未来面试要刷脸测性格英语美文

时间:2018-08-14 面试英语 我要投稿

  So-called emotion recognition technology is in its infancy. But artificial intelligence companies claim it has the power to transform recruitment.

  所谓的情感识别技术还处于早期发展阶段。但是人工智能公司声称,这项技术完全有可能改变招聘的模式。

  Their algorithms, they say, can decipher how enthusiastic, bored or honest a job applicant may be — and help employers weed out candidates with undesirable characteristics. Employers, including Unilever, are already beginning to use the technology.

  这些公司指出,他们的算法可以解读求职者有多热情、多厌烦或多诚实——并且帮助雇主排除性格不太合适的应聘者。包括联合利华(Unilever)在内的雇主已经开始使用这项技术。

  London-based Human, founded in 2016, is a start-up that analyses video-based job applications. The company claims it can spot the emotional expressions of prospective candidates and match them with personality traits — information its algorithms collect by deciphering subliminal facial expressions when the applicant answers questions.

  互曼公司(Human)是伦敦的一家初创公司,于2016年成立。该公司主要对求职者提交的视频材料进行分析。该公司声称,它可以发现潜在候选人的情感表达,并将其与他们的性格特征——其算法通过对求职者回答问题时下意识的面部表情进行解读所收集的信息——进行比对。

  Human sends a report to the recruiter detailing candidates’ emotional reactions to each interview question, with scores against characteristics that specify how “honest” or “passionate” an applicant is.

  互曼会向招聘公司发送报告,详细说明应聘者对面试中每个问题的情绪反应,通过对照其性格特征给出评分,用于反映申请人的“诚实度”或“热情度”。

  “If [the recruiter] says, ‘We are looking for the most curious candidate,’ they can find that person by comparing the candidates’ scores,” says Yi Xu, Human’s founder and chief executive.

  互曼的创始人兼首席执行官Yi Xu指出:“如果(招聘公司)说,’我们在寻找好奇心特别强的人’,他们可以通过比较各候选人的得分来找到合适的人。”

  Recruiters can still assess candidates at interview in the conventional way, but there is a limit to how many they can meet or the number of video applications they can watch. Ms Xu says her company’s emotion recognition technology helps employers screen a larger pool of candidates and shortlist people they may not have considered otherwise.

  招聘公司仍然可以采用传统的面试方式来评估候选人,但他们可以面谈的人数或观看视频申请的数量是有限的。Yi Xu说,互曼公司的情感识别技术可以帮助雇主筛查更多的候选人,并筛选出他们通过其他面试方式可能不会考虑的候选人。

  “An interviewer will have bias, but [with technology] they don’t judge the face but the personality of the applicant,” she says. One aim, she claims, is to overcome ethnic and gender discrimination in recruitment.

  她说:“面试官会有偏见,但(采用技术后),他们就不会依据外表来评判申请人,而是会依据他们的性格。”她声称,这项技术的目标之一就是克服招聘过程的种族和性别歧视。

  The algorithms of Affectiva and Human are based at least partially on Facs. A specialist first labels the emotions of hundreds or thousands of images (videos are analysed frame by frame), before letting an algorithm process them — the training phase.

  Affectiva和互曼这两家公司的算法都至少部分基于FACS系统。一位专家首先要对成百上千张图像(视频分析需要一帧一帧地进行)中人脸所流露的情绪进行标记,然后让算法进行处理——这是训练阶段。

  During training, the algorithm is watched to see how closely it predicts emotions compared with the manual labelling done by the Facs specialist. Errors are taken into account and the model adjusts itself. The process is repeated with other labelled images until the error is minimised.

  在训练过程中,要对算法进行观察,看看其对情绪的预测结果与FACS专家所做的手动标记有多接近。模型会根据发现的错误自行进行调整。用其他已标记的图像重复这一过程,直到差错降到尽可能低的水平。

  Once the training is done, the algorithm can be introduced to images it has never seen and it makes predictions based on its training.

  训练完成后,可以用算法来观察其从未见过的图像,并根据之前的训练进行预测。

  Frederike Kaltheuner, policy adviser on data innovation at Privacy International, a global campaigning organisation, agrees that human interviewers can be biased. But she says: “new systems bring new problems”.

  “隐私国际”(Privacy International)数据创新方面的政策顾问弗雷德里克.卡尔特霍伊纳(Frederike Kaltheuner)同意人类面试官可能会有偏见,但她说:“新系统会带来新问题”。


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