Biases are everywhere, and they dictate more than you might think: who your friends are, where you live, what you eat and who you hire. In recent years, companies have been reminded of the effect of their biases, and many have made a point to create a more inclusive working environment for everyone.
However, while this is a solid starting point, some businesses still fail to recognise (or simply underestimate) unconscious biases in the hiring and screening of candidates. In other words, an inclusion and diversity policy only goes so far.
For example, in software development, it can be argued that there’s a clear bias towards men, with women making up just 20%. The figure is even more astounding when it comes to race, with black women making up a mere 0.7% of the IT workforce in 2020.
In this article, we will explore how harnessing AI can help reduce (or eliminate) unconscious bias in recruiting software developers to create a fairer, more diverse and equality-driven workforce.
What Is Unconscious Bias?
In essence, unconscious bias — also known as cognitive bias — is what happens when we act on subconscious, deeply ingrained biases, stereotypes, and attitudes formed from our inherent human cognition, experiences, upbringing, and environment. It’s something that’s difficult to spot and just as difficult to unlearn.
In the hiring process, unconscious bias can take the form of acting on your first impressions of a particular candidate. In addition, with LinkedIn soaring in popularity in the hiring sphere, a recruiter/potential employer is even more susceptible to unconscious bias as they could subconsciously react to a person’s appearance or name.
Common Biases in Recruitment
To help recognise the different types of biases existing in software developer recruitment, we’ve highlighted some of the most common types below:
- Gender bias: You might unconsciously lean favourably towards a candidate who matches the gender you associate with the role. For example, recruiters may subconsciously favour male candidates in traditionally male-dominated roles, like we sometimes see in software development.
- Confirmation bias: This means you only take in the information that confirms your beliefs, ignoring everything else. In the hiring process, confirmation bias occurs when a person forms an impression of a candidate and unintentionally searches for information to confirm that impression.
- Affinity bias: This bias occurs when people show a preference or bias towards candidates who are similar to you, for instance, believing that someone is a ‘good fit’ for your development team because you’re of a similar age or socioeconomic background.
- The halo effect: This refers to the tendency that once we perceive someone in a positive light, it’s very hard to darken this light, with subsequent negative characteristics being ignored. When reviewing CVs, a hirer might be impressed by the fact that a candidate worked at a big-name tech company like Google. This positive impression could distort their perception of the rest of the application because once we take a shine to someone, we generally look for reasons to keep liking them.
Using AI to Reduce Unconscious Bias in Recruitment
Humans are bombarded with a staggering 11 million pieces of information at any one time, yet they can only process 40. The human brain is therefore forced to take shortcuts, resulting in these biases. AI, on the other hand, can process every piece of information fed into the software while digesting it in a way that humans can’t achieve: without bias.
There are several ways AI can help eliminate unconscious bias in the recruitment of software developers:
1. Processing the Entire Pipeline of CVs Quickly and Effectively
Humans get tired — particularly when doing the same things over and over again. When you’re trying to analyse tens of CVs objectively, it’s only natural that your energy levels dip at some point, meaning unconscious bias is more likely to occur.
In contrast, AI has the ability to screen hundreds of résumés and shortlist the strongest candidates in minutes, with little risk of bias. It works by checking facts and desired attributes — for example, programming languages, years of experience and soft skills — with no understanding of who each person really is. The process is entirely based on the candidate’s skills.
2. Creating an Equal Screening Process
What’s in a name? Apparently, an awful lot.
Research conducted in 2019 showed that British citizens from ethnic minority backgrounds have to send, on average, 60% more job applications compared to their white counterparts. The only thing that varied between the white applicants’ CVs and those from ethnic minority backgrounds was the name.
Recruiters can leverage smart AI tech to hide names, images and other bias-prone information from applicant profiles so that they can focus solely on candidates’ skills and qualifications. This can go a long way to creating a more equality-driven software development industry, which is currently suffering from a diversity standpoint.
3. Offering Fairer Assessments
Accurately determining a software developer’s on-the-job potential remains a challenge to do without bias. Recruiters and employers can only assume how someone will perform before they’re hired, and these assumptions aren’t always based on skill or ability but on preconceived ideas of candidates.
However, AI-driven testing tools like the Predictive Assessment tool from BlueOptima can present a reliable overview of the candidate’s coding ability and predict their future productivity. By analysing a potential employee’s performance contextually, AI can remove the risk of unconscious bias and enable decision-makers to hire a strong candidate objectively.
Build Inclusive Development Teams with BlueOptima’s Predictive Assessment
Unconscious bias isn’t always easy to recognise and can therefore creep into any company’s hiring process, leading to discrimination.
Our Predictive Assessment tool uses AI to help guarantee an equal hiring process by giving you objective, granular insights into software developers’ current and predicted performance. With the power of data, you can source quality programmers based solely on their ability to do a good job, enhancing the productivity of the whole team.
Start your free trial of our Predictive Assessment solution today.
On Girls in ICT day in 2022, we sat down with our Head of Product, Alessa Schaeffer to discuss her career to date and tips for getting started in tech.
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