Artificial Intelligence in Human Resources

Artificial Intelligence in HR

One of the phrases we see on blogs, in articles and around the table in meetings is today’s digital technology and how important it is to our current and future plans. A recent survey conducted by Accenture Technology Vision for 2019 surveyed over 6000 business and IT executives and well over 90% saw the pace of technological innovation as having accelerated significantly over the last three years.

Companies see Digital Technology as giving their organisation the differentiating advantage, but also recognise that inevitably, those technologies that really “take off” will have to be embraced by all, so this advantage may only be a short term advantage, by not embracing it, inevitably a disadvantage for those that do not take it on.

Back in mid 1990’s I remember well the arrival of email. One of the innovations of the day. This “digital technology” has been around for a long time but (an invention by Ray Tomlinson in the 1960’s and recognisable in todays form by the 1970’s) but in business, in the mid 1990’s most CV’s I received were by post. The mounds of post that arrived with unsolicited and solicited CV’s would cover the desk and a letter opener an essential part of my equipment, by the late 1990’s physical post had dropped significantly to be replaced with email and in January 2019, I was most surprised to have a CV sent to me in the post (now what did I do with the letter opener?). Email took off big time in the “naughties”. The next big innovation, fast on the back of email, was the use of websites and job boards, and then “Applicant Tracking Systems” and mobile telephony – voice mail, followed by SMS or texting. Some of these we embraced in the early days, others took us a bit longer to adopt.

Some things take off, others flounder. Rabbit phones on the London Underground is one innovation that some may still remember. Unfortunately it flunked but it was a precursor and mobile telephony – network operators such as One2One and Cellnet really took off. The Rabbit died but the Orange flourished! I have seen the customer numbers for one mobile operator finally hit 100,000 customers, and then very soon after 1,000,000 and just 3 years after hitting 100,000 customers, it hit 16 million! I have worked with some great ATS’s, and saw it transform the world of the In-House Recruiter, by providing reams of useful data and management information.   And with meaningful MI, we can really make effective change and transformations.

I have not always gone with the winning side from the start. When working for a recruitment agency, I had a lot of success cornering the PICK market and placing a lot of people with this operating system, but to my shame ignored UNIX, but within just three years saw the need to change into this sector, embraced the UNIX market place and we saw PICK disappear almost overnight.

So what is the next innovation in Digital Technology that will really take off? What is that “thing” where every company will eventually converge on the same turning point?

Amongst the various offerings and discussion points, Artificial Intelligence has to be ranking as one of the potential great game changers.

We are beginning to see the use of Artificial Intelligence within HR. This has the potential to offer significant opportunities to improve various HR functions. As we have moved towards a set of “self service” transactions AI technologies has great potential, particularly including recruiting, payroll, reporting, accessing policies and procedures, on-boarding….

There are a variety of definitions for AI but pretty much all going along with the concept of AI being the branch of “computer science that enables solving cognitive problems typically associated with human intelligence, in essence “AI enables computers to think like humans” and to perform tasks such as problem-solving, reasoning and learning. Computers are being built which are able to “learn”, to learn from and make predictions based on data. It is much the same way that humans learn. Put you hand in a flame and you get burnt and suffer pain. Do it three or four times and typically a child has learned the lesson. The reinforcement, of good or bad behaviour, by consequences. Harder is teaching a child not to run across the road. Being hit by a car might drive the lesson home, but the overall result could be very severe! In the days when it was acceptable to smack a child, rather than being struck by a car, a parent would smack the child if they ran in to the road. How do you teach a machine?

