It’s well documented that the humans who program artificial intelligence (AI) also unintentionally program their social biases into the systems.
Even if the programmers manage to evade bias, per se, the majority of contemporary programmers tend to retain only shallow understandings of demographics that aren’t their own.
“Biased algorithms are linked to discrimination in hiring practices, performance management, and mortgage lending,” reports Security Intelligence.
To improve the accuracy and efficacy of artificial intelligence-based systems, cognitive and physical diversity are needed within the development phase.
But it’s not just hiring diversity that makes a difference. It’s also taking the time to walk your new hires through your operations, getting them up to speed. Within the corporate environment, micro inequities are often present, meaning that those who speak other languages, come from other cultures and are not of the dominant age range may experience hidden challenges. You’ll want to make every effort to create a level playing field. It’ll pay off in the long run.
Once you’ve hired a diverse workforce, the next issue is retaining it. “Biased performance management practices are part of the problem, as workplace cultures and policies can be especially detrimental to women and minorities. For example, an absence of flex-time policies can disproportionately hurt women.”
Academic analysis shows that organizations that close the gender pay gap and take other equalizing measures see higher revenue gains than those that don’t. Retaining your workforce is just as important as hiring it.
For more on eliminating bias from AI technologies, read this CyberTalk article.