（大多数健康饮食文化中的人们有什么共同点？）

Compared with the average American, people in healthy societies .（与普通美国人相比，健康社会的人们。）

What is the finding of the new study?（这项新研究的发现是什么？）

What was the purpose of psychologist Myriam Bechtoldt's experiment?（心理学家米里亚姆·贝克托尔德的实验目的是什么？）

What does the author say about working from home? (作者认为居家办公是怎样的？)

Why do some people oppose working from home? (为什么有些人反对居家办公？)

Why did the author run the estimates for Montréal? (作者为什么要对蒙特利尔进行估算？)

What can we conclude from the author's calculations? (从作者的计算中我们能得出什么结论？)

What is the author's opinion on working from home? (作者对居家办公的看法是什么？)

The human thirst for knowledge is the driving force behind our successful development as a species. But curiosity can also be dangerous, leading to setbacks or even downfalls. Given curiosity's complexity, scientists have found it hard to define. While pinning down a definition has proven tricky, the general consensus is it's some means of information gathering. Psychologists also agree curiosity is intrinsically (内在地) motivated. Curiosity covers such a large set of behaviors that there probably isn't any single "curiosity gene" that makes humans wonder about and explore their environment. That said, curiosity does have a genetic component. Genes and the environment interact in many complex ways to shape individuals and guide their behavior, including curiosity. Regardless of their genetic makeup, infants have to learn an incredible amount of information in a short time, and curiosity is one of the tools humans have found to accomplish that gigantic task. Hundreds of studies show that infants prefer novelty. It's what motivates non-human animals, human infants and probably human adults to explore and seek out new things before growing less interested in them after continued exposure. But curiosity often comes with a cost. In some situations, the stakes are low and failure is a healthy part of growth. For instance, many babies are perfectly proficient crawlers, but they decide to try walking because there's more to see and do when they stand upright. But this milestone comes at a small cost. A study of 12- to 19-month-olds learning how to walk documented that these children fell down a lot—seventeen times per hour, to be exact. But walking is faster than crawling, so this motivates expert crawlers to transition to walking. Sometimes, however, testing out a new idea can lead to disaster. For instance, the Inuit people of the Arctic regions have created incredible modes to deal with the challenges of living in northern climates, but what we forget about are the tens of thousands of people that tried and failed to make it in those challenging landscapes. (译文) 人类对知识的渴望是我们作为一个物种成功发展的驱动力。但好奇心也可能是危险的，会导致挫折甚至失败。鉴于好奇心的复杂性，科学家们发现很难对其下定义。尽管给好奇心下定义被证明颇具难度，但普遍共识是，它是一种收集信息的方式。心理学家也一致认为，好奇心是由内在驱动的。好奇心涵盖了一系列广泛的行为，因此可能并不存在单一的"好奇心基因"来促使人类对环境产生好奇并进行探索。即便如此，好奇心确实带有基因层面的因素。基因和环境以多种复杂的方式相互作用，塑造个体并引导其行为，其中也包括好奇心。无论基因构成如何，婴儿都必须在短时间内学习海量信息，而好奇心是人类发现的完成这一艰巨任务的工具之一。数百项研究表明，婴儿偏爱新奇事物。这一特质促使非人类动物、人类婴儿，或许还有成年人去探索和寻找新事物，而后随着接触增多，对这些事物的兴趣会逐渐降低。但好奇心往往是有代价的。在某些情况下，风险较低，失败是成长中有益的一部分。例如，许多婴儿爬行已经非常熟练，但他们还是决定尝试走路，因为直立行走能看到更多东西、做更多事。但这一里程碑的达成伴随着小小的代价。一项针对12至19个月大学习走路的婴儿的研究记录显示，这些孩子经常摔倒——确切地说，每小时摔17次。但走路比爬行快，这就促使爬行高手们转而学习走路。然而，有时尝试新想法可能会导致灾难。例如，北极地区的因纽特人创造了令人难以置信的方式来应对北方气候的挑战，但我们忘记了成千上万试图在这些充满挑战的环境中生存却失败的人。【缺少答案，请补充】

What does the author say about curiosity? (作者认为好奇心是怎样的？)

What is the general understanding of curiosity? (对好奇心的普遍认知是什么？)

What do we learn about how genes shape people's behavior? (关于基因如何塑造人类行为，我们能了解到什么？)

What do numerous studies show about infants? (众多研究表明婴儿有什么特点？)

What does the example of the Inuit people of the Arctic regions illustrate? (北极地区因纽特人的例子说明了什么？)

