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Hiring and firing is one of the biggest processes that a company must have a hold on in order to stay afloat. The problem for many companies, from small businesses to enterprise corporations, is how to attract the best talent, or sift through the mass of applications to find the best talent. 

In the olden days, a human resources director may have sat down on a Sunday afternoon with a foot-high stack of paper applications, or maybe a laptop clogged to the digital brim with .docx’s of virtually-submitted applications, and look for the tell-tale criteria on each app to see who is worthy of consideration, and who ends up in the “do not hire, do not even interview” stack. 

Technology has gotten more sophisticated over the years, and has boosted HR operations in previously unthinkable ways. One of the biggest areas of technological innovation that is impacting the process of hiring today is artificial intelligence. 

No, you are not going to be entering an interview and chatting with the HR version of Siri (not yet, at least.) That part, for now, will remain for a human sitting across a desk, or looking at your Zoom window, to suss out whether you are the right fit or not for a company. 

Really, AI can be responsible for everything in the hiring process leading up to the face-to-face, human-to-human interview. Have a look below at what AI processes you can implement into your company to make hiring easier. 

Separating the Wheat from the Chaff

Depending on what role you are looking to fill, you are probably looking for a candidate that will fill certain criteria. You can customize your needs with an AI agent that functions something like a prediction platform, where it scans applications for certain data to figure out which ones you are most likely to be impressed by. 

Is it a four-year college education? A certain number of years in a certain industry? Is there a skill, or multiple, that you consider essential? What about a combination of all these things, and more? Whatever it is, an AI agent can be trained to search through all of the applications your company receives and select the ones that meet the standards you set for it. 

Candidate Interactions and Pre-Screenings with Conversational AI

Applicants can reach out to your companies in a variety of ways. They may email your company inquiring about hiring positions, or, if you offer it, submit their application through an online portal on your website. 

Whatever their method, it is expected that the company will return their inquiries in an adequate span of time, at least the worthier candidates. 

Conversational AI is a type of AI system that specializes in natural language processing, or NLP for short, where the agent can independently interact with customers via voice or text exchange, without having to be supervised by a user. 

Such AI can answer applicants immediately after they submit, telling them that their application has been received and is under review. 

If a company wishes, they can have a number of pre-written preliminary questions that the conversational AI can ask in that email. This can help further screen out the clients with questions that you may not be able to answer on the application, such as whether the applicant would be willing to show proof of vaccination or submit to a COVID test within a week of starting work. 

Potential Problems, and Remedies, with AI in Hiring

AI can make the hiring process much more efficient for both the company and the applicant, but it is not without its problems. That being said, these problems are not without their solutions. 

The biggest one is bias, which is something that will ideally be handled by the developers in the training phase, because that is where the bias is typically bred in the agent, oftentimes unwittingly and with no malice on the part of the developers. 

This is because the agent gets far too used to certain kinds of data in a data set, such as applicants that are male, where there is not enough gender diversity in the data set to ensure that male applicants are not the ones the agent gets used to selecting. 

Unfortunately, this is not always the case with developers, so a company is advised to hire an in-house expert that can detect for biased trends in the AI agent’s applicant selection, and so mitigate the problem.