Advances in artificial intelligence and the u...

Advances in artificial intelligence and the use of big data are changing the way many large companies recruit (招募) entry level and junior management positions. These days, graduates’ CVs may well have to impress an algorithm (算法) rather than an (human resources) manager.

While algorithms supposedly treat each application equally, experts are divided about whether so-called robo-recruitment promises an end to human prejudice in the selection process —or whether it may in fact add to it.

“AI systems are not all equal,” says Loren Larsen, chief technology officer for HireVue, which has developed an automated video interview analysis system. “I think you have to look at the science team behind the work,” says Mr Larsen.

The problem, experts say, is that to find the best candidates an algorithm has first to be told what “good” looks like in any given organization. Even if it is not given criteria that seem discriminatory, a powerful machine-learning system will quickly be able to copy the characteristics of existing workers. If an organization has favoured white male graduates from well-known universities, the algorithm will learn to select more of the same.

The growing dependence on automation to judge suitability for everything from a loan to a job worries Yuriy Brun, an associate professor specializing in software engineering. “It takes a lot of the time for a company to put out software but it doesn’t know if it is discriminatory” he says. Prof Brun explains that, considering the use of big data, algorithms will unavoidably learn to discriminate.

Many of those working with robo-recruiters are more optimistic. Kate Glazebrook, the leader and co-founder of Applied, a hiring platform, says her task is to encourage hiring manager to move away from such indicators of quality as schools or universities and move to more evidence-based methods. When candidates complete tests online, Applied hides their names and shows the tests the candidates have completed, question by question, to human assessors. Every stage of the process has been designed to remove prejudice.

With the same aim, Unilever decided in 2016 to switch to a more automated process for its graduate-level entry programme. Unilever worked with HireVue, Amberjack, which provides and advises on automated recruitment processes, and Pymetrics, another high volume recruitment company, which developed a game-based test in which candidates are scored on their ability to take risks and learn from mistakes, as well as on emotional intelligence. Unilever says the process has increased the ethnic diversity of its listed candidates and has been more successful at selecting candidates who will eventually be hired.

“The things that we can do right now are impressive, but not as impressive as we’re going to be able to do next year or the year after,” says Mr Larsen.

Still, robo-recruiters must be regularly tested in case prejudice has occurred without anyone realizing it, says Frida Polli, the leader and co-founder of Pymetrics. “The majority of algorithmic tools are most likely causing prejudice to continue existing. The good ones should be examined.”

1.What’s the purpose of adopting automated recruitment processes according to the passage?

A. For the sake of fairness.

B. For the purpose of cutting down costs.

C. To relieve the pressure of staff.

D. To favor graduates from well-known universities.

2.The automated process Unilever adopted in 2016 for its graduate-level entry programme ________.

A. was found to have prejudice

B. was copied by many other companies

C. scored the candidates on their ethnic backgrounds

D. turned out to be less or not racially discriminatory

3.According to Mr Larsen, robo-recruitment ________.

A. is good enough for wide use now

B. is not suitable for practical use now

C. will do better and better in the near future

D. will completely replace HR staff within two years

4.Frida Polli stresses in the last paragraph that algorithmic tools ________.

A. need routine checks

B. will unavoidably have prejudice

C. are mostly good and effective

D. must be combined with human staff

高二英语阅读理解中等难度题查看答案及解析

Rapid progress in artificial intelligence, also called AI, and the wide use of robots across different industries are causing the worry about the growth in joblessness. People have different opinions on this development, and they mainly have focused on what to do to make sure that robots don't steal jobs.

Bill Cates, for example, have called for taxing(对…征税)robots that take away jobs. This has led to disagreement from other leading figures, such as Larry Summers, who thinks that robots are job creators and that it is totally wrong. Another idea is to use a basic income for all-the ides that everyone receives the lowest income-to pay for influence of technological unemployment. This idea also causes disagreement.

However, jobs are not created or lost because of a single technology, but because of the business system designed to make use of the power of the technology.

We have seen a similar example in history, with recorded music in the last century. It wasn't the 1930s recording technology itself that affected the jobs of the live musicians. It was its connection with radio broadcasting，jukeboxes(自动唱机)and the way businesses operated that led to the job losses. Hotels, restaurants and bars replaced live musicians with jukeboxes. A single recording could be placed over and over without requiring the appearance of the musicians.

The early recording of music destroyed the jobs of some live musicians and made them earn less money than before. The social dissatisfaction was largely about monopoly power(垄断势力)and less about the technology itself.

Job creation or loss has to be considered with everything considered. This is the best explained by looking at the difference between recorded music in the last century and robots now.

1.What's people's main attention according to the first paragraph?

