Boon Founder Dakota Younger on how machine learning is changing the industry
With the increasing demand for technical talent, it’s no surprise that the recruiting arms race continues to push companies to create new ways of attracting the very best people… One of the newest weapons in the arsenal in machine learning. Boon founder Dakota Younger answers some of the pressing questions facing machine learning in recruiting.
What is Machine Learning?
Machine learning is giving computers the ability to learn without explicit programming. This is done through pattern recognition. For example, if you tell a computer to find the best candidates for a job by identifying patterns in data that produce the best results. In this way, a computer will find correlations and patterns that a human would overlook – leading to increasingly higher quality candidates.
Beyond that, the possibilities are infinite! Imagine that you are able to predict the crash of a certain market, and know that there will be a surplus of available candidates in that specific field, you can then focus your efforts as a recruiter to take advantage of that situation. The ability to predict upticks and downticks in a given market is a revolutionary new possibility thanks to machine learning. It would give recruiters a serious advantage over their competitors and would allow them to reach out and make connections much earlier in the recruiting process.
How is machine learning changing recruiting?
The biggest issue for recruiters right now is that we all have these massive networks and we never really had a way to properly use all of those connections. If you have 5,000 LinkedIn connections, what does that do except allow you to brag about it?
This is where I think machine learning comes into play. We can start to recognize pure data points of candidates’ contact information, their profile, their work history, etc. and be able to match those with opportunities. Machine learning gives you the ability to quickly discern between someone that’s a good fit and a dud, and that saves you a massive amount of time and money. It gives you a higher R.O.I. for your effort and more clarity on where you should put that effort.
We can start to understand trends in specific industries and even specific job titles.
For example, machine learning could determine that a certain developer has been at their job for a year and a half and there is a, let’s say, 98% chance that they will leave their job in the next three months. That is a huge insight that can be determined very quickly with machine learning. There is an enormous R.O.I. for every singular effort that the recruiter makes. Time equals money, and machine learning will save recruiters unimaginable amounts of time.
Will Human Recruiters be replaced by Robots?
This is sensibly applied technology, not the end of days. Anyone who claims they can create a full replacement for the human recruiter is not being realistic. First of all, the technology for that currently does not exist, but also, I don’t think there is a demand for fully automated recruiting. There is a human element to the hiring process that is essential to both sides of the process. There are ways for technology to streamline and improve the hiring process, but at the end of the day, no one wants to feel like they are some sort of cog in a machine.
Recruiters should be spending their time on the more personal aspects. Machine learning will eliminate the recruiter’s need to perform mundane tasks like sifting through resumes and comparing qualifications, and allow them to focus on the person-to-person aspect of the hiring process. I would say that recruiters spend over a majority of their time performing these tasks that computers can not only perform exponentially faster, but also a lot better.
This is a sponsored post written by Dakota Younger on behalf of Boon. All opinions are 100% those of the author.