How Artificial Intelligence unlocks 'extreme' screening tactics

Facebook expands AI research program

Since the birth of social media, employee vetting, including social media background checking, has been a way for employers to legally or illegally gain information about employees or prospective hires. They know what we all know: posts on Facebook and Twitter can shed a light on our true selves in a way that a resume or job interview might not.

Until now, employee screening tactics and social media checks have only been as powerful as the amount of time employers sink into them. That could change dramatically as artificial intelligence gets in on the action.

The Challenges of Modern Vetting

To employers, the biggest challenge of social-enhanced employee vetting has probably been the sheer scope of them. People who are active on Twitter sometimes tweet hundreds of times per day. Sifting through these posts to find objectionable or relevant content is something that has required a genuine level of commitment from employers or hiring managers.

Facebook profiles often don’t have quite as much content, but they present their own challenges. Facebook is older than Twitter, so most people’s posts on the platform go back further. More people take advantage of Facebook’s privacy settings, making it difficult for employers to access candidate profiles -- let alone explore them fully.

Artificial Intelligence and Employee Screening

Artificial intelligence could solve at least one of these problems for employers.

New tech platforms including Fama are reshaping the strategies behind modern employee vetting. Fama is a tech platform that works by "applying machine learning to public online content and internal HR data." The system has filters that look for sexist or bigoted comments as well as flags that indicate "violence, drugs, and crime." Employers that use Fama can customize the platform to search for red flags related to "company-specific issues or threats."

Fama digs up questionable social media posts -- no matter how old they are -- and presents them directly to employers for consideration.

This technology now extends far beyond employee screening: another platform, Predictim, offers algorithmic social media background checks for parents hiring babysitters. The system searches user profiles and rates each candidate on a scale of 1 to 5 based on their posts -- with 5 representing a "high-risk" hire. The platform also seeks to get past the obstacle that Fama can’t: privacy settings. If a user has private posts on Facebook or Twitter, a family using Predictim can ask a prospective babysitter for access to those posts.

Case Study: James Gunn

This technology has major implications. Let’s look at an exceptionally well-known incident in which someone’s social media past came back to haunt their professional future.

On July 22, 2018, Walt Disney Studios fired director James Gunn from his job helming the third Guardians of the Galaxy film. Social media had exploded with discussion about Gunn involving tweets that he had posted between 2008 and 2012. The tweets, which included crude jokes about things like rape and pedophilia, had been found and shared by alt-right social media personality Mike Cernovich, who was retaliating against Gunn for the director’s criticisms of President Donald Trump. In a statement, Walt Disney Studios chairman Alan Horn called Gunn’s jokes "indefensible and inconsistent with our studio’s values" and announced that the company had "severed [its] business relationship with him."

Gunn’s firing led to massive fallout for Disney. The company was accused on social media of capitulating to the alt-right. The cast of the Guardians of the Galaxy films penned a statement in support of Gunn and urging that he be re-hired. One cast member, Dave Bautista, threatened to leave the Guardians film franchise -- itself a part of the Avengers universe. Finally, Disney drew criticism for not vetting Gunn fully before they hired him to direct the first two Guardians films.

Extreme Vetting and Employer Ethics

On the one hand, if Disney had possessed a tool like Fama when considering directors to lead the Guardians franchise, the company may not have hired him in the first place. The system would likely have surfaced the old tweets and predicted the potential risk of hiring someone like Gunn. Had Disney not hired Gunn, the company would never have dealt with the fallout from firing him.

On the other hand, there are significant questions here about privacy, context, and growth. Is it fair for a person’s entire online life to be on the table and fair game during a hiring process? Can an AI tool designed to root out red flags understand context? Can a person who made an offensive joke on Twitter ten years ago be forgiven for the beliefs they used to hold -- and should they be?

Gunn was fired over jokes that were 6-10 years old at the time when Disney fired him. To put this fact into an employee vetting context, in most states, it is not even legal for employers to consider criminal convictions that are more than seven years old.


Many employers will be scrambling to get a tool like Fama at their disposal. We will likely see a growth of AI in employer vetting -- and a rise in screening procedures that are more extreme than what most job seekers are used to -- over the next few short years.

We will also probably see greater efforts from social media users including celebrities, job seekers, and average users beginning to recognize and combat the power of algorithmic social media checks. Already, there are services that can go back and delete a person’s Twitter history before a certain point. Privacy settings on Facebook and Twitter might also grow more popular.

It’s hard to predict how effective "extreme" AI-enhanced screening will be, and how much backlash it may draw from the public -- but it will almost certainly change the hiring process forever.

Photo credit: agsandrew / Shutterstock

Michael Klazema is Chief Marketing Technologist at and has over two decades of experience in digital consulting, online product management, and technology innovation. He is the lead author and editor for Dallas-based with a focus on human resource and employment screening developments.

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