The Need for Man-Machine Harmony in Shortlisting Candidates
The introduction of Artificial Intelligence (AI) and Machine Learning (ML) into the employee recruitment process has taken global industries by storm. As the world rapidly converges into using computer processes to streamline operations, no application stands out quite like self-learning data management and predictive assessment. The new generation of technology has now become an integral part of business optimisation.
But is complete digitisation the best option for talent acquisition?
Digital Platforms for Talent Acquisition
In a study conducted by international talent acquisition and management brand Alexander Mann Solutions in 2017, it was concluded that nearly 96% of HR professionals believe in the potential of AI in enhancing candidate recruitment. This statistic has only appreciated in the four years leading to today.
However, this is quite misleading in the bigger picture. The process of talent acquisition involves a lot more than just technical assessment. Sure, recent developments in AI, including chat-bots such as Olivia and video recruitment platforms such as Paññã, have revolutionised employee recruitment. But they lack the many essential qualities of humans which determine the retention of recruits in the long run. Therefore, it is important to make use of this growing technology responsibly, especially when assessing the bread and butter of your firm’s operations.
In order to put things into a simpler perspective, let us look at some merits and drawbacks of digital recruitment systems:
Merits of Digital Recruitment
- It decreases human bias by disregarding influencing factors apart from skill such as race, gender, ethnicity, etc.
- Increases recruiting efficiency, removing the need for manual data manipulation.
- Improves candidate engagement by limiting the interaction to only basic requirements.
Drawbacks of Digital Recruitment
- Digital solutions may not always be 100% reliable.
- The nature of digital assessments allows its program to be cheated by a knowledgeable individual, thus, reducing reliability.
- Human intervention will still be required to make up for the algorithm’s lack of experience in judging abstract features such as character and personality.
Platforms for Technical Assessment
Various other evaluation tools are also available to assess only technical skills such as coding. However, these do not seem to be good alternatives when looking at their high dropout rates. This is due to the purely answer-based nature of the assessment with little to no attention to problem-solving approach, skill, etc. Such binary approaches to candidate evaluation is never a good idea for candidate retention and operation sustainability.
It is essential to recognise the significance of current technology in streamlining candidate recruitment. Although the field is still growing, continuous application and bug-fixing is the only way to build this process. However, for now, and for the foreseeable future, the use of AI/ML will play a vital role in employee recruitment when combined efficiently with human interaction. This is why at HireHunch, we believe in predictive hiring and not just conditional hiring. Our AI software streamlines technical candidate evaluation while our veteran team makes the final call.
To learn more about our process, visit HireHunch and connect for a demo today!