A.Artificial intelligence. B.The growing opportunities.

C.Not letting robots take away jobs. D.Stopping the wide use of robots.

2.What does the underlined word "it" in paragraph 2 refer to?

A.The idea of taxing robots. B.The belief that robots steal jobs.

C.Rapid progress in artificial intelligence. D.Disagreement between leading figures.

3.What can we know about Larry Summers?

A.He agrees with Bill Gates' opinion. B.He thinks robots can create jobs.

C.He supports the idea of taxing robots. D.He praises using a basic income for all

4.What can we infer from the last two paragraphs?

A.There will be more social dissatisfaction in the future.

B.Monopoly power is a terrible social phenomenon.

C.We should tell job creation or loss with full consideration.

D.Recorded music is completely different from robots.

高二英语阅读理解困难题查看答案及解析

短文改错

With the development of science and technology, intelligent robots will be wide used in the future. At home, robots will help people do some housework and taking care of the elderly, babies and patients. In addition to these task, robots will even be able to play the chess and do exercise with people. In factories, robots will be used to perform some dangerous jobs avoid accidents. Robots will change our future life by many ways, what will make it more colorful and comfortable. Therefore, we shouldn’t depend on intelligent robots too much, for they were made to help humans rather than replace us. As helpers of we humans, robots should be used properly.

高二英语短文改错中等难度题查看答案及解析

Learning, Fast and Deep

Over the past five years researchers in artificial intelligence have become the rock stars of the technology world. A branch of AI known as deep learning, which uses neural(神经的) networks to scan through large volumes of data looking for patterns, has proven so useful that skilled practitioners can command high six-figure salaries to build software for Amazon, Apple, Facebook and Google.

The standard route into these jobs has been a PhD in computer science from one of America’s top universities. Earning one takes years and requires a personality suited to academia, which is rare among more normal folk.

That is changing.

Last month fast.ai, a non-profit education organization based in San Francisco, kicked off the third year of its course in deep learning. Since its foundation it has attracted more than 100,000 students around the globe from India to Nigeria. The course and others like it, come with a simple idea: there is no need to spend years obtaining a PhD in order to practise deep learning. Creating software that learns can be taught as a craft, not as a high intellectual pursuit to be undertaken only in an ivory tower. Fast.ai’s course can be completed in just seven weeks.

To make it accessible to anyone who wants to learn how to build AI software is the aim of Jeremy Howard, who founded fast.ai with Rachel Thomas, a mathematician. He says school mathematics is sufficient. “No. Greek. Letters,” Mr. Howard intones, pounding the table with his fist for punctuation.

Some experts worry that this will serve only to create a flood of unreliable AI systems which will be useless at best and dangerous at worst. In the earliest days of the Internet, only a select few nerds, namely computerholics with specific skills, could build applications. Not many people used them. Then the invention of the World Wide Web led to an explosion of web pages, both good and bad. But it was only by opening up to all that the Internet gave birth to online shopping, instant global communications and search. If Mr. Howard and others have their way, making the development of AI software easier will bring forth a new crop of fruit of a different kind.

1.What can we learn about deep learning?

A.It replaces artificial intelligence.

B.It attracts rock stars to practice.

C.It scans patterns for large companies.

D.It helps technicians to create software.

2.Fast.ai is an organization that __________________.

A.ensures one to obtain a PhD B.teaches craft in ivory tower

C.offers a course in deep learning D.requires weeks to apply

3.The underlined words “No. Greek. Letters”in Paragraph 5 means doing fast.ai course is _______.

A.easy B.difficult

C.interesting D.boring

4.It can be inferred from the last paragraph that _______.

A.it is quite reliable for anyone to grasp artificial intelligence

B.the Internet has brought forth a flood of useless AI systems

C.opening up to all leads to instant global search and online shopping

D.simplifying software development may result in unexpected outcomes

高二英语阅读理解中等难度题查看答案及解析

Let us all raise a glass to AlphaGo and the advance of artificial　 intelligence. AlphaGo，

DeepMind’s Go-playing AI，just defeated the best Go-playing human，Lee Sedol. But as we drink to its success. we should also begin trying to understand what it means for the future.

The number of possible moves in a game of Go is so huge that. in order to win against a player like Lee. AlphaGo was designed to adopt a human—like style of gameplay by using a relatively recent development--deep learning. Deep learning uses large data sets，“machine learning”algorithms （计算程序） and deep neural networks to teach the AI how to perform a particular set of tasks. Rather than programming complex Go rules and strategies into AlphaGo，DeepMind designers taught AlphaGo to play the game by feeding it data based on typical Go moves. Then，AlphaGo played against itself, tirelessly learning from its own mistakes and improving its gameplay over time. The results speak for themselves.

