How Ethical AI Helps Overcome Racial Hiring Bias
Artificial intelligence (AI) is not new to recruiting and hiring practices. In fact, 99% of Fortune 500 companies use some form of AI-enabled application tracking system (ATS). Whereas smaller companies, between 50-999 employees, use this tracking and screening technology extensively, according to a recent Harvard Business School study.
Although AI is used extensively in recruiting processes, this doesn’t mean that it’s been without its issues – primarily producing biased results. After all, AI depends on the inputted data (often inputted by humans), often leading directly to bias in hiring. In other words, if biased data is used to build AI, then AI will use that biased data in rendering its results.
Even if the inputted data is accurate, HR professionals and employers are still concerned that the hiring technology is genuinely bias-free.
AI-enabled biased outputs simply won’t be tolerated in today’s diversity, equity, and inclusion (DEI) focused workplaces.
Keep reading to learn more about how ethical artificial intelligence helps HR professionals and organizations overcome racial hiring bias.
What Is Ethical AI?
Ethical AI is artificial intelligence that adheres to pillars of accountability, transparency, explainability, and fairness, specifically focusing on non-discrimination and non-manipulation of data. Additionally, ethical AI is compliant with equal opportunity and privacy laws and regulations.
According to the MIT Sloan Management Review, “[w]hether it;s reviewing a job applicant’s information, selecting candidates to interview, making assessments, or conducting interviews, every step of the traditional hiring process is vulnerable to unconscious human biases.”
However, when ethical AI is used in the recruiting process, employers can “reduce and even eliminate” any unconscious bias in hiring inherent in the hiring process, including racial discrimination.
How Does Ethical AI Overcome Racial Hiring Bias?
To understand how ethical AI overcomes unconscious racial hiring bias, let’s take another dive into how AI-enabled recruiting systems can produce biased outcomes.
Suppose that within the company, an inherent bias in hiring against a certain group of people existed. Any information inputted by that company would have the same inherent bias, thus creating an algorithmic bias within the AI itself. This bias in hiring would then be consistently applied across all recruiting decisions, similar to if no AI was used at all.
However, if ethical AI is used, then the explainability and transparency allow you to understand how the AI came to a specific conclusion. For example, if the AI decided that Candidate A was selected and not Candidate N, the decision would be explainable, giving humans a path to inspect for any racial biases.
How Can Cangrade Help You Overcome Racial Bias in Hiring?
To combat racial bias in talent acquisition and management, Cangrade’s patented recruitment technology references a separate “Adverse Impact” testing set to check for disparities, identifying the statistical elements of an algorithm leading to bias in hiring.
Cangrade’s AI processes then iteratively run and remove those elements until they identify an accurate and bias-free algorithm. As such, Cangrade can uniquely predict candidate success without bias against any gender, race, ethnicity, age, or another protected category. This covers more groups than the U.S. Equal Employment Opportunity Commission (EEOC) requires.
In fact, Cangrade was recently granted patent 11429859 for its revolutionary process for mitigating and removing bias from AI. With Cangrade, organizations can confidently remove bias from their talent screening decisions and accurately predict candidate success and retention with their unique AI-powered pre-hire assessment, with zero percent chance of introducing bias.
For more information, visit www.cangrade.com.