3 Mistakes To Avoid When Using AI In HR

Today, artificial intelligence is increasingly used for solving HR tasks, but before introducing AI in recruitment processes, one should look at this technology from different angles and find pitfalls — without knowing them, it is impossible to use an AI system at its full potential. We would like to tell you about three mistakes that must be avoided when using AI in HR, otherwise the effect of an HR solution will only be partial. So, one should not:

1. Use low-quality data

In computer science there is the GIGO (Garbage In, Garbage Out) principle, which means that flawed or nonsense input data produces nonsense output, even though the algorithm itself is correct. Of course, this is very important for systems that use artificial intelligence, without data of good quality, software’s decisions just cannot be relied on.

2. Ignore the importance of confidentiality and data security
AI systems in HR primarily deal with data on individuals and this information should be treated with extreme care and stored securely. When introducing AI in HR processes, it is necessary to make sure that access to sensitive data is strictly limited. A great option for storing information securely is blockchain technology. By the way, this exactly why its development is important for GoRecruit.

3. Disregard «leveling-up» the workers’ skills in advance
Before adopting an AI solution, one needs to make sure that employees ready to work with it, know who it functions, what tasks undertakes. Or else there is a danger that a program will be used incorrectly. Though with regard to GoRecruit, everything is simple, you only need to authorize a job applicant in the system, evaluate him, compare with other candidates and then invite for an interview only the applicants with the highest scores.

The popularity of AI-based solutions for HR is constantly rising, but if companies blindly chase technology without knowing pitfalls of such solutions, they might receive suboptimal benefits. We told you about three possible mistakes that organizations should pay attention to, otherwise the effectiveness of a recently acquired Ai system is going to be questionable.