AI will excel at hiring without ever reading your resume

Imagine if everyone you’ve ever known, worked with, or related to gave you complete and honest feedback. Sounds like a futile gesture that would do more harm than good, right?

Well, it turns out that it could be a key to running a wildly successful business.
Ray Dalio, the founder of the world’s largest hedge fund, Bridgewater Associates, employs a tactic around the office known as radical transparency. The theory encourages criticism and blunt honesty in all professional situations.

It’s not meant to be an open-door for coworkers to roast each other’s outfit choices. Rather, it’s a way to openly discuss opinions, without always defaulting to hierarchy. Dalio claims that this culture has helped them create an Idea Meritocracy, where the best ideas rise to the top.

However, the culture can’t do it alone. Instead, it must be paired with technology. And when done properly, it actually gives us a glimpse of how companies will operate more efficiently in the near future.

Bridgewater employs algorithms to graph the responses of associates over time, thus creating rich profiles of each participant. Dalio likes to refer to these profiles as baseball cards because they are practically stats sheets. More likely, it’s a way to graph strengths and weaknesses, thus bringing more context to a person’s actions. You can see an example (from a company that copied Dalio) below:

Initially, you may think about how wildly inaccurate this could be, considering it’s all subjective feedback. However, you’ll actually find that the more subjective data an algorithm receives, the closer and closer it can get to objective truths. It’s really a numbers game.

For instance, another AI company known as polls the opinions of large amounts of people and applies an algorithm to this data to make nearly perfect predictions. Their track record is impressive thus far. In 2016, they used their methodology to correctly predict the first four horses in the Kentucky Derby, a bet that paid off 542:1. Earlier that year, their methodology predicted 76% of Oscar winners (better than a majority of movie critics).

It goes to show that there’s actually value in using subjective data to create objective truth.

Nonetheless, the point of these “player cards” is to make better staffing decisions – consulting a person’s card to decide whether they’d fit a certain team initiative. No doubt in my mind, many other organizations will find ways to replicate what Bridgewater has implemented. However, I’m intrigued as to how this could affect the larger economy. More specifically, how it could be used to eliminate our cryptic hiring process.

DeepSense is an application that aims to do the same thing above (map a person’s strengths and weaknesses) but for any possible person. Currently, it does so using only a person’s Twitter handle, so the data isn’t very encompassing. But, in the future, I can see them taking into account other social media profiles, their history at other companies, and perhaps user-generated responses.

Should this become a reality, effectively, they become the Hiring Department for every company nationwide because they’ll have the best system for predicting a person’s fit at a company pre-hire. For example, managers could describe the characteristics they are looking in their next hire and the AI Hiring Department will match the best candidates.

It’s a great vision for the future, especially considering how ineffective the hiring process is today. Jobvite found that it takes on average 38 days to hire a new employee. Combine this with the fact that the recruiting process relies on standardized resumes and potentially biased interviewers, it’s no wonder companies suffer from hiring the wrong people.

Fortunately, there are increasing amounts and diversity of data that can inform algorithms on how to properly fill positions. Although algorithms can currently use this data to source great candidates, it falls short at actually placing them in the correct job because it fails to understand the idiosyncrasies of each company’s business model. This requires a framework where employers can easily translate their needs, thus communicating with the AI.

By 2032, AI-enabled Hiring Departments will be the standard method for staffing companies.

Will you trust AI to place you in a new job?