AI and Recruitment
This article aims to explore how Artificial Intelligence is changing the various facets of Human Resource Management and in particular, the process of talent acquisition.
AI and Recruitment
July 29, 2022 7 MIN READ
Arthur Schopenhauer, the German philosopher once said that change alone is eternal, perpetual and immortal. Over the last two decades, every single sector of the economy has witnessed some form of disruption driven by technology and the HR industry is no different. This article aims to explore how Artificial Intelligence is changing the various facets of Human Resource Management and in particular, the process of talent acquisition.
Background:
The “Great Resignation” or the “Great Reshuffle” in the last two years has shown how talent acquisition teams struggle when facing high attrition – exposing and exacerbating the inherent issues in their processes. Deloitte’s 2019 Global Human Capital Trends survey1 showed that these issues existed before the 2020’s pandemic as well. It found that only 6% of respondents believed that they had the best-in-class recruitment processes in technology, while 81% believed their organization’s processes were standard or below standard. The need to transform traditional talent acquisition and on-boarding is the need of the hour, and the integration of artificial intelligence into these processes could lead to the disruption this industry needed.
Use-Cases:
The first important use-case of Artificial Intelligence in the field of recruitment is efficiency. The current process of candidate sourcing is both cumbersome and expensive. Whilst most firms prefer to have the entire Human Resource function in-house, external recruitment consultants have to be hired as well if positions need to be urgently filled. This practice not only impacts the bottom line but also leads to a loss of control which defeats the purpose of having an in-house HR function in the first place. Owning the head-hunting function also poses several issues as HR managers would rather have their employees focus on the more strategic elements of their scope than scouring through multiple applications to find the right matches for available jobs and other low-level administrative duties of that ilk.
This is where Artificial Intelligence comes in. Using AI to evaluate large volumes of data points relative to the local market including listed salaries by competitors will not only ensure that the best candidates are selected for an interview but will also provide the HR department with the information needed to make the most competitive offers. It can increase recruiting efficiency by matching a specific offer with an individual’s employment history to calculate the probability of a candidate accepting the offer as well2.
Since firms heavily rely on employee referrals to fill vacant positions, AI can be used to analyze performance data from previous referrals and recognize when candidates similar to successful employees are being recommended3 – as quoted by Adriana Bokel Herde, Pega’s chief people officer.
Another critical use case for AI is in the rediscovery of candidates. By maintaining a repository of past applicants, an AI technology can evaluate the existing pool of applicants and compare them with past applicants to ensure the best fit for vacancies. This way the HR professionals can use technology to quickly identify suitable employees4.
The past few years have also put a renewed focus on the need for diversity, equity and inclusion (DEI) in recruitment processes as cases of racial and gender inequality come to the fore. The fundamental issue of relying solely on manual recruitment is that humans can’t eliminate subconscious bias. However, if the data input into the AI systems is blind to non-critical fields like gender, race, age and disabilities, they can ensure that there is no element of bias in their selection process. Only critical data points can be used to evaluate a potential candidate’s ability and fit for the vacant positions. This can help diversify a company’s workforce and promote a culture of inclusive growth.
Challenges:
Whilst AI is being touted as the answer to eliminating the subconscious bias which affects talent acquisition, some critics are worried that this bias will simply get automated. The Amazon case of 2018 comes to mind, where Amazon decided to shut down its experimental AI recruitment tool after discovering that it downgraded women’s CVs for technical jobs and preferred male candidates. The issue with such algorithms is that they are solely reliant on historical data as a starting point, and past data is again full of inherent human bias and discrimination. In the case of Amazon, its algorithm scanned all CVs submitted to the company over ten years to learn how to spot the best candidates. Given the low proportion of women working in the company, the algorithm quickly spotted male dominance and thought it was a factor in its success5.
Another question that businesses ponder upon is whether the cost-benefit analysis of adopting an AI-recruitment algorithm would yield positive results, as adopting such a recruitment tool would not only require substantial capital at the time of purchase but also require constant monitoring to ensure it doesn’t amplify biases it aims to prevent, similar to the Amazon recruitment tool. Since the HR Department is usually viewed as a cost center rather than a driver of revenue, managers might be eager to increase automation to cut costs without doing a thorough analysis of whether such automation would be beneficial to the company.
Conclusion:
It’s safe to say that since AI-based recruitment algorithms and their corresponding predictive analytics are at a nascent stage, the possibility of a dystopian future where the recruitment process is completely automated seems remote and daresay impossible. Since the technology requires large volumes of data to aid its decision-making process, it would lead to the creation of a parallel industry of AI audits to maintain a checks and balances system. These audits would become a necessity to ensure that the input data is free from inherent biases and that no biases creep into the algorithms at any point in time lending further credence to the notion that AI will not replace humans but will only create new jobs in the economy. Without the use of AI, employers will struggle to recover from the Great Resignation hence, for now, industry best practices dictate a combination of human sensibilities and AI-fueled efficiency.