AI hiring bias is real — Here’s how you can fix it
AI can be the fuel that pushes many processes — like recruiting — to operate better, faster, and more robust. Many AI hiring tools attempt to leverage their machine learning capabilities to pinpoint quality candidates by modeling and replicating past successful hires, thereby removing human bias from the process.
However, AI is a product of human innovation, which means it also has human flaws — namely, unconscious bias. Consider Amazon’s failed recruitment experiment to design a tool that could learn to pick the best people fast. The only problem? The tool used historical hiring data from Amazon, and it ended up choosing top candidates through the same partial lens as human hirers.
Biases are typical, and they all get triggered in us in some way. Whether language, location, level of education, or gender, everyone has biases — and they can easily lead to AI bias in hiring. By working in tandem with automated hiring tools, companies can address the challenges of AI in recruitment and still achieve internal hiring goals related to diversity. Here’s where to focus:
1. Your People:
Research from TribePad indicates that 42% of people believe technology dehumanizes hiring. This feeling likely comes from an overreliance on tech. AI hiring tools can be their most effective and pull a diverse pool of candidates by working in tandem with a diverse and DEI-focused group of decision-makers.
Build a team from different departments and backgrounds that recognize the biases in your company; this group should also watch for any AI recruiting bias. Challenge this team to keep diversity top of mind and act as gatekeepers in the event that discrimination occurs.
Staying aware of these biases on a human level better informs your technology. That cognizance, hopefully, can mitigate the challenges of AI in recruitment.
2. Your Process:
All companies have their go-to sources for finding talent. They visit certain job sites, colleges, or organizations to find ideal candidates. For technology to collect a deep and impartial talent pool, its sources need to be equally diverse.
Turn to your usual sources while adding in new ones. Try adding different job boards and placement agencies to your array of sources. Collaborate with your diverse hiring team on the areas of concern in your hiring, and then find places to address those areas.
Then, let your hiring AI sift through the most qualified candidates from those platforms to balance diversity and people-first recruitment.
3. Your Technology:
Once you have the people and processes in place, it’s time to examine your technology to see how AI bias in hiring can materialize.
Take a close look at the information being fed to your technology to determine how that might introduce bias. For instance, look at the words and phrases that populate each job listing (e.g., “go-getter,” self-starter,” “nurture,” “aggressive”). Do those phrases lean toward a particular gender, race, or anything biased in any way?
Look at how sophisticated your technology is to determine whether it and your team can work together to be stewards of diversity for your company. For instance, Arya’s solutions work to cut through potentially biased keywords to look at the depth of someone’s qualifications in assessing their ability to perform a job.
Unite your team and processes with cutting-edge, innovative hiring AI to bypass potential bias.
AI recruiting tools don’t operate in a vacuum. They need the eyes and ears of human expertise to build a diverse talent pool. Practice a people-first mindset in your use of AI hiring tools, and they can act as complementary parts of your efforts to attract and retain a more diverse team.
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