How to Tackle Recruiter Bias Using AI [Infographic]

Written by brianwallace | Published 2021/02/07
Tech Story Tags: diversity | tech-diversity | unconscious-bias | artificial-intelligence | technology | infographic | recruiting | hr

TLDR AI recruiting programs are built from the hiring data of human recruiters. Special care must be taken to ensure the data does not contain the biases of the human recruiter. Amazon’s recruiting AI accidentally learned to favor male applicants because of its programming based on ten years of human recruitment processes, resumes, and hiring data. Unbiased recruiting AI also improves a candidates experience by matching them to companies where they will truly be a good fit. Learn more about how AI can combat recruiting bias and the benefits of a diverse company in this infographic.via the TL;DR App

Implicit bias in the hiring process harms efforts to build a diverse employee base of different opinions, ideas, and methods. Which, in turn, harms a company’s success. In the past, recruiters have favored candidates with traits in common to themselves, made quick judgements based on first impressions, and allowed contrasts to other candidates to affect their opinions. Recruiting software and artificial intelligence have been used as an attempt to streamline the recruitment process, but often the technology ends up adapting similar biases to those of the human recruiters. 
Some believe that the key to hacking the recruitment process is to use an AI programmed with unbiased data.
Because AI recruiting programs are built from the hiring data of human recruiters, special care must be taken to ensure the data does not contain the biases of the human recruiter, which could then be transferred to the AI.
For example, Amazon’s recruiting AI accidentally learned to favor male applicants because of its programming based on ten years of human recruitment processes, resumes, and hiring data. If the AI is trained with biased patterns, it will repeat and exaggerate those patterns. Ultimately if it is programmed with biased data, it will continuously harm efforts to value diverse candidates. 
To train an AI without using flawed data a few different practices should be used. These practices will allow you to hack the recruitment process, having a quick and fair approach to hiring using unbiased AI. Using hiring data from a wide variety of resumes and companies as well as valuing factors like a candidate’s skills and interests helps program an unbiased AI. Taking information like age, gender, and names out of the AI’s data also helps to eliminate bias based on these factors.  
Using an unbiased recruiting AI can instantly help a company increase their diversity and success in the recruiting process. Unbiased recruiting AI also improves a candidates experience by matching them to companies where they will truly be a good fit. Learn more about how AI can combat recruiting bias and the benefits of a diverse company in this deep dive below:

Written by brianwallace | Founder @ NowSourcing | Contributor at Hackernoon | Advisor: Google Small Biz, SXSW
Published by HackerNoon on 2021/02/07