Deep learning represents a shift in the relationship humans have with their technological creations. It results in AI that displays surprising and unpredictable behaviour. Commenting after his first loss，Lee described being shocked by an unconventional move he claimed no human would ever have made. Demis Hassabis. one of DeepMind's founders，echoed this comment：“We're very pleased that AlphaGo played some quite surprising and beautiful moves. ”

Unpredictability and surprises are—or can be—a good thing. They can indicate that a system is working well，perhaps better than the humans that came before it. Such is the case with AlphaGo. However，unpredictability also indicates a loss of human control. That Hassabis is surprised at his creation's behaviour suggests a lack of control in the design. And though some loss of control might be fine in the context of a game such as Go，it raises urgent questions elsewhere.

How much and what kind of control should we give up to AI machines? How should we design appropriate human control into AI that requires us to give up some of that very control? Is there some AI that we should just not develop if it means any loss of human control? How much of a say should corporations，governments，experts or citizens have in these matters? These important questions, and many others like them，have emerged in response，but remain unanswered. They require human，not human - like，solutions.

So as we drink to the milestone in AI, let's also drink to the understanding that the time to answer deeply human questions about deep learning and AI is now.

1.What contributes most to the unconventional move of AlphaGo in the game?

A. The capability of self-improvement.

B. The constant input of large data sets.

C. The installation of deep neutral networks.

D. The knowledge of Go rules and strategies.

2.A potential danger of Al is _____.

A. the loss of human control　　 B. the friendly relationship

C. the fierce competition　　 D. the lack of challenge

3.How should we deal with the unpredictability of AI?

A. We should stop AI machines from developing even further.

B. We should call on the government to solve these problems for us.

C. We should rely on ourselves and come up with effective solutions.

D. We should invent even more intelligent machines to solve everything.

4.What's the author’s attitude towards this remarkable advance in AI?

A. Supportive.　　 B. Optimistic.

C. Doubtful.　　 D. Cautious.

高二英语阅读理解中等难度题查看答案及解析

Let us all raise a glass to AlphaGo and the advance of artificial　 intelligence. AlphaGo，

DeepMind’s Go-playing AI，just defeated the best Go-playing human，Lee Sedol. But as we drink to its success. we should also begin trying to understand what it means for the future.

The number of possible moves in a game of Go is so huge that. in order to win against a player like Lee. AlphaGo was designed to adopt a human—like style of gameplay by using a relatively recent development--deep learning. Deep learning uses large data sets，“machine learning”algorithms （计算程序） and deep neural networks to teach the AI how to perform a particular set of tasks. Rather than programming complex Go rules and strategies into AlphaGo，DeepMind designers taught AlphaGo to play the game by feeding it data based on typical Go moves. Then，AlphaGo played against itself, tirelessly learning from its own mistakes and improving its gameplay over time. The results speak for themselves.

Deep learning represents a shift in the relationship humans have with their technological creations. It results in AI that displays surprising and unpredictable behaviour. Commenting after his first loss，Lee described being shocked by an unconventional move he claimed no human would ever have made. Demis Hassabis. one of DeepMind's founders，echoed this comment：“We're very pleased that AlphaGo played some quite surprising and beautiful moves. ”

Unpredictability and surprises are—or can be—a good thing. They can indicate that a system is working well，perhaps better than the humans that came before it. Such is the case with AlphaGo. However，unpredictability also indicates a loss of human control. That Hassabis is surprised at his creation's behaviour suggests a lack of control in the design. And though some loss of control might be fine in the context of a game such as Go，it raises urgent questions elsewhere.

How much and what kind of control should we give up to AI machines? How should we design appropriate human control into AI that requires us to give up some of that very control? Is there some AI that we should just not develop if it means any loss of human control? How much of a say should corporations，governments，experts or citizens have in these matters? These important questions, and many others like them，have emerged in response，but remain unanswered. They require human，not human - like，solutions.

So as we drink to the milestone in AI, let's also drink to the understanding that the time to answer deeply human questions about deep learning and AI is now.

1.What contributes most to the unconventional move of AlphaGo in the game?

A. The capability of self-improvement.

B. The constant input of large data sets.

C. The installation of deep neutral networks.

D. The knowledge of Go rules and strategies.

2.A potential danger of Al is _____.

A. the loss of human control　　 B. the friendly relationship

C. the fierce competition　　 D. the lack of challenge

3.How should we deal with the unpredictability of AI?

