How AI can overcome human bias in hiring decisions

Bias-on-neon-sign

Artificial intelligence (AI) and machine learning are being used by enterprise human resources (HR) professionals to streamline the hiring process (as I wrote back in April). Not only can AI-powered virtual assistants “converse” with job applicants, they can schedule interviews for candidates who appear promising.

While reducing time-to-hire can help organizations fill staffing needs more quickly and save money on recruiting, smart machines may also enable enterprise HR leaders to avoid the very human pitfall of allowing conscious and unconscious biases to influence hiring decisions.

Human biases inject a corrosive element into the hiring process that can result in:

  • A reduced the talent pool (because not all qualified candidates are considered)
  • A bad hire (or at least not the right hire)
  • Lower productivity and workplace morale
  • Greater turnover, leading to higher ongoing recruitment and training costs

And all these negative outcomes arise because recruiters and interviewers have some kind of bias, large or small. Which brings us to the premise behind Eightfold.ai’s talent acquisition platform — eliminating human bias in hiring.  Eightfold.ai CEO and co-founder Ashutosh Garg writes:

The quickest path to reducing and eventually eliminating bad hiring decisions is to use machine learning to seek out candidates who most closely resemble high performers’ profiles. Using comparative analysis that goes far beyond the constraints of resumes, machine learning algorithms can in seconds find a pipeline of potential candidates that are most comparable to the digital personas of the highest achieving profiles for each position. Taking this data-driven approach to hiring also removes the potential for personal biases, both conscious and unconscious, from the decision making process. The more data-driven the hiring process, the greater the diversity every company will be able to achieve.

In other words, by going beyond the information on a person’s resume to amass data that can provide a fuller, contextual picture of a candidate and his or her skills, strengths and expertise, AI and machines can bury human biases under a mountain of relevant information.

The end results (at least ideally) are better hires, higher productivity and morale, and lower hiring and training costs. Nothing wrong with those outcomes.

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