Re-Balancing Automation and Human Touch: Best Practices for AI in Recruitment

Over the past few months, there has been a significant amount of AI catastrophising and hyperbole.

Recently, at a Talent Acquisition