Research questions AI recruitment services amidst market growth

Why we write about this topic:

The development of artificial intelligence recruitment systems is becoming a market trend in many companies; therefore, discussing the applicability and reliability of such tools is relevant.

The University of Cambridge published a study alarming about the flourishing market of artificial intelligence recruitment services. Researchers from the Centre for Gender Studies of the British school claim that AI recruitment tools may generate more “uniformity” than “diversity,” so the university in a press release. 

AI computer recruiters are more commonly adopted nowadays to exclude human resource bias and incentive more variety in the workplace. For instance, racism, sexism, and other possible gender and ethnicity tendencies aim to be eliminated by such devices. The algorithms behind this technology analyze some of the interviewee’s features, like facial expressions, to find the “ideal candidate.”  

However, according to the report published in Philosophy and Technology, artificial intelligence recruitment presents aspects of superficiality. In other words, the experts believe that AI recruiter programming simply focuses on facial features to establish personality traits. This kind of practice might highlight a company’s preconceived hiring habits even more, as reported in the study.

A model designed by the researchers, denominated as “Personality Machine,” indicated that visual elements in a candidate could directly influence the progression of a job application. The specialists affirm that AI recruitment tends to follow a company’s predetermined profiles instead of cutting out biases and preconceived ideas. In that sense, companies might diminish factors like race and gender as “data points” opposingly to a more complex social and empowerment structure. 

The study finally supports that companies should invest in recruitment training, raising questions about the actual application of AI recruitment services. They are mainly aware of the accountability of these products’ manufacturing and the lack of depth in candidate analysis. 

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