Don't count on a college degree to land your dream job in Silicon Valley. Increasingly, founders and tech companies are judging talent by how quickly someone can learn, adapt, and build - not on how long they spent in a lecture hall - reshaping traditional pathways into the workforce. Fei-Fei Li, the Stanford computer science professor widely known as the "Godmother of AI," is one example of this.
It's my first job interview in more than eight years. Even though it's a video interview, I'm still keen to impress. When I log on, my interviewer, whose name I didn't catch, looks relaxed and friendly. He asks carefully articulated questions, listens intently, and even asks follow ups regarding particular examples I mention. But then, strange things start happening. He takes a while to process what I'm saying, and his facial expression remains unchanged.
The top performers are seasoned engineers who have adopted AI early and know how to leverage it effectively. "The most productive engineers I know, they're not fresh college grads," said Ng, who now leads several AI-focused ventures, including AI Fund. "They are people of 10, 20 years of experience or whatever, and really on top of AI," he added. These engineers "move faster than anything the world has seen even one or two years ago," Ng said.
Business leaders have been incorporating Artificial Intelligence into their hiring strategies, promising streamlined and fair processes. But is this really the case? Is it possible that the current use of AI in candidate sourcing, screening, and interviewing is not eliminating but actually perpetuating biases? And if that's what's really happening, how can we turn this situation around and reduce bias in AI-powered hiring?
Integrating Artificial Intelligence into the various stages of your recruitment process, and specifically interviewing, promises quick and targeted growth for your organization. This is due to the speed and efficiency you can gain through automating time-consuming tasks, as well as eliminating mistakes and oversights that stem from increased workloads. However, you can only enjoy these benefits if you are very careful about how you implement AI interviews.
As the CEO and cofounder of an AI-native skills company, I've spent the last decade working with talent leaders to build better and fairer hiring processes. And, here's the uncomfortable truth: The biggest source of hiring bias isn't AI-it's us. While high-profile lawsuits like Mobley gets all the headlines, over 99.9% of employment discrimination claims in the previous five years don't center on AI bias, but on human bias.