A. We should stop AI machines from developing even further.

B. We should call on the government to solve these problems for us.

C. We should rely on ourselves and come up with effective solutions.

D. We should invent even more intelligent machines to solve everything.

4.What's the author’s attitude towards this remarkable advance in AI?

A. Supportive.　　 B. Optimistic.

C. Doubtful.　　 D. Cautious.

高二英语阅读理解困难题查看答案及解析

“Data is the new oil.” Like the sticky black thing, all those Is and 0s are of little use until they are processed into something more valuable. That something is you.

Five of the world’s ten most valuable companies are built on a foundation of tying data to human beings. Google and Facebook want to find out as much as possible about their users’ interests, activities, friends and family. Amazon has a detailed history of consumer behavior. Tencent and Alibaba are the digital wallets for hundreds of millions of Chinese; both know enough about consumers to provide widely used credit scores. Those with a good Zhima credit score, provided by Alibaba, enjoy discounts. Those without receive few offers. In other words, data are used to decide what sort of access people have to services.

That data are valuable is increasingly well-understood by individuals, too, especially because personal information is so often leaked（泄露）or stolen. The list of companies that have suffered some sort of data leak in 2018 alone reads like a roll call of household names: Facebook, Google, British Airways and so on. Such events have caused a switch in the public understanding of data collection. People have started to take notice of all the data they are giving away.

Yet few people have changed their online behavior or exercised what few digital rights they possess. Partly this is because managing your own data is time-consuming and complex. But it is more because of a misunderstanding of what is at risk. “Data” is an abstract concept. Far more solid is the idea of identity. It is only when “data” is understood to mean “people” that individuals will demand responsibility from those who seek to know them.

The fossils of past actions fuel future economic and social outcomes. Privacy rules and data-protection regulations are extremely important in protecting the rights of individuals. But the first step towards ensuring the fairness of the new information age is to understand that it is not data that are valuable. It is you.

1.The example of Zhima credit scores is mentioned to show __________.

A.data help companies target their services

B.credit scores change people’s way of life

C.Alibaba gains popularity among customers

D.people prefer to be offered discounts

2.What has caused a change in the public understanding of data collection?

A.The development of companies. B.The history of consumption.

C.Cases of data leak and theft. D.Lists of household names.

3.People don’t protect their data well mainly because __________.

A.they find it time-consuming and complex

B.they are not fully aware of its importance

C.they have no access to their personal data

D.they are afraid of taking responsibility

4.What is the author’s purpose in writing the text?

A.To defend companies’ use of data.

B.To show the economic value of data.

C.To call for more regulations to protect data.

D.To advocate a new way of thinking about data.

高二英语阅读理解困难题查看答案及解析

Many leading AI researchers think that in a matter of decades, artificial intelligence will be able to do not merely some of our jobs, but all of our jobs, forever transforming life on Earth.

The reason why many regard this as science fiction is that we've traditionally thought of intelligence as something mysterious that can only exist in biological organisms, especially humans. But such an idea is unscientific.

From my point of view as a physicist and AI researcher, intelligence is simply a certain kind of information-processing performed by elementary particles (基本粒子) moving around, and there is no law of physics that says one can't build machines more intelligent than us in all ways. This suggests that we've only seen the tip of the intelligence iceberg and that there is an amazing potential to unlock the full intelligence that is potential in nature and use it to help humanity.

If we get it right, the upside is huge. Since everything we love about civilization is the product of intelligence, amplifying (扩大) our own intelligence with AI has the potential to solve tomorrow's toughest problems. For example, why risk our loved ones dying in traffic accidents that self-driving cars could prevent or dying of cancers that AI might help us find cures for? Why not increase productivity through automation (自动化) and use AI to accelerate our research and development of affordable sustainable (可持续的) energy?

I'm optimistic that we can develop rapidly with advanced AI as long as we win the race between the growing power of our technology and the knowledge with which we manage it. But this requires giving up our outdated concept of learning form mistakes. That helped us win the race with less powerful technology: We messed up with fire and then invented fire extinguishers (灭火器), and we messed up with cars and then invented seat belts. However, it's an awful idea for more powerful technologies, such as nuclear weapons or superintelligent AI—where even a single mistake is unacceptable and we need to get things right the first time.

1.How do many people feel about leading AI researchers' predictions?

A.Worried. B.Curious. C.Doubtful. D.Disappointed.

2.What does the author think of intelligence?

A.We know little about it. B.It belongs to human beings.

C.It is too difficult to understand. D.We have nothing more to discover.

3.What does the underlined word “upside” in Paragraph 4 probably mean?

A.Cost. B.Risk. C.Quantity. D.Advantage.

4.What's important for us in the race between people and technology?

A.Learning from failure. B.Increasing our intelligence.

