Artificial Intelligence has literally become the new buzzword for corporates across the globe. Whether it is technological applications, assistance provision, knowledge base creation, or recruiting and talent acquisitions, AI has been amping up its role in the business world.
But, since we are a HR-Tech start-up, we will restrict to the relevant bits. In one of our previous blogs, we had talked about how AI is changing the face of the recruitment world. In this one, let us look at the pitfalls that need to be avoided! So, without much ado, let us have a look.
5 Mistake to Avoid when using AI for Talent Management.
A thorough analysis of technology needs to be done before implementing it in the business process. The more aware we are of possible pitfalls, the more we can optimize machine learning and artificial intelligence to our advantage. Given below are five mistakes to avoid when using AI for Talent management.
Assuming that AI can play over purely human roles
No doubt a mechanized process well equipped with AI can narrow down a lengthy list of applicants to a more manageable shortlist based on certain parameters, BUT it is unreasonable to expect AI to carry out more human roles than this. A case in point is that the AI tech, an Israel based startup, Faception released. They claimed that this tool could analyze the facial structure of candidates and, from it, gauge their IQ, personality type, and even their tendency to exhibit violent behavior. On their website, they showed various types of facial structures and labelled them as “high IQ,” “academic researcher,” “professional poker player,” and more so “terrorist.” This was a highly derogatory and questionable conclusion to be drawn by the company and was also downright ludicrous. This is when claims of the potential of technology go from ridiculous to unquestionably discriminatory. Personality tests and personal interviews are as important and relevant today as they were decades ago. This is something that must never be overlooked because HR decisions should always be people-driven.
Not Emphasizing on data size.
It is advisable to proceed with the utmost caution when it comes to the implementation and management of AI in Hr processes. This exercise demands a large number of skills and expertise. The size and scale of data matter to a great extent while taking various HR decisions. It is a well-known fact that effective statistical interpretation requires samples of significant size so as to avoid any erroneous results. It is the same for data analysis. Allowing for a large amount of data to be fed into machine learning models also enables the inclusion of all possible scenarios, thereby side-stepping glitches in decision making that could have perilous consequences in the future.
No upskilling before the implementation of the AI process.
The most obvious and perhaps the most pertinent point is that Hr professionals need to become more data fluent. It’s important for those in the Human Resource field to view their function as data-driven. Implementing a range of AI-equipped processes without the requisite training and proper insight and guidance from domain experts can not only leave the HR department in the lurch but can also lead to faulty use of Ai tools, thereby affecting decision making and costing the entire organization, not to mention a whole host of potential employees. Muddled and poorly managed AI system then succumb to the very same human biases that they are designed to side-step. Hence, it is advisable to start in a small sample and then extend eventually. Once preliminary training and expert advice are absorbed, the HR department will be ready to incorporate sophisticated tech tools.
Though AI most certainly has revolutionized the entire hiring and HR space and brought about positive changes in the work environment, it is not free from glitches. From monitoring workplace issues to keeping track of the individual stress levels and productivity, AI tools can not only alert leaders about their team’s general morale but can also predict incidents of data theft and cyber-attack by observing the unusual activity. But this comes at a cost. There is a lot of invasion of privacy if viewed from an employee’s point of view. Not only do such processes require utmost transparency to be implemented, but the implementation should be based on the consent of the workforce. Otherwise, it can lead to a breach of privacy and personal space of the employees.
Not prioritizing the importance of bias elimination.
Ai learning is often susceptible to bias, which may lead to misleading results, which in turn can jeopardize the entire decision-making process of the HR department. The whole concept of AI is that humans are training technology to behave like humans. And if humans have garnered biases over centuries, it is only natural that these get unconsciously taught to artificial intelligence programs. It becomes rudimentary to become extra conscious of human biases and consequently eliminate any chances of associated machine-made errors.
So, that was all folks! As a responsible organisation, it is our duty to let our prospects know of not just the advantages but the cautions that need to be taken too!
We feel that we did a good job at that!
See you with another blog soon!
See Also: The Rise of AI in Talent Management