The use of artificial intelligence (“AI”) and machine learning in the workplace is growing exponentially – and specifically in hiring. Over the last two decades, web-based applications and questionnaires have made paper applications nearly obsolete. As employers seek to streamline recruitment and control costs, they have jumped to use computer-based screening tools such as “chatbots” to communicate with job applicants, to schedule interviews, ask screening questions, and even conduct video conference interviews and presentations in the selection process. Employers of all sizes are creating their own systems, or hiring vendors who will design and implement keyword searches, predictive algorithms and even facial recognition algorithms to find the best-suited candidates. The algorithms in these computer models make inferences from data about people, including their identities, their demographic attributes, their preferences, and their likely future behaviors. Now faced with the impact of COVID-19 and the growing talent shortage, employers may see the use of AI as a more efficient way through the hiring process.

However, the use of AI technology is controversial. Researchers have voiced increasing concerns about the inherent risk of automating systemic bias. Because algorithms rely on historical datasets and human inputs, the technology can generate bias, or exacerbate existing bias. AI systems can generate unfounded conclusions that may be based on protected characteristics.

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