Article: The opportunities (and threats) of using AI during recruitment


The opportunities (and threats) of using AI during recruitment

AI promises a bundle of opportunities when applied to business processes. But how is it slowly changing the face of modern day recruitment?
The opportunities (and threats) of using AI during recruitment

The ability for machines and programs to learn and improve human operations, while significantly reducing costs has been a great force of change within modern day corporations. They, as a result, are reshaping the most ‘human’ part of companies today; their human capital management. One of such applications is of AI within recruitment of candidates

In addition to enabling recruiters to deal with change better, AI helps improve the process, one that is fraught with systemic inefficiencies and biases (both conscious and unconscious) that hamper the recruitment process. This is done by identifying and recruiting the right candidate. To take a better look we consider the following four cases:

Automating transactional workload

For recruiters today to needed to make long-term talent decisions, something that is only possible when their time taken in dealing with operational burden is reduced. This one the foremost areas where AI can prove beneficial to the recruitment function. By automating low-level tasks and providing key insights faster, AI successfully frees up valuable time that recruiters can use to address more vital issues. Instead of wasting precious hours chasing operational tasks, AI enables the productivity of recruiters to meet the talent needs of their companies to go up significantly. 

Creating organization-wide learning 

Effective recruitment often contains the following steps identifying business needs, finding the right talent pool, sourcing the right candidates and having the correct screening and review mechanism that ensures only the best fit is hired to fill the empty position. Although recruiters might crack the formula for it once, with the help of AI, this learning becomes a part of how the organization does the future hiring. With the help of AI, recruitment data can effectively be used to hire instead of starting from scratch every time a position within the company needs to be filled. 

Making smarter decisions

Besides just assisting recruitment teams to automate transactional work, AI will also change the way critical talent decisions are taken within the function. As AI has the computational power that enables it to make objective, data-driven, and often bias-free decisions, its use within the recruitment function would not just improve decision making of recruiters but also help them contribute to business growth by hiring the right candidates. 

Linking competencies to the right job roles

With businesses becoming more competitive by the day, the pressure on recruiters to find the right fit for the company has also gone up. AI can help out by creating more holistic ways of assessing candidates fit for the job role. By identifying certain qualifications, educational history, behaviour traits, work experience and other factors that would indicate a candidates suitability to the job role, the “best fit” for the job can be recruited. This exposes recruiters to a way that’s different from their usually intuitive way of making hiring decisions. 

To effectively use AI and avoid some of the potential pitfalls of using it within recruitment processes, it is important to understand some of the ethical and procedural implications it poses. The following cases become of importance for employers to be wary of during the recruiting process that leverages AI.

Can increase incidents of snooping

AI like many other technologies of our time is a powerful resource that can help its wielder perform a lot of meaningful tasks. With the use of AI, collecting data and drawing assumptions to understand the candidates' behaviour and predicting their future performance might lead recruiters into breaching the privacy of their candidates. 

With different governments slowly waking up to the potential harm such overreaching AI and prediction software can do, recruiters and HR professionals need to establish clear guidelines on how social and private data of a candidate is being used. This should not only be done from a compliance perspective but also taking into consideration the ethical aspects of data snooping.

Predicting biased outcomes

When it comes to HR processes biases, both conscious and unconscious in nature, often creep in how they are run and executed. Often arising due to the subjective and impressionistic nature of managing human talent it’s a hindrance to recruiters when it comes to hiring the best talent. But such biases can also creep in AI platforms.  

Human biases can be coded into machine learning algorithms. Even when that not the case, learning from data of previous hires, AI can learn to emulate similar biases. Although AI holds great promise in being an ally to eliminate human bias from the recruitment process, there still remains a potential for it to fall into the same trap.  

Scepticism of new technology

AI is yet to be accepted as a way to make human decision making more efficient as it still remains a technology that not everybody completely understands. With the application of AI within recruitment processes is still at an infant stage, recruiters might just give in to their scepticism and allow their judgements to alter AI results. For greater effectiveness, more industry best practices need to be created. Even recruiters would need to reskill to understand the nuances of AI programs better. It becomes especially relevant with regards to mid and small level businesses where recruiters need to be sure that any software that will automate one of their work tasks is going to be able to do as good of a job as they can.

The final responsibility

Within traditional recruitment processes, efficiency could be obtained by clearly identifying the source of the problem and rectifying it. The response would generally be training recruiters or tweaking talent acquisition strategies to reach closer to the desired result.  But in the era of AI-driven technologies, the lines are not as clear. Machine learning algorithms figure out for themselves how to react to events, and while data gives them context, not even the developers of those algorithms can explain every single scenario and decision that their product makes. Given that this tool would increasingly be used by HR practitioners who are yet to develop their skills in handling such programs, addressing faults in the system could pose a problem. 

The utilization of AI to improve recruitment is only going to go up in the coming years. Recruitment, like many other business functions, are sure to benefit from AI making the decision easier for them. But at the same time, faster and cheaper prediction does not automatically solve the fundamental challenges of recruitment. Organizations still need to understand their talent needs better to fruitfully utilize the potential of AI. It is only when they have clear, solid measures of human performance that they can build meaningful models to predict performance and quantify a person's suitability for a role or job.

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Topics: Recruitment, #Hiring

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