This is a line credited to Peter Drucker, a well-known management guru. Organisations have been selective on whether they use quotas or targets in the diversity space – it’s still a hot political issue for many. Targets are said to help align organisational investment and effort to achieve a given goal, whether it be a sales target or an internal promote target. But as any good sales Director or CEO will tell you, you need the data to track it, and that means ‘lead’ not just lag indicators, as then it’s too late.
When it comes to bias around hiring and promotion, its mostly unconscious bias we have to worry about.
With AI enabled interviewing and assessment, there is now no excuse. The bias is trackable, visible, at the micro level, so your CHRO can hold the mirror up to every manager to show their bias. A game-changer for changing behaviours. Something no amount of bias training will give you.
Given that we do not collect the above demographic details from our candidate, we use an external service, NamSor, to derive ethnicity and gender from candidate names. NamSor is one of the leaders in name to gender, ethnicity and origin classifications.The ability to measure bias is one reason to use AI based screening tools over traditional processes. Growing awareness that AI can be fairer for people prompted the California State Assembly to pass a resolution to use unbiased technology to promote diversity in hiring.Not all AI tools are equal however. The US is shining the spotlight on video interviewing with HireVue, an AI-driven recruitment company, recently taken to the US Federal Trade Commission claiming unfair and deceptive trade practices in their use of face-scanning technology to assess job candidates’ “employability”.
One US state introduced legislation this year, the Artificial Intelligence Video Interview Act, which requires companies to secure applicant’s consent to use AI, imposes limits on who can view an applicant’s recorded video interview and requires that companies delete any video that an applicant submits within a month of their request.
Read our whitepaper on bias and assessments here
Recommended reading: Invisible Women: Data Bias in World Designed for Men
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