May 22, 2020 Equidpro

Artificial Intelligence & Recruitment: How To Use AI To Find The Best Candidate And How To Avoid Its Failures

Executive Summary

  • Artificial intelligence (AI) is helping business leaders and organizations from all sectors improve their processes
  • The power of big data, deep learning, predictive analytics, and algorithm technology are being harnessed to usher in the fourth wave of industrialization
  • Recruitment and talent acquisition teams have tools, like ATS, specifically designed for them to find high qualified candidates
  • Although there are many benefits to ATS technology, your HR managers and talent acquisition teams may be crippling their ability to actually deliver the right candidate
  • Ensuring that AI is used as a tool for your HR team, rather than the hiring process itself, in combination with using recruitment experts will best help you match a job role to the right candidate

What is artificial intelligence?

In simple terms, you can think of artificial intelligence as using computers to replicate cognitive functions to perform human tasks such as design, communication, learning, problem solving, and much more.

The power of artificial intelligence, or AI, is being harnessed on many technological fronts across every economic sector from healthcare to eCommerce and everything in-between. These AI technologies vary in use, functionality, and features, but all serve a common purpose: improve work performance.

Many futurists and business leaders discuss the future of AI and the implications it will have in automation, displacing jobs, and leading the fourth wave of industrialization.

There is no shortage of excitement and fear surrounding the topic. However, as futuristic as much of the conversation surrounding artificial intelligence is, the reality is that it has already permeated into our everyday lives today. Many business processes have been redesigned to include elements of artificial intelligence. The results usually mean quicker lead times, improved accuracy, and above all else, larger bottom lines.

The world of recruitment and talent acquisition is no different. AI has been introduced in several facets ranging from seamless interview scheduling integration to the process of candidate selection itself. This article will detail some of the uses of AI in recruitment along with its current shortcomings.

The overall thesis of this article is to advise you that your HR department must view AI as a tool to assist with the recruitment process and not as the recruitment process itself.

How is it being used in the business world?

Big Data

IBM describes big data as “a term applied to data sets whose size or type is beyond the ability of traditional relational databases to capture, manage and process the data with low latency.”

Big data has enabled organizations to collect, manipulate, and utilize volumes of data that far exceed what previous systems were capable of processing. In addition to that, the types of information that can be collected and processed is expanding. In traditional data collection, databases were limited to text or numerical inputs. With big data, the boundaries for what type of information that be curated and databased is growing to include image, audio, and even feeling data. This assists tremendously with AI technology that companies use to scour social media with the intent to understand how their company’s customers are sharing sentiment about the business across digital platforms.

Fundamentally, what big data allows for is greater data context. Further development of AI and its capacity to parse through great volumes of complex data will invariably lead to better customer relationships and increased efficiencies in front end and back end processes alike.

Deep Learning

Deep learning, or machine learning, is one of the driving forces of expanding AI capabilities with big data.

In an article all about deep learning, Forbes describes deep learning as “a subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Similarly to how we learn from experience, the deep learning algorithm would perform a task repeatedly, each time tweaking it a little to improve the outcome…

Deep learning allows machines to solve complex problems even when using a data set that is very diverse, unstructured, and inter-connected. The more deep learning algorithms learn, the better they perform”.

In other words, deep learning is where the utility of big data processing meets the limitless possibilities of artificial intelligence technology. The combination of big data and AI will enable organizations to connect the dots on a scale that was previously unimaginable, drawing insights in real time from what could be billions of data points collected instantaneously from millions of sources.

More can be learned about deep learning from visiting the Harvard Business Review’s Overview of Machine Learning and AI.

As a leader, you may be asking yourself what the practical implications of AI, big data, and deep learning technology can have for your business and recruitment needs. For this, we turn to the power of predictive analytics and algorithm technology.

Predictive Analytics and Algorithm Technology

Predictive analytics is how organizations are able to make complex, statistically modeled, data-informed decisions with large datasets with significant accuracy. Algorithms go one step further and use the data points to make predictions and then act upon them. You may be most familiar with them when you are on an ecommerce site and receive product recommendations that are intimately accurate or when receiving content suggestions on entertainment platforms that perfectly predict your interests.

A deeper dive into the technology and modeling
behind predictive analytics can be found here

How does it apply to recruitment?

Your imagination can run wild imagining the possibilities of predictive analytics and algorithms in the business world, but let’s focus on recruitment. AI has been paramount in reducing time and improving efficiencies in HR work including talent acquisition. The most obvious example of this has been the development of Applicant Tracking Systems or Software (ATS). Below we detail how an ATS works, what the benefits and drawbacks are, as well as a recommendation on how to incorporate AI in your recruitment processes.

