For all the incredible work recruiters, HR professionals and business leaders do to reduce bias within recruitment, it sadly persists.
There is, however, some good news: the impact of technology on bias reduction within recruitment is incredibly positive. The long-term effectiveness of recruitment tech in removing as much bias as possible from the recruitment process relies on forward-thinking recruiters, hands-on leadership, open-minded teams, targeted tech implementation and an obsession with monitoring and measuring the improvements of tech introductions.
Bias in the modern workplace.
Socialtalent.com put the effect of bias on our relationship building and interpersonal communication very succinctly:
“Biases affects us and our decision-making processes in a number of different ways:
- Our Perception – how we see people and perceive reality.
- Our Attitude – how we react towards certain people.
- Our Behaviours – how receptive/friendly we are towards certain people.
- Our Attention – which aspects of a person we pay most attention to.
- Our Listening Skills – how much we actively listen to what certain people say.
- Our Micro-affirmations – how much or how little we comfort certain people in certain situations”.
Even a cursory look online gives you ample evidence of bias in the workplace and throughout the recruitment process. Equalture.com summarises how bias manifests, including 10 types of bias that “can leave the biggest negative impact on your hiring decisions”.
- Affinity Bias
- In-Group Bias
- Halo Effect
- Horns Effect
- Confirmation Bias
- Social Bias
- Illusory Correlation Bias
- Anchoring Bias
- Attribution Bias
- Beauty Bias.
Data and measurement of process change is, like most tech-based solutions, essential. Recruiters need to be empowered with up-to-date information on the effect of bias in recruitment, how bias can create non-inclusive cultures of hiring, and how and where tech can help.
Tech vs Bias.
The addition of recruitment tech into the HR matrix has been slowly and surely chipping away at conscious and unconscious biases for years now, creating more inclusive, safer recruitment processes, and drawing attention to legacy recruitment workflows (not to mention leadership mindsets) that hamper inclusivity.
Bias still very much lives within recruitment, but how it manifests is changing. Overt examples of bias – for example, companies displaying openly discriminatory policies, and not hiring people based on race or sex – have been significantly reduced (and many companies provide great advice on continuing this good work).
Now, employees are becoming more empowered to challenge the still-present subtle, insidious forms of bias that reject workers based on factors like age, weight, religion, accent, or sexual orientation.
In large part, this comes down to a certain sort of bias “market knowledge” – if you don’t know how and where bias manifests, or if you cannot measure it, or understand its impact, you cannot improve your services.
So how can tech help?
The rise of “blind” screening.
“If technology is incorporated into the hiring process, to ‘blind’ screen applicants during the initial stages, the decision to hire someone based on personal characteristics is significantly reduced.
No longer will a candidate’s perceived perception impact their chances of getting a job”.
It is virtually impossible to remove all bias from recruitment, but one of the most visible and effective ways of recruiting anyone for any job is by “blind” screening applicants. Naturally, modern AI and automation programmes can take blind screening policies and supercharge them.
The humble ATS has gone through a bit of a revolution over the last few years. The idea of competent AI screening software that can fairly, and diligently, “blind” screen candidates is one of the unicorn features of effective ATS service provision, and many now offer just that. The reduction of bias is pretty clear:
- “A two-year study of the impact of race in hiring practices found when African-American candidates removed details from their resumes, such as participation in ethnic affinity groups, they had a 25 per cent chance of getting a callback for the position”.
- “Studies show that blind hiring works—including examples where as many as 50% more women have got through to the final selection stages when using a blind screen”.
Collect the right data.
The engine room of effective bias reduction is through understanding where it occurs, how often it occurs, who generally does it, and why it happens.
There are certain tech-led criteria that can be put in place to monitor interview and screening behaviours – such as effective CRM and ATS data collation and cross-referencing – and procedural changes that can reduce bias, such as “using prescriptive questions, and interview scorecards to ensure your process is as fair and objective as possible”.
Data is also generated in myriad other ways that an effective ATS can capture, such as from skills tests and resume screening for keywords.
Bias-free interview questions.
While a relatively “new” concept, AI-created interview questions can generate “bias-free interview questions that are linked to the science-driven behavioural insights that are both individually relevant and anchored in the fundamentals of the job”.
While we don’t condone removing the human from interviewing at all, certainly from a data collation and skills-assessment point of view having AI support within interview creation and curation can rapidly reduce bias.
The collected data can be cross-referenced to hiring effectiveness and crucially gives recruitment leaders a pathway to improving the systems if they are deemed insufficient.
A quick, responsive process is what you need to attract and engage the best talent.
At Rectec we help organisations to find the best Applicant Tracking System or best Recruitment CRM to suit your needs, accompanied by our unique complementary technology marketplace, to help you build the perfect recruitment tech stack for your business.
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