C.Avoiding making mistakes. D.Being more optimistic.

高二英语阅读理解中等难度题查看答案及解析

Many leading AI researchers think that in a matter of decades, artificial intelligence will be able to do not merely some of our jobs, but all of our jobs, forever transforming life on Earth.

The reason why many reject this as science fiction is that we’ve traditionally thought of intelligence as something mysterious that can only exist in biological organisms, especially humans. But such an idea is unscientific.

From my point of view as a physicist and AI researcher, intelligence is simply a certain kind of information-processing performed by elementary particles(基本粒子) moving around, and there is no law of physics that says one can’t build machines more intelligent than us in all ways. This suggests that we’ve only seen the tip of the intelligence iceberg and that there is an amazing potential to unlock the full intelligence that is potential in nature and use it to help humanity.

If we get it right, the upside is huge. Since everything we love about civilization is the product of intelligence, amplifying(扩大) our own intelligence with AI has the potential to solve tomorrow’s toughest problems. For example, why risk our loved ones dying in traffic accidents that self-driving cars could prevent or dying of cancers that AI might help us find cures for? Why not increase productivity through automation and use AI to accelerate our research and development of affordable sustainable(可持续的) energy?

I’m optimistic that we can develop rapidly with advanced AI as long as we win the race between the growing power of our technology and the knowledge with which we manage it. But this requires giving up our outdated concept of learning from mistakes. That helped us win the race with less powerful technology: We messed up with fire and then invented fire extinguishers, and we messed up with cars and then invented seat belts. However, it’s an awful idea for more powerful technologies, such as nuclear weapons or superintelligent AI—where even a single mistake is unacceptable and we need to get things right the first time.

1.How do many people feel about leading AI researchers’ predictions?

A. Acceptable　　 B. Curious

C. Doubtful　　 D. Disappointed

2.What does the author think of intelligence?

A. We know little about it.　　 B. It belongs to human beings.

C. It is too difficult to understand.　　 D. We have a good command of it.

3.What does the underlined word “upside” in Paragraph 4 probably mean?

A. Cost.　　 B. Potential.

C. Quantity.　　 D. Advantage.

4.What’s important for us in the race between people and technology?

A. Learning from failure.　　 B. Increasing our intelligence.

C. Avoiding making mistakes.　　 D. Making accurate predictions.

高二英语阅读理解中等难度题查看答案及解析

Artificial intelligence, or AI, has been applied in a wide range of fields to perform specific tasks, including education, finance, heavy industry, transportation, and so on.

Education

There are a number of companies that create robots to teach subjects to children ranging from biology to computer science, though such tools have not become widespread yet. Advancements in natural language processing, combined with machine learning, have also enabled automatic grading of assignments. AI has also led to an explosion in popularity of MOOCs, or Massive Open Online Courses, which allows students from around the world to take classes online.

Finance

Use of AI in banking can be tracked back to 1987. Banks use artificial intelligence systems to organize operations, maintain book-keeping, invest in stocks, and manage properties. Also, systems are being developed, like Atria, to translate complex data into simple and personable language. There are also wallets, like Wallet AI, which monitor an individual’s spending habits and provides ways to improve them.

Heavy industry

Robots have become common in many industries and are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to failure in concentration and other jobs which humans may find degrading.

Transportation

Today’S cars can have AI-based driver assist features such as self-parking and advanced cruise controls. AI in transportation is expected to provide safe, efficient, and reliable transportation while minimizing the impact on the environment and communities.

Toys and games

Companies like Mattel have been creating AI-enabled toys for kids as young as age three. Using proprietary AI engines and speech recognition tools, they are able to understand conversations, give intelligent responses and learn quickly. AI has also been applied to video games, for example video game bots, which are designed to stand in as opponents where humans aren’t available or desired.

1.Which is true about AI and education?

A.Robots have been widely used to teach children.

B.AI has been used to grade students’ homework.

C.AI has enabled more students to receive education at school.

D.Education was the first field where A1 was used.

2.Which can be inferred from the passage?

A.Atria can help people understand complex data.

B.Wallet AI can help people make more money.

C.Robots’ jobs are considered dangerous to humans.

D.Robots can help people concentrate.

3.From the last two paragraphs we can know that_______________.

A.Today’s drivers needn’t learn to park their cars

B.AI ensures safe, efficient, and reliable transportation

C.AI-enabled toys is designed to improve kids’ intelligence

D.Video game bots can fight against you in video games

4.What is the passage mainly about?

A.The latest progress in AI. B.AI is of great use.

C.Some applications of AI. D.AI is used in all fields.

高二英语阅读理解简单题查看答案及解析