Applicant Tracking Systems (ATS)

According to Jobscan, an ATS is “software used by companies to assist with human resources, recruitment, and hiring needs. While each system offers a different package of features, applicant tracking systems are primarily used to help hiring companies organize and navigate large numbers of applicants”.

The simplest way to understand ATS, and perhaps its most noteworthy function, is keyword scanning technology. An organization will post a job description onto a job board, applicants will apply with their resumes, and the software will use keyword matching to attribute “match scores” to candidates based on words that are common in both the job description and the received resumes. In short, it creates a sortable, qualified database out of the volume of applications to assist HR teams with identifying talent.

The benefits of ATS

As we learned above in the sections about deep learning and predictive analytics, we can draw the conclusion that the use of an ATS can help improve efficiency.

Here’s a short list of how it can increase

  • Reduce the amount of manual time spent reading through resumes
  • Remove “candidate fatigue” that HR managers may experience going through applications
  • Potentially weed out candidates that may have applied to the wrong position or may be unqualified from the role
  • Identify “non-negotiable” skills or experiences that are mandatory for the job role you are hiring for

Without a doubt, this technology can free up time for HR managers and talent acquisition teams. The efficiency is difficult to dispute. However, you must not conflate efficiency with effectiveness. To rely solely on an ATS in the hopes of allowing technological efficiency to find the right talent, you may be crippling how effective your talent team can be at finding the right candidate.

How ATS fails

The ATS system is a powerful tool to assist a company with combing through pools of candidates. By selecting which qualifications, skills, and experiences make it through “the filter”, hiring managers can quite quickly draw a fraction of worthwhile applicants to explore from an otherwise seemingly endless list of resumes and cover letters. However, the tool is not perfect and in fact, can yield ineffective results if used improperly.

Two major problems of finding the right candidate through ATS alone:

  1. Applicants that outsmart the ATS system
  2. High quality candidates without ATS-friendly applications

Applications that outsmart the ATS system

With increased popularity and usage of ATS systems among companies of all scopes and sizes, the notoriety of the ATS system becomes noted by job-seekers of all skill-levels. By taking a peek behind the curtain, job seekers can game the system by ensuring that they will achieve a high compatibility score through the ATS. They will do this by spamming keywords from the job description, manipulating their resume format, and grooming the details of their work experience and skills to better fit what the HR team is looking for.

  • Because of this you will find that the ATS filter will disproportionately reward job seekers willing to cheat the system
  • Talent acquisition teams will then spend time interviewing candidates that may not actually be qualified but scored highly
    • Worse yet, these ATS processes may influence HR managers by providing a false sense of security that the objective ATS process found a stellar candidate
    • The HR team, now over-relying on AI technology, will already have a candidate in mind for the position before even interviewing them, and allow their justification to extend an offer build around their preconceived desire to hire them

This leads to the other problem that arises with over reliance on ATS tech.

High quality candidates without ATS-friendly applications

In the same way that less qualified candidates can game the system, otherwise high quality job seekers may either not be “in the know” of the ATS technology, or may simply be unwilling to blur the ethical lines of optimizing their resumes based on keywords. However, you do not need to identify moral reasons for poor ATS scoring when instead you can consider quite simple reasons for missed recruitment opportunities:

  • If a candidate uses the wrong file format, they can be penalized by the ATS system
  • According to the Wall Street Journal, “one small error, such as listing the name of a former employer after the years worked there, instead of before, can ruin a great candidate’s chances”
  • For more senior or high skill positions, qualified candidates may not be looking at online job boards for their next position. Hiring for these types of positions may be fruitless if relying on online job posting

This is in no way shifting blame to the HR manager. What this is to say is that it is very attractive to rely on artificial intelligence and expensive tech tools to do the work for us. Talent acquisition teams are not immune to the effects of technological persuasion.

What does this mean for you?

Like a hammer, the use of technology can drive a nail through a board or put a hole in the wall. In other words, AI technology when used correctly is done so as a tool in the belt of a talent expert. This in many ways highlights the benefits of using a recruitment agency or recruitment expert when finding the right candidate for a job. Using an expert in talent acquisition and the candidate pool they have in their own professional database will yield results on par or better than blindly posting a job and filtering it through an ATS scanner. When combining these two approaches, your ability to find the right candidate can far exceed the individual capacity of either the ATS or recruiter alone. In an ideal scenario, your company’s HR managers are able to curate a well articulated job description, facilitate a relationship with a qualified recruiter, and then have then combine the recruiter’s expertise with AI technology to deliver the best possible candidate in the least amount of time.