The basis of computer learning is imbedded in pattern recognition and the concept that algorithms can be written enabling the computer to learn from recorded data without being programmed to so do. The typical techniques being used and some advantages are listed below:

• Detection of Anomalies: Computers are able to identify items or events which do not confirm to an expected pattern with a set of data. This removes the need for people to have to read through reams of information, trying to spot anomalies and given the amount of data potentially needed to be covered (3000 people on your payroll, 300 new hires all with 5 to 10 years work experience) you can understand how a rather mundane, but vitally important task, can be covered in a fraction of the time – I would suggest that human intervention is then needed to make the decision on an individual case but AI enables the tasks to be done more swiftly and anomalies reported more accurately.
• Background verification: Computer learning-powered predictive models and rapidly go through huge amounts of data, raise flags where there are potential issues showing in an employees CV, around dates, gaps, crossovers or referees.
• Potential Leavers: Attrition is an ongoing concern for clients and by understanding who are “high risk” potential leavers, by flagging these through the use of AI analysing the data, using predictive models the HR teams can proactively engage with the flight risks in order to retain them and reduce attrition.
• Job Alerts and content personalisation: We are already seeing this technology being harnessed by various job boards and social media sites. Just as Facebook and Google have algorithms targeting you with specific advertisements and content based on your previous search engine use and sites like Booking.com and Trip Adviser forward information on holiday destinations, so new roles going live are directed to an audience already active in their search.

Another way to “teach” a computer is by what the technologists call “Deep Learning”. This is where one trains a computer to learn from large amounts of data through neural network architecture. This is a much more advanced form of machine learning, which breaks down data into abstract layers. Rather than organising data to run through predefine equations, Deep Learning establishes basic parameters about the data and then trains the computer to learn on its own by recognising patters using multiple neural network layers for processing – sound like neurons in the brain? Pretty much that is what this is. After sufficient training, deep learning algorithms can begin to make predictions and interpretations of very complex data.

Some typical techniques being used and advantages of Deep Learning are listed below:

• Image and video recognition: Deep learning algorithms outperform humans in object classification. Given videos and photos of thousands of applicants, deep learning systems can identify and classify candidates based on objective data. There is a drawback found by some of the programmers. There is a bias towards certain ethnic origins by those ethnic groups, there is also a gender bias and companies in the UK are proactively seeking female programmers to work on the recognition technology and incorporate this in to the computer learning.
• Voice Recognition: While understanding human voice and the plethora of accents is difficult for most machines, deep learning algorithms are now being designed to recognise and respond to human voice inputs. Virtual assistants use speech recognition algorithms to process human voice and respond accordingly.
• Chatbots: Natural language processing (NLP) trains chatbots and similar systems to understand human language, tone, and context. NLP is not there yet but we are seeing major steps being made every week and one day will emerge as a crucial capability for AI systems.
• Recommendation engines: Digital learning experiences often involve personalised learning recommendations related to skill levels and professional interests. Using Big Data and Deep Learning, learning experience platforms can identify learning pathways that might interest individual employees.

Conclusion to this article. So the next big game-changer could be, and I think will be AI and its use in HR will be a fantastic opportunity to release HR personnel from some of the mundane aspects of the work they do today. AI will be able to take on many tasks – checking for anomalies, assessing vast elements of data and highlighting differences providing time for the HR professional to focus on finding solutions to complex issues

AI has already made candidate sourcing, screening, and matching easier for those organisations brave enough and with the foresight to invest in the technology, helping to improve organisations. And improve efficiency. AI is beginning to help HR leaders overcome human-bias in decision making.

AI systems are being used to create inclusive job descriptions and review them for gender-coded language. With several large corporations embracing this on a company-wide level, it is expected that AI-augmented job descriptions will become commonplace.

 AI is still in its early days in HR but already it is being used for:

• Sourcing candidates
• Nurturing leads
• Screening candidates
• Interviewing candidates and
• Onboarding 

It is still early days for AI in HR, but it is already happening. ATS companies are beginning to have Bots in place to ask questions and to answer questions. Questionnaires and surveys are being issued to candidates and hiring managers to explore their requirements further and to help businesses understand their thoughts and ideas. AI is not just around the corner, it is here. Embrace it now or “jump on the bandwagon” in a few years. But I would encourage you to look at this now, embrace the technology now. It is going to evolve further in the months and years to come. It does require an investment but it is an investment worth making.

? Ian Morrison 2019