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The Role of Artificial Intelligence and Machine Learning in HR

August 20, 2018

A report from the McKinsey Institute suggests that artificial intelligence (AI) will be responsible for the automation of 800 million jobs globally by 2030. While the term "artificial intelligence" typically conjures up images more aligned to science fiction, in reality, AI and machine learning (ML) are already incorporated into a range of day to day activities and are very commonplace. The potential of AI and ML offers many opportunities to automate a variety of activities and enhance the quality of recruitment decisions.  

What is it?  

AI and ML are typically used interchangeably but they are not the same thing. AI is a branch of computer science attempting to build machines capable of intelligent behavior. This can be broken down into applied or general. Generalized AI in principle can handle any task, while applied AI is designed to do a specific activity. On the other hand, Stanford University defines machine learning as “the science of getting computers to act without being explicitly programmed.” Both applied AI and ML are being incorporated into HR technologies. 

How is it being used? 

AI and ML for recruitment have potential for many applications. However, the most commonly referenced is automating high-volume, repetitive tasks such as CV screening, application reviews, chatbots, and applicant testing. Many organizations are currently integrating AI and ML technologies into existing online platforms such as applicant tracking systems and video interviewing tools, with the goal of intelligently screening individuals based on large quantities of existing data. In addition, there are also some providers looking at creating AI chatbots that provide real-time interaction to candidates by asking questions based on the job requirements and providing feedback, updates, and next-step suggestions. 

The scope of AI and ML is very broad and some of the trends reference the use in every aspect of recruitment. However, it should be noted that they are not aimed at removing recruiters from the process but to augment what they are currently doing. The potential of these methodologies are endless and will arguably have the biggest impact on recruitment. PricewaterhouseCoopers reports that 40% of the HR functions of international companies are currently using AI-applications. However, it will be interesting to see whether GDPR and other legislation will impact how AI is utilized in the high stakes world of recruitment.   

Benefits 

  • Enhance decision making: The use of this type of software may increase the quality of the hiring decisions as it is using data to improve the decisions that are being made. 
  • Reduce unconscious bias: Many providers highlight that the use of this may reduce unconscious bias by ignoring information such as a candidate’s age, gender and race.  
  • Enables more focus on meaningful activities: CV and application screening is still one of the most time-consuming activities. Therefore, if this is done automatically, it may enable people to focus on other areas of the hiring process.  

Key Considerations 

  • Data led: AI and ML are completely objective but they are dependent on the quality of the data being used. It also requires thousands of data points. Therefore, it may present challenges if recruiting in lower volume for job roles.  
  • Perceptions of fairness: Whilst these new technologies are first being adopted there may be some challenges in relation to candidates’ and stakeholders’ acceptance. Especially when the scores generated are being used to inform high stakes decisions. Therefore, having a sufficiently clear rationale that can be understood and transparent enough will be a key challenge to making sure the process is perceived as fair. Interestingly, in our own research of graduates, 59.7% indicated they would be “comfortable” or “very comfortable” with AI taking a role in their initial screening process, suggesting there may be demographic differences in how these approaches are perceived.
  • Need for human interaction: When considering the extent of usage of these technologies, the amount of human interaction with the candidate needs to be considered. Research by Randstad suggests that 82% of respondents agree they are often frustrated with overly automated recruitment experiences. Therefore, when using these technologies, it is worth considering how they are used and when you may consider integrating human interaction.  

Discover more with our webinar 

Emerging Trends in Talent Management: 5 Ways to Captivate Candidates 

You can hear more about our thoughts and recommendations on AI and machine learning in our recent webinar: Emerging Trends in Talent Management: 5 ways to captivate candidates. 


 

Ali Shalfrooshan is a Managing R&D Consultant at PSI Services LLC.

Click here to learn more about PSI’s Talent Measurement solutions.

Claire McCue Claire McCue Claire is the Digital Marketing and PR Manager at PSI. She specializes in content marketing for the talent management, leadership, higher education, certification, and licensing industries.