Disruption in Recruitment: Machine Learning

Disruption used to be a dirty word.

If your lunch was disrupted, something had got in the way of your sandwich. If companies advertised on the basis that they were ‘disrupting lunch’ then chances are, people would have avoided them. Lunch is important, and shouldn't be tampered with.

However today, at the first mention of a cool new app from LA disrupting lunchtimes along the West Coast and beyond, you can guarantee that people will be downloading it by the hatful.

That’s because, today, it’s great to be a disruptor.

It means doing things differently, shaking up a market and making people re-evaluate what it means to work in or interact with a certain product or service. We've all seen some variation on this doing the rounds:

“Uber, the world’s biggest taxi company, owns no vehicles"

"Facebook, the world’s most popular media provider creates no content"

"AirBnB, the world’s largest accommodation provider owns no real estate”

All have been majorly disruptive.

But when it comes to recruitment, where is it? Or is it still to come?

On the face of it, and by applying the same logic as we’ve seen with the companies above, Indeed seems to fit the bill:

“Indeed, the world’s biggest jobsite, has no jobs of its own”

Indeed started in 2006 as an ‘aggregator’ of jobs from all over the internet. Since then, they’ve acquired Monster to also become the largest job board in North America, and when it comes to web traffic and traction online, it still has a huge draw.

The site trawls the internet for positions, and stick them all in one place - their site – hence the motto “one search, all jobs”.

However, Indeed may have to start looking over their shoulder as, in the US, Google have decided to enter the fray, and in May Google for Jobs was launched. Google for jobs works in much the same way as Indeed, as an aggregator, but Google also have access to some pretty sophisticated Artificial Intelligence and Machine Learning technology.

This means that, when you use Google for Jobs, their software won’t just match you to a job based on its title – it will read through the entirety of the job spec before matching you up with something that might actually be a fit for you, based on the massive amounts of information Google already has on you.

Artificial Intelligence & Machine Learning

AI and Machine Learning are and have been for a while, talked about as the next big thing in virtually every sector, in every area of industry. The two terms are often used interchangeably, but there are subtle differences as to what they mean.

AI refers to artificial intelligence as a whole, and basically, means computers making decisions as a human would.

Machine learning is the idea that you can put data in front of a machine and it will consume, interpret and learn it on its’ own (such as when reading job descriptions).

Machine learning is becoming more and more prevalent amongst the big names in recruitment. For example, LinkedIn has recently revamped it's Jobs app, which means that their algorithms can now ‘read’ job descriptions posted on their site and match them to the skills, industries and other specialities that you’ve inputted when creating your LinkedIn profile.

It even goes a step further and will increase the likelihood of you being sent roles from companies whose pages you have visited, or followed, in the past. It’s all a move towards more sophisticated, personalised job matching.

Another idea currently being rolled out is Natural Language Processing (NLP). This is centred around our communication with machines, notably speech. The idea behind NLP is that we should be able to speak to computers naturally, without putting on that weird voice we do on the occasion we ask Siri to do something. Think Alexa, Google Now etc.

Going Internal

When it comes to making direct hires, this new technology has given major companies with major budgets the opportunity to put together some really innovative recruitment processes. 

For example, gigantic consumer goods company Unilever have adopted NLP technology, amongst other things with the hiring process of their ‘future leaders’ programme. Their recruitment process for this now consists of 3 stages before a face to face interview, none of which require a CV, all of which depends on a computer’s decision-making ability, based on the information you put into it.

For Unilever, candidates can apply with LinkedIn before being tasked with completing 12 games which are designed to assess decision making and cognitive ability. Then, if they get past this phase, it’s a video interview, where the candidate records themselves answering a variety of questions on video.

At this point, the NLP technology kicks in, and the software will effectively watch and listen to the interview before making recommendations as to who should progress to a face to face interview. It’s not just fancy for the sake of it though - apparently, it works -  and has saved thousands of hours of candidates’ time from not attending unnecessary interviews, and has reduced the time recruiters spend screening CVs by 75%.

So there’s a good chance that in the next few years, your job hunt could consist of:

  • A great job landing in your inbox,
  • Applying in a few clicks,
  • Playing a game or 12
  • Having a chat with your laptop
  • Being invited to a face to face interview - 5 stages later!

How does that sound? Is efficiency everything when it comes to recruitment, or is that personal touch important? Interested to hear what people think whether you're a candidate, hiring manager or recruiter.


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