導讀:人臉識別技術能讓我們支付午餐費、解鎖手機——它甚至能把我們送進監獄?，F如今，這項技術還在不斷發展：算法不僅可以學會認識我們是誰，還可以知道我們的所感所想。近期，人工智能公司聲稱，這項技術完全有可能改變招聘的模式。AI如何識別求職者的性格呢？本文會給出你答案。
So-called emotion recognition technology is in its infancy. But artificial intelligence companies claim it has the power to transform recruitment.
所謂的情感識別技術還處于早期發展階段。但是人工智能公司聲稱，這項技術完全有可能改變招聘的模式。
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.
這些公司指出，他們的算法可以解讀求職者有多熱情、多厭煩或多誠實——并且幫助雇主排除性格不太合適的應聘者。包括聯合利華(Unilever)在內的雇主已經開始使用這項技術。
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)是倫敦的一家初創公司，于2016年成立。該公司主要對求職者提交的視頻材料進行分析。該公司聲稱，它可以發現潛在候選人的情感表達，并將其與他們的性格特征——其算法通過對求職者回答問題時下意識的面部表情進行解讀所收集的信息——進行比對。
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.
互曼會向招聘公司發送報告，詳細說明應聘者對面試中每個問題的情緒反應，通過對照其性格特征給出評分，用于反映申請人的“誠實度”或“熱情度”。
“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.
互曼的創始人兼首席執行官Yi Xu指出：“如果（招聘公司）說，’我們在尋找好奇心特別強的人’，他們可以通過比較各候選人的得分來找到合適的人?！?/p>
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傳統的面試方式來評估候選人，但他們可以面談的人數或觀看視頻申請的數量是有限的。Yi Xu說，互曼公司的情感識別技術可以幫助雇主篩查更多的候選人，并篩選出他們通過其他面試方式可能不會考慮的候選人。
“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.
她說：“面試官會有偏見，但（采用技術后），他們就不會依據外表來評判申請人，而是會依據他們的性格?！彼暦Q，這項技術的目標之一就是克服招聘過程的種族和性別歧視。
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和互曼這兩家公司的算法都至少部分基于FACS系統。一位專家首先要對成百上千張圖像（視頻分析需要一幀一幀地進行）中人臉所流露的情緒進行標記，然后讓算法進行處理——這是訓練階段。
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.
在訓練過程中，要對算法進行觀察，看看其對情緒的預測結果與FACS專家所做的手動標記有多接近。模型會根據發現的錯誤自行進行調整。用其他已標記的圖像重復這一過程，直到差錯降到盡可能低的水平。
Once the training is done, the algorithm can be introduced to images it has never seen and it makes predictions based on its training.
訓練完成后，可以用算法來觀察其從未見過的圖像，并根據之前的訓練進行預測。
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”.
“隱私國際”(Privacy International)數據創新方面的政策顧問弗雷德里克.卡爾特霍伊納(Frederike Kaltheuner)同意人類面試官可能會有偏見，但她說：“新系統會帶來新問題”。
