Question

Some people believe that the use of staffing technology and software is wrong because it dehumanizes the staffing experience, making it nothing but a mechanical process that treats applicants like digital widgets. Others believe staffing technology helps organizations identify the most qualified applicants while weeding out those who are not qualified at all, making the hiring process smooth and freeing up the HR department for other tasks. Where do you stand on this topic? Defend your position.

Answer 1

As the manager, we need to hire the right people for the right position in the first place. This means that not only would the initial recruitment needs to be standardized, but also the fact that human tendencies towards bais do exist, be it due to experience, likeness or something similar to “just like me” error, we do have the tendency to let bias creep in no matter the level of objectively we display. It can be argued that for this reason alone, the use of AI should have ample application as a possible fix to staffing problems. It does not dehumanize as much as it standardizes the process, teaching the HR executives the best patches to prepare for the recruitment process. This level of preparedness would have the benefit without the technology but with the technology, sifting through a large pile of resumes becomes less tedious and more functional. We need to consider the benefit it brings to the organization in the form of saved time, recruitment cost, training cost, turnover costs in the sense that employees that are most suited for the job being offered would need less training and would have more engagement and morale to do their jobs.

The counter-argument of dehumanization is however also valid in the sense that the level of expertise some managers have with regard to the future potential of an employee is not properly replicated by a machine as of yet, and this is where a hybrid approach would make the most sense, where individuals the automation systems go through the resume and provide the necessary intel to the staffing managers which then see why some of the candidates were rejected, the most prominent candidates and even, through(deep relearning algorithms), the candidates that show potential but not for the current position, so that the essence of the process can be preserved while simultaneously making it far better than manual application.

The problem is with fully autonomous decision making which I agree should not be left solely with a system. But with the advancements that have been shown in the field of machine learning in the recent years, especially in deep learning paradigm, means that we are moving towards a fully autonomous system with human-level intellect and ability to process information like a machine to then make the decisions for us, but that application is at least 5 to 10 years into the future.

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