AI Delivers Smarter Recruitment & HR

Firstly, we all know that AI can bring automation to many business processes and with it comes greater productivity as a result of machine learning for repetitive tasks, but there is a lot more to machine learning and AI then you may think.

I’m about to tell you how AI delivers a far more streamlined, fairer and more accurate recruitment process - at scale.

Let’s jump right in.

A multinational British telecoms company has over 100,000 graduates applying for just 1,000 jobs each year and it recently tested an AI application to automate the bias out of the recruitment process.

You’re probably wondering, how does it do this?

The AI application extracts as many as 25,000 data points from video interviews and then examines visual and verbal cues while comparing word choice, facial movements, body language, and tone to help identify the very best candidates.

And it doesn’t stop there.

The program also sorts the candidates into highly recommended, recommended, and not recommended. The telecoms company concluded that the AI system correlates well with their own internal assessments (around 70% for the ‘highly recommended’ candidates) and while they quite rightly remain cautious as they are only at the early stages, they also stated that this is something which will be part of the future of recruitment.

Here’s the thing.

When AI is trained properly with the right data sets in order for it to learn and eliminate any human bias, which can be transferred into algorithmic bias if not done correctly, then this type of automation has clear and tangible benefits over and above the sheer magnitudes of increased efficiency we see here.

In the recruitment process it can be used to identify real talent that could otherwise easily fall under the radar when such numbers come into play. AI in recruitment will surely become a ‘new normal’ as more large companies adopt this process and share their experiences.

Sounds good, right?

Yes! This will usher in a future job market which is talent driven rather than ‘who you know’ being more important than ‘what you know’.

And the best part?

This type of AI driven future is taking place right now and we are starting to see thousands of data analyst jobs being created in order to have skilled people ready to ‘fuel’ the algorithms with properly annotated data.

In fact Gartner, the world's leading research and advisory company predicts AI-related job creation will reach two million net-new jobs in the next few years.

An exciting time ahead as AI will touch many, many aspects of our business and personal life in the coming years.

Not only that but The World Economic Forum in its recent report went on to identify data analysts and scientists, AI and machine learning specialists, big data specialists and digital marketing and strategy specialists as the top four roles seeing increased demand.

It may seem like it will only be those currently proficient in AI and data analysis that will be able to take advantage of the huge number of roles on offer. To reach the critical mass needed to meet with current and growing demand, a much larger recruitment base is needed. The good news is that the main requirement for those looking to retrain in AI is the same level of computer literacy found in most current roles. Furthermore, rather than taking three years to complete, many entry level AI courses take just 12 weeks.

Underpinning all of this is AI’s need for data. Whilst AI is often seen through the lens of removing existing roles, a better interpretation would be a process of upskilling. Machine learning requires a huge amount of data, all of which needs labelling in order to be processed -something which by its nature requires human intervention.

Depending on the complexity of the AI model being built, the size of dataset required to train the AI through machine learning will vary from case to case. Other factors that influence this will be the performance that an AI model is expected to deliver. Often machine learning practitioners will try to achieve the best results with the minimum amount of data or resources in order to build their predictive model. This will generally take the form of a simple model using few data points. Once a desired outcome has been achieved, they will then move onto building a more advanced model, and this is when the potential for a vast amount of data is required.

When it comes to recruitment and HR, would we consider AI as the ideal candidate?

Surely a perfect match!