Immediate Implications of ChatGPT and Machine Learning for Recruiters
With all of the recent discourse about ChatGPT and its implications, recruiters out there might be wondering what all of the hype is about. Here is what you need to know about machine learning as a recruiter looking to take your sourcing strategy to the next level.
Get ChatGPT started on your sourcing project
ChatGPT is not sentient, but it taps into a vast database and understands words in context. It is an application of generative machine learning – an algorithm that looks at many examples from existing data to generalize something new – in the case of ChatGPT that’s text. So if you have written notes from a hiring-manager conversation and need to pull together a job description, ChatGPT is an excellent place to start. Just ask it to write a req based on your criteria and see what happens.
Another way you can put ChatGPT to work is candidate outreach. While ChatGPT is not that good with tone (e.g. don’t ask it to write a humorous email), and won’t know the details about what makes your company or role special, it can draft a note for that engineering candidate you want to wow. Just ask it to “write an email to help me recruit [Name] for [Company]”.
Traditional AI, New Generative AI and Machine Learning
So while a generative machine learning platform like ChatGPT can help you draft a great word document, it can’t help you source candidates. Moreover, the traditional AI algorithms that power sourcing platforms like LinkedIn Recruiter don’t adapt to your preferences, so when you and other recruiters search for “Software Engineers in San Francisco” you’re all getting the same results. That means you’re sitting for hours sorting through hundreds of resumes trying to scroll past candidates you’ve already reviewed (shocking, but LinkedIn doesn’t do this for you).
Enter machine learning (ML). Machine learning is a subfield of artificial intelligence that is quickly becoming ubiquitous. Simply put, machine learning algorithms give computers the ability to learn without explicitly being programmed. Why does that matter for sourcing?
When you use a machine-learning sourcing platform like Recruitbot, our algorithms look at examples to determine patterns and then make judgements about new examples they haven’t yet seen. What does all of that computer-speak mean to you? It means that we reverse-engineer your preferences for each position, allowing you to find candidates that are a perfect fit for your role based on your feedback (star ratings of profiles). It should come as no surprise that recruiters who use our sourcing platform report finding candidates 5X faster than on LinkedIn Recruiter.
Use Machine Learning to match more people to the right roles faster, and then use ChatGPT to write great emails for those roles. This is not science fiction. The technology is here today for recruiters not afraid to try it.