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5 Ways Manufacturing Recruiters Can Use Machine Learning to Fill Positions Faster

Artificial intelligence (AI) and machine learning are in the news everywhere these days, thanks to the popularity of ChatGPT. In this blog post, we share five ways manufacturing companies can leverage machine learning to automate their recruitment process and reduce the time it takes to hire qualified workers.

Artificial intelligence (AI) and machine learning are in the news everywhere these days, thanks to the launch of ChatGPT, a chatbot that “interacts in a conversational way [and can] answer follow-up questions.” ChatGPT impresses people with its ability to write basic code, draft college essays and fulfill other unique requests

If machine learning tools like ChatGPT can revolutionize writing, what could they do for human resources departments?

We’ve compiled five ways manufacturing companies can leverage machine learning to automate their recruitment process and reduce the time it takes to hire qualified workers. But first, let’s take a step back to consider what machine learning is. 

What Is Machine Learning and Is It Useful for Manufacturing Recruiters?

Machine learning is a type of AI that “gives computers the ability to learn without explicitly being programmed.” Every time you watch a video on YouTube, for example, its algorithm pays attention, noting your interests and curating content that it thinks you’ll enjoy. With each video you like or dislike, it makes adjustments to its calculations. But no one is telling the algorithm what it should do; it’s learning independently. 

Companies have been working on machine learning models for recruitment for years now, with mixed success. One of the biggest cautionary tales comes from Amazon, which trained a model “to vet applicants by observing patterns in resumes submitted to the company.” After all, if a program could sift through hundreds of applications and identify the five best candidates in a few minutes, wouldn’t you want to use it? 

Well, maybe not. The Amazon system learned the wrong lesson from those resumes: it “taught itself that male candidates were preferable.” 

Amazon’s experience proves that machine learning isn’t exempt from unconscious bias. If an AI system is trained on biased data, it can “automate and perpetuate those biased models.” 

So, should recruiters use machine learning? Absolutely—just be sure your people are keeping their own hands on the wheel instead of trusting the machine to do the driving. Here are five ways machine learning can streamline recruiting and help your team fill positions faster. 

5 Ways Machine Learning Can Accelerate Manufacturing Recruitment

When you’re trying to hire more people quickly, you need to expedite every step of the recruitment and hiring process. That’s where machine learning shines. 

  1. Get your job posting up faster. We’re not saying your team should go have coffee while a chatbot writes job descriptions! But machine learning tools can translate a bullet list of qualifications and job requirements into polished text in a fraction of the time it would take most recruiters. From there, your team can adapt the text and post a job listing mere hours after learning about an opening. 

  1. Find more diverse candidates in talent pools. Wait, what? How can AI be trusted to identify diverse candidates when it’s subject to unconscious bias? Machine learning isn’t necessarily biased; it’s entirely neutral so long as it’s fed neutral data. So, as long as your criteria are unbiased, machine learning can help your team identify promising candidates without being misled by unconscious human bias. Also, machine learning can help your team sort through candidates faster, so they can evaluate a larger pool of potential candidates. 

  1. Screen candidates for required qualifications in minutes. Your team doesn’t have time to spend on candidates who don’t have the skills your factory needs—but it takes time to manually assess each candidate and figure out who fits the bill and who you should pass on. Fortunately, machine learning can screen candidates in just minutes, ensuring that your team invests its time in the most promising candidates. 

  1. Expedite interview scheduling. We’ve all been there: trying to schedule a meeting with someone who’s so busy that you spend more time going back and forth about available times than you do in the eventual meeting itself. Streamline scheduling—and avoid frustrating your candidates—by having a machine-learning-powered chatbot identify available times and quickly schedule interviews. 

  1. Keep candidates engaged. The faster your team can hire, the lower the odds that your best candidates will have accepted other positions. In the meantime, staying in touch with candidates can keep them interested and engaged. But who has the time to chat with dozens of people every day? A text-recruiting chatbot! These systems don’t fully replace your team’s personal communications, but they’re great at answering questions and maintaining engagement between human touchpoints.  

Whether your team wants to streamline job postings, identify promising candidates faster or improve their overall time to hire, machine learning can be a useful recruitment tool.