The algorithm is trained to identify the language, tone and facial expressions to select the best applicants by assessing their performances in the videos.
Facial expressions assessed by the algorithms include brow furrowing, brow raising, eye widening or closing, lip tightening, chin raising and smiling, which are important in sales or other public-facing jobs.
Loren Larsen, Hirevue’s chief technology officer, told The Daily Telegraph that 80 to 90 per cent of the predictive assessment was based on the algorithms’ analysis of candidates’ use of language and verbal skills.
“There are 350-ish features that we look at in language: do you use passive or active words? Do you talk about ‘I’ or ‘We.’ What is the word choice or sentence length? In doctors, you might expect a good one to use more technical language,” he said.
“Then we look at the tone of voice. If someone speaks really slowly, you are probably not going to stay on the phone to buy something from them. If someone speaks at 400 words a minute, people are not going to understand them. Empathy is a piece of that.”
