新概念英语第一册,职场新概念英语（14）

【#新概念英语# 导语】新概念一共144课，其中单课为课文，双课为语法和练习。整本书是以单数课为正课，并附带有插图而双数课则是针对单数课所讲的内容有针对性地进行练习，展现出整个新概念一教材区别于其他教材的独特之处。©文档大全网为您整理了以下内容，仅供参考。希望可以帮助到您！如果您想要了解更多相关内容，欢迎关注©文档大全网！

【篇一】马云出席财富论坛 畅谈全球化的影响

Jack Ma, founder of Alibaba Group Holding Ltd, said that globalization will help reduce inequality as technology empowers small countries and businesses.

"In the next 30 to 40 years, globalization will empower 80 percent of countries, businesses and people that have not benefited from globalization. That's because of the power of the internet and technology," Ma said at the 2017 Fortune Global Forum held in Guangzhou, capital of Guangdong province.

"If more efforts are made to impart knowledge and know-how to small businesses, that will significantly contribute to inclusive growth," he said.

As founder of China's largest e-commerce player, Ma also addressed concerns about market freedom and monopoly as Alibaba is getting bigger in both size and influence.

"We will get bigger, but we are building an infrastructure for doing businesses. Our goal is to be an enabler that helps small businesses reach more consumers and apply technology in a very cost-effective way. We are also helping big companies such as P&G reach the rural market in China," he said.

The tech tycoon also made suggestions to foreign companies which want to better tap into the China market, adding they should be more patient about investments into the country and have a long-term commitment.

【篇二】译文

阿里巴巴集团的创始人马云日前表示，由于科技使小国家和商业团体更富有力量，全球化将会帮助减少不公平的现象。

马云在广东省省会广州市举办的2017财富全球论坛上称：“在接下来的30到40年里，全球化将会使80%原来没有从全球化中获利的国家、企业和人们获益。这源于互联网和科技的力量。”

他说道：“如果加强向小型企业传授知识和专业技术，那将会极大推动其在各方面的发展。”

作为中国的电子商务平台的创始人，马云在阿里巴巴在规模和影响力都逐渐扩大的同时，也对自由市场和垄断行为加以关注。

他表示：“我们的规模将会变得更大，但我们是为商业贸易搭建基础平台。我们的目标是有能力帮助小商业获得更多的顾客，以一种经济有效的方式提供技术。我们同样会帮助像宝洁这样的大公司进入中国乡村市场。”

此外，这位科技公司的大亨也对想要更好利用中国市场的外国公司提出了建议，并称他们应该对中国的投资更有耐心，且保持长期合作。

【篇三】机器人招聘系统的人类偏见

Advances in artificial intelligence and the use of big data are changing the way many large companies recruit for entry level and junior management positions. These days, graduates’ CVs may well have to impress an algorithm rather than an HR executive.

“There’s been a dramatic increase in the use of automation in [high] volume selection processes over the past two years,” says Sophie Meaney, managing director, client solutions and strategic development at Amberjack, which provides and advises on automated recruitment processes.

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

“AI systems are not all equal,” says Loren Larsen, chief technology officer for HireVue, which has developed an automated video interview analysis system. It has been used by companies including Unilever, the consumer goods group, Vodafone, the telecoms company, and Urban Outfitters, the retailer. “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 organisation. Even if it is not fed criteria that seem discriminatory, an efficient machine-learning system will quickly be able to replicate the characteristics of existing workers. If an organisation has favoured white male graduates from prestigious universities, the algorithm will learn to select more of the same.

The growing reliance on automation to judge suitability for everything from a loan to a job or even to probation in the criminal justice system, worries Yuriy Brun, an associate professor specialising in software engineering at the University of Massachusetts.

“A lot of the time a company will put out software but they don’t know if it is discriminatory,” he says. He points to the Compas tool in use in several US states to help assess a person’s likelihood to reoffend, which was reported to have discriminated against African Americans.

Prof Brun explains that, given the use of big data, algorithms will inevitably learn to discriminate. “People see that this is a really important problem. There’s a real danger of making things worse than they already are,” he says. His concern led him to co-develop a tool that tests systems for signs of bias.

Many of those working with robo-recruiters are more optimistic. Kate Glazebrook, chief executive of Applied, a hiring platform, says her mission is to encourage hiring managers to move away from what she calls “proxies for quality” — indicators such as schools or universities — and move to more evidence-based methods.

