Eyal Grayevsky has a plan to make Silicon Valley more diverse. Mya Systems, the San Francisco-based artificial intelligence company that he cofounded in 2012, has built its strategy on a single idea: Reduce the influence of humans in recruiting. “We’re taking out bias from the process,” he tells me.

Simon Chandler is a freelance journalist covering tech, politics, and music. Sign up to get Backchannel's weekly newsletter, and follow us on Facebook and Twitter.

They’re doing this with Mya, an intelligent chatbot that, much like a recruiter, interviews and evaluates job candidates. Grayevsky argues that unlike some recruiters, Mya is programmed to ask objective, performance-based questions and avoid the subconscious judgments that a human might make. When Mya evaluates a candidate’s resume, it doesn’t look at the candidate’s appearance, gender, or name. “We’re stripping all of those components away,” Grayevsky adds.

Though Grayevsky declined to name the companies that use Mya, he says that it’s currently used by several large recruitment agencies, all of which employ the chatbot for “that initial conversation.” It filters applicants against the job’s core requirements, learns more about their educational and professional backgrounds, informs them about the specifics of the role, measures their level of interest, and answers questions on company policies and culture.

Everyone knows that the tech industry has a diversity problem, but attempts to rectify these imbalances have been disappointingly slow. Though some firms have blamed the “pipeline problem,” much of the slowness stems from recruiting. Hiring is an extremely complex, high-volume process, where human recruiters—with their all-too-human biases—ferret out the best candidates for a role. In part, this system is responsible for the uniform tech workforce we have today. But what if you could reinvent hiring—and remove people? A number of startups are building tools and platforms that recruit using artificial intelligence, which they claim will take human bias largely out of the recruitment process.

Another program that seeks to automate the bias out of recruiting is HireVue. Using intelligent video- and text-based software, HireVue predicts the best performers for a job by extracting as many as 25,000 data points from video interviews. Used by companies like Intel, Vodafone, Unilever and Nike, HireVue’s assessments are based on everything from facial expressions to vocabulary; they can even measure such abstract qualities as candidate empathy. HireVue's CTO Loren Larsen says that through HireVue, candidates are “getting the same shot regardless of gender, ethnicity, age, employment gaps, or college attended.” That’s because the tool applies the same process to all applicants, who in the past risked being evaluated by someone whose judgement could change based on mood and circumstance.

Though AI recruiters aren’t widely used, their prevalence in HR is increasing, according to Aman Alexander, a Product Management Director at consultancy firm CEB, which provides a wide range of HR tools to such corporations as AMD, Comcast, Philips, Thomson Reuters, and Walmart. “Demand has been growing rapidly,” he says, adding that the biggest users aren’t tech companies, but rather large retailers that hire in high volumes. Meaning that the main attraction of automation is efficiency, rather than a fairer system.

Yet the teams behind products such as HireVue and Mya believe that their tools have the potential to make hiring more equitable, and there are reasons to believe them. Since automation requires set criteria, using an AI assistant require companies to be conscious of how they evaluate prospective employees. In a best-case scenario, these parameters can be constantly updated in a virtuous cycle, in which the AI uses data it has collected to make its process even more bias-free.

Of course, there’s a caveat. AI is only as good as the data that powers it—data that’s generated by messy, disappointing, bias-filled humans.

Dig into any algorithm intended to promote fairness and you’ll find hidden prejudice. When ProPublica examined police tools that predict recidivism rates, reporters found that the algorithm was biased against African Americans. Or there’s Beauty.AI, an AI that used facial and age recognition algorithms to select the most attractive person from an array of submitted photos. Sadly, it exhibited a strong preference for light-skinned, light-haired entrants.