But some are raising red flags. Greene says that because AI relies on human-inputted data to make decisions, there’s the potential for bias to infect the algorithms. Removing humans from decision-making doesn’t ensure less descrimination or bias. When humans are unaware of how their biases impact their decision-making, researchers like Cappelli and Greene say they are concerned that AI tools will simply mirror those flaws.

Greene says there isn’t a lot of science underpinning hiring platforms like HireVue, for example, which records an interview and uses AI to evaluate a candidate’s voice or expression to score them on attributes like friendliness and assertiveness. “This, unfortunately, has led to the resurrection of physiognomy,” says Greene, referring to the pseudoscientific and often racist practice of assessing someone based on physical characteristics such as their facial features.

Other AI-powered recruiting tools rely on past hiring data to identify optimal candidates, so if companies have mostly hired men, says Greene, the algorithm will continue to choose men for available jobs. “Bias in past hiring might cause bias in current hiring,” he says. An AI-powered recruiting tool for Amazon, for instance, made headlines in 2008 for teaching itself to systematically favor male job candidates over female candidates based on past hiring practices.