What do we learn about the scientists trying to raise money online for their projects? (关于试图为项目在线筹款的科学家，我们能了解到什么？)

What do we learn about the scientists trying to raise money online for their projects? 关于试图为项目在线筹款的科学家，我们能了解到什么？

What is the purpose of Mike Schäfer's research of recent crowdfunding campaigns? 迈克·舍费尔对近期众筹活动的研究目的是什么？

What trait contributes to the success of a crowdfunding campaign? 什么特质有助于众筹项目的成功？

What did the researchers think of the financial targets of crowdfunding projects? 研究人员如何看待众筹项目的财务目标？

What motivates people to donate in a crowdfunding campaign? 是什么促使人们在众筹活动中捐款？

Professor Ashok Goel of Georgia Tech developed an artificially intelligent teaching assistant to help handle the enormous number of student questions in the online class, Knowledge-Based Artificial Intelligence. This online course is a core requirement of Georgia Tech's online Master of Science in Computer Science program. Professor Goel already had 8 teaching assistants, but that wasn't enough to deal with the overwhelming number of questions from students. Many students drop out of online courses because of the lack of teaching support. When students feel isolated or confused and reach out with questions that go unanswered, their motivation to continue begins to fade. Professor Goel decided to do something to remedy the situation and his solution was to create a virtual assistant named Jill Watson, which is based on the IBM Watson platform. Goel and his team developed several versions of Jill Watson before releasing her to the online forums. At first, the virtual assistant wasn't too great. But Goel and his team scoured the online discussion forum to find all 40,000 questions that had ever been asked since the class was launched. Then they began to feed Jill the questions and answers. After some adjustments and sufficient time, Jill was able to answer the students' questions correctly 97% of the time. The virtual assistant became so advanced and realistic that the students didn't know she was a computer. The students, who were studying artificial intelligence, were interacting with the virtual assistant and couldn't tell it apart from a real human being. Goel didn't inform them about Jill's true identity until April 26th. The students were actually very positive about the experience. The goal of Professor Goel's virtual assistant next year is to take over answering 40% of all the questions posed by students on the online forum. The name Jill Watson will, of course, change to something else next semester. Professor Goel has a much rosier outlook on the future of artificial intelligence than, say, Elon Musk, Stephen Hawking, Bill Gates or Steve Wozniak. 佐治亚理工学院的阿肖克·戈尔教授开发了一款人工智能助教，以协助处理在线课程《基于知识的人工智能》中大量的学生问题。这门在线课程是佐治亚理工学院在线计算机科学硕士项目的核心必修课。戈尔教授原本已有8名助教，但仍不足以应对学生提出的海量问题。许多学生因缺乏教学支持而退出在线课程。当学生感到孤立无援或困惑不解，提出的问题又无人解答时，他们继续学习的动力就会开始消退。戈尔教授决定采取措施改变这一状况，他的解决方案是打造一个名为吉尔·沃森的虚拟助手，该助手基于IBM沃森平台开发。戈尔和他的团队在将吉尔·沃森投入在线论坛前，开发了多个版本。起初，这个虚拟助手的表现并不出色。但戈尔团队仔细查阅了在线讨论论坛，找出了课程开设以来被提出的全部4万个问题，随后开始将这些问题和答案输入给吉尔。经过一些调整和足够的训练时间，吉尔回答学生问题的正确率达到了97%。这个虚拟助手变得非常先进、逼真，以至于学生们都不知道她是一台计算机。这些学习人工智能的学生与虚拟助手互动时，根本无法将其与真人区分开。戈尔直到4月26日才告知学生们吉尔的真实身份，而学生们对这次体验的反馈其实非常积极。戈尔教授的虚拟助手明年的目标是接手回答在线论坛上40%的学生问题。吉尔·沃森这个名字下学期当然会更换。与埃隆·马斯克、史蒂芬·霍金、比尔·盖茨或史蒂夫·沃兹尼亚克等人相比，戈尔教授对人工智能的未来持更为乐观的态度。【缺少答案，请补充】

What do we learn about Knowledge-Based Artificial Intelligence? 关于《基于知识的人工智能》，我们能了解到什么？

What problem did Professor Goel meet with? 戈尔教授遇到了什么问题？

What do we learn about Jill Watson? 关于吉尔·沃森，我们能了解到什么？

How did the students feel about Jill Watson? 学生们对吉尔·沃森的感受如何？

What does Professor Goel plan to do with Jill Watson? 戈尔教授计划如何处理吉尔·沃森？