2018年12月英语四级真题 第1套

Section C
Directions: There are 2 passages in this section. Each passage is followed by some questions or unfinished statements. For each of them there are four choices marked A), B), C) and D). You should decide on the best choice and mark the corresponding letter on Answer Sheet 2 with a single line through the centre.

Passage One
Questions 46 to 50 are based on the following passage.

California has been facing a drought for many years now, with certain areas even having to pump freshwater hundreds of miles to their distribution system. The problem is growing as the population of the state continues to expand. New research has found deep water reserves under the state which could help solve their drought crisis. Previous drilling of wells could only reach depths of 1,000 feet, but due to new pumping practices, water deeper than this can now be extracted (抽取) . The team at Stanford investigated the aquifers (地下蓄水层) below this depth and found that reserves may be triple what was previously thought.
It is profitable to drill to depths more than 1,000 feet for oil and gas extraction, but only recently in California has it become profitable to pump water from this depth. The aquifers range from 1,000 to 3,000 feet below the ground, which means that pumping will be expensive and there are other concerns. The biggest concern of pumping out water from this deep is the gradual settling down of the land surface. As the water is pumped out, the vacant space left is compacted by the weight of the earth above.
Even though pumping from these depths is expensive, it is still cheaper than desalinating (脱盐) the ocean water in the largely coastal state. Some desalination plants exist where feasible, but they are costly to run and can need constant repairs. Wells are much more reliable sources of freshwater, and California is hoping that these deep wells may be the answer to their severe water shortage.
One problem with these sources is that the deep water also has a higher level of salt than shallower aquifers. This means that some wells may even need to undergo desalination after extraction, thus increasing the cost. Research from the exhaustive study of groundwater from over 950 drilling logs has just been published. New estimates of the water reserves now go up to 2,700 billion cubic meters of freshwater.

目前，加利福尼亚州已经面临干旱多年了，有些地区甚至要在几百英里之外抽淡水到其配水系统中。随着该州人口数量持续增加，干旱的问题也日益严重。[46] 新的研究已经发现了加州深层地下水储备，能够帮助解决该州的干旱危机。之前的钻井只能达到1000英尺的深度，但由于新的抽水方式，现在，更深处的淡水已经可以被抽取出来了。斯坦福大学的研究团队调研了1000英尺以下的地下蓄水层，发现水资源储备可能是之前预期的三倍。
[47] 就油气开采而言，钻探深度超过1000英尺是有利润的，但是钻探到这个深度抽水直到最近在加利福尼亚州才变得划算。地下蓄水层位于地下1000至3000英尺的地方，这意味着抽水的成本非常高昂，并且还有其他顾虑。[48] 从这么深的地方抽水最令人担忧的问题就是陆地地面的逐渐下陷。随着水被抽出来，上层土地的重量会压缩被抽空的空间。
尽管从这样的深度抽水非常昂贵，但是这也比在这个大部分地区都临海的州将海水脱盐得到淡水要更便宜。在适宜的地方是有一些海水脱盐装置的，但是要运行这些装置花费巨大，并且脱盐罐需要不断维修。[49] 井是更可靠的淡水来源，加利福尼亚州希望这些深井会是其严重的水资源短缺问题的解决方案。
[50] 这些水资源的一个问题是，深层水比较浅的蓄水层的水含盐量还是要高。这意味着有些井水被抽上来之后甚至可能也要进行脱盐处理，因此会增加成本。最近发表了一份研究报告，该报告对950多份钻井日志记录的地下水进行了全面研究。根据最新的估计，目前淡水资源储备上升到了2.7万亿立方米。

Passage Two
Questions 51 to 55 are based on the following passage.

The AlphaGo program’s victory is an example of how smart computers have become.
But can artificial intelligence (AI) machines act ethically, meaning can they be honest and fair?
One example of AI is driverless cars. They are already on California roads, so it is not too soon to ask whether we can program a machine to act ethically. As driverless cars improve, they will save lives. They will make fewer mistakes than human drivers do. Sometimes, however, they will face a choice between lives. Should the cars be programmed to avoid hitting a child running across the road, even if that will put their passengers at risk? What about making a sudden turn to avoid a dog? What if the only risk is damage to the car itself, not to the passengers?
Perhaps there will be lessons to learn from driverless cars, but they are not super-intelligent beings. Teaching ethics to a machine even more intelligent than we are will be the bigger challenge.
About the same time as AlphaGo’s triumph, Microsoft’s ‘chatbot’ took a bad turn. The software, named Taylor, was designed to answer messages from people aged 18-24. Taylor was supposed to be able to learn from the messages she received. She was designed to slowly improve her ability to handle conversations, but some people were teaching Taylor racist ideas. When she started saying nice things about Hitler, Microsoft turned her off and deleted her ugliest messages.
AlphaGo’s victory and Taylor’s defeat happened at about the same time. This should be a warning to us. It is one thing to use AI within a game with clear rules and clear goals. It is something very different to use AI in the real world. The unpredictability of the real world may bring to the surface a troubling software problem.
Eric Schmidt is one of the bosses of Google, which owns AlphaGo. He thinks AI will be positive for humans. He said people will be the winner, whatever the outcome. Advances in AI will make human beings smarter, more able and “just better human beings.”

[51] 阿尔法围棋程序的胜利是计算机已经变得十分智能的一个例子。
[52] 但是人工智能(AI)机器的行为能合乎道德规范吗？也就是说，它们能诚实而公正吗？
人工智能的一个例子就是无人驾驶汽车。它们已经行驶在加利福尼亚州的道路上了，所以现在询问我们能否为机器编程让其行为符合道德规范并非为时尚早。随着无人驾驶汽车的改良，它们将能够挽救生命。它们会比人类司机犯的错误更少。[52] 但是，有时它们会面临生命的抉择。这些汽车是否应该被编程去避开一个突然冲出马路的小孩，即使这样做会将车上的乘客置于危险之中？为了避免撞到一条狗要进行急转弯怎么办？如果风险只是车辆本身会有损坏，但是乘客不会有危险呢？
也许会有从无人驾驶汽车身上学习的教训，但是它们不是超级智能的生物。[53] 教一台甚至比我们还要智能的机器道德规范将会是更大的挑战。
[54] 大概在阿尔法围棋胜利的同时，微软的“聊天机器人”的情况却开始向坏的方向发展。这款软件被命名为泰勒，被设计用来回复18到24岁之间的年轻人发来的消息。泰勒应该能从她收到的消息中学习。[54] 最初的设计是，她能够慢慢地增强处理对话的能力，但是有些人教给泰勒种族主义观念。当她开始为希特勒说一些好话的时候，微软将其关掉并删除了她最令人厌恶的消息。
阿尔法围棋的胜利和泰勒的失败差不多是同时发生的。这对我们来说应该是一个警示。在有着清晰的规则和明确的目标的比赛中使用人工智能是一回事。在真实世界中使用人工智能是另外一回事。真实世界的不可预测性可能会使棘手的软件问题浮出水面。 埃里克·施密特是谷歌的老板之一，谷歌即阿尔法围棋程序的拥有者。[55] 他认为人工智能将会对人类有益。他说，无论结果如何，人类都将是赢家。人工智能的发展进步将会使人类更加聪明，更有能力，并且“只会成为更好的人类”。