“Artificial Intelligence is the study of how to make computers do things which, at the moment, people are better.” – Elain Rich (computer scientist)
This quote by computer scientist Elain Rich describes artificial intelligence as systems and technologies that are intended to relieve humans of redundant work and to make our everyday lives easier. These technologies are deployed in more and more areas of our society to automate various processes. They can also be used in personnel recruiting. Here, in particular, technologies such as machine learning and big data analytics can be applied.
What is machine learning and big data analytics?
Machine learning is the automatic recognition of repeating patterns. Based on these patterns a system is able to set up own rules by which it operates once certain processes occur again. Such systems and their technologies continue to develop independently and are able to “learn” reacting to patterns accordingly, which in turn improves them continuously.
The term big data analytics describes the process of collecting data in infinite quantities and evaluating it. These evaluations in turn are used for recognizing patterns in order to enable machine learning. In this way, processes can be automated and improved.
Artificial intelligence in personnel recruiting
Without the use of artificial intelligence, the recruitment of new employees can be a very costly process for a company. The flood of applications requires a lot of work and time (and therefore costs) for the HR department to find potentially suitable candidates which have the right skills and qualifications for an advertised position. By using an AI-based system, companies are able to simplify and speed up this process by automatically searching applicant data and filtering it for the desired results.
One way of using AI in personnel recruitment is to use CV parsing. This involves selecting applicant data from CVs and online profiles and merging it into an applicant database. Afterwards, it is possible to search automatically for applicants with certain characteristics. Even the first qualification interviews with applicants could be conducted with AI-based video systems or chatbots to make a pre-selection. Here, questions predefined by the company are asked in order to query an applicant’s knowledge and work experience. Depending on the suitability of the applicant, the hiring process can then be continued with an employee of the HR department.
On the part of the company the advertisement for the vacant positions is just as important as the process of applicant selection. Therefore companies can also use artificial intelligence to address as many (preferably suitable) applicants as possible with their job advertisement and to place them in an advantageous position. For example, an AI-based system such as developed by the start-up 100Worte GmbH can be used to optimize job advertisement texts. Their system is able to compare the text with many other job advertisements on the basis of the big data principle and draw conclusions from it. Thereby, the system can make suggestions for improvement to a company’s job advertisement text. For example, it is suggested to adjust the length of the text or to use other words that are more appropriate to the applicant’s motives.
The placement of the job advertisement is also an important factor in view of the number of applicants. For companies, it is decisive which channels are used by the most and best applicants. For example, the HR operating system “Personio” can be used for such a purpose. Based on evaluations of numerous recruiting websites, it is able to find the best placement for the job ad and guarantees higher visibility.
Currently, only 3.9% of all companies in Germany use digital tools for recruiting, although advantages such as time savings, cost reductions and process accuracy speak for the use of AI in human resources.
The companies usually cite a lack of technical knowledge as a reason for not using it. Whether and how the use of artificial intelligence in recruiting will develop in the future remains to be seen.
An Article by Maja Rubinstein, Carolin Scheu, Sarah Schmitt, Teona Burnadze and Edith Schwegler