“In general, the more you can make the hiring process relevant, the more likely that you will get the right person for the job,” she says.

Applied anonymises tests that candidates complete online and feeds them, question by question, to human assessors. Every stage of the process has been designed to strip out bias.

With the same aim, Unilever decided in 2016 to switch to a more automated process for its graduate-level entry programme, which has about 300,000 applicants a year for 800 positions.

Unilever worked with Amberjack, HireVue 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 shortlisted candidates and has been more successful at selecting candidates who will eventually be hired.

“The things that we can do right now are stunning, but not as stunning 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 bias has crept in, says Frida Polli, chief executive of Pymetrics. “The majority of algorithmic tools are most likely perpetuating bias. The good ones should have auditing.”

【篇四】译文

人工智能(AI)的进步和大数据的使用，正在改变许多大公司招聘入门级和初级管理职位员工的方式。如今，毕业生的简历很可能不得不打动某个算法，而不是一位人力资源高管。

“过去两年里，在大流量筛选的过程中使用自动化的情况出现戏剧性增加，”Amberjack负责客户解决方案和战略发展的董事总经理索菲?米尼(Sophie Meaney)说。该公司提供自动化招聘流程以及相关咨询服务。

尽管算法理应平等对待每份申请，但在机器人招聘(robo-recruitment)将会终结遴选过程中的人类偏见、还是实际上也许会强化人类偏见的问题上，专家们看法不一。

“AI系统并非完全平等，”HireVue首席技术官洛伦?拉森(Loren Larsen)说。该公司开发出一套自动化的视频面试分析系统。包括消费品集团联合利华(Unilever)、电信运营商沃达丰(Vodafone)和零售商Urban Outfitters在内的很多公司已采用了该系统。“我认为，你必须考察一下这项工作背后的科学团队，”拉森说。

专家们表示，问题在于，要想找出候选人，首先必须告诉算法在任何一个给定组织里，“好”是什么样子。即便没有馈入似乎有成见的标准，一套高效率的机器学习系统将很快能够复制现有员工的特点。如果某个组织喜欢知名大学的白人男性毕业生，算法将学会选出更多这一类别的人。

从一笔贷款、一份工作，到刑事司法系统中的缓刑决定，在判断众多事情的合适性方面越来越依赖自动化，让马萨诸塞大学(University of Massachusetts)软件工程副教授尤里?布朗(Yuriy Brun)感到不安。

“很多时候，一家公司推出软件，却不知道软件是否有成见，”他说。他提到了美国好几个州正在使用的帮助评估一个人再犯罪可能性的Compas工具。据报道，该工具倾向于歧视非洲裔美国人。

布朗教授解释称，鉴于大数据的使用，算法将不可避免地学会歧视。“人们看到，这是一个真正重要的问题。有一种让事情变得比现在更糟糕的真实危险，”他说。这种担心导致他与人联合开发出一种检测系统偏见迹象的工具。

与机器人招聘合作的很多人更为乐观。招聘平台Applied首席执行官凯特?格莱兹布鲁克(Kate Glazebrook)表示，她的使命是鼓励招聘经理远离她所说的“质素指标”，比如学校或大学等，转向在更大程度上基于证据的方法。

“总体来说，你能让招聘流程变得越相关，你就越有可能为工作岗位找到合适人选，”她说。

Applied把候选人在线完成的测试隐去姓名，然后把所有问题逐一提供给人类评估者。整个流程每一阶段的设计都是为了剔除偏见。

带着相同目的，联合利华在2016年决定将其毕业生招聘计划转向一个自动化程度更高的流程。每年有大约30万名候选人申请该公司的800个工作岗位。

联合利华跟Amberjack、HireVue以及另一家大流量招聘公司Pymetrics合作。Pymetrics开发了一种基于游戏的测试，通过测试对候选人在承担风险和从错误中学习的能力、以及情商进行打分。

联合利华表示，这种方法提高了入围候选人名单的民族多样性，而且在遴选最终将被聘用的候选人方面更为成功。

“我们现在做得到的事情令人惊叹，但我们明年或后年能够做到的事情将会更加令人惊叹，”拉森说。

话虽如此，Pymetrics首席执行官弗里达?波利(Frida Polli)说，机器人招聘系统仍必须接受定期测试，以防偏见渗入。“大部分算法工具很可能会强化偏见。好的算法应当有审核。”

本文来源：https://www.wddqw.com/9g35.html