Skip to Content
Uncategorized

An AI Recruiter Could Find You Your Next Job

November 27, 2017

The hiring process is tedious for people on both sides of the interview table. There are online forms, stacks of résumés, LinkedIn browsing, and countless job interviews. Each of these tasks is repetitive, a matter of scanning the Internet for data. That makes them ideal for artificial intelligence to take on.


AI is skilled at automating tasks that have a lot of easily accessible data it can learn from. Enter Woo, a recruitment platform that harnesses AI to get people into jobs that best fit them. The platform serves as a headhunting tool for large corporations and a simplified job-hunting tool for talent.


“If you think about an interview, it’s an outcome of a lack of information on both sides,” Woo CEO and founder Liran Kotzer told Forbes. “But if there’s a machine that knows everything—like a god—knows about your past experiences, about your projects, your culture—the machine is going to tell you that there’s a perfect fit and both parties won’t question it.” The company claims its headhunting software, Helena, has a 52 percent success rate of interested candidates accepting job interviews, more than twice that of human recruiters.


Woo isn’t alone—Belong, a startup based in Bengaluru, India, also uses AI to pull information on candidates from all over the Web, including sites like GitHub and Twitter. It then generates a ranking of the best candidates based on the requirements for a given position.


But while using algorithms to streamline the hiring process is clearly attractive to any firm that wants to save on costs and time spent recruiting, as we have written before, AI can often be biased (see “How to Root Out Hidden Biases in AI”). This isn’t the fault of the software, as such—it’s only as good as the data it is fed. And we humans have an unfortunate habit of being unable to shake habits like gender and racial bias. If we’re to avoid such pitfalls in a world in which AI mediates the hiring process, then, we’re going to have to keep a sharp eye out to make sure it does a better job than we have of playing fair.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.