题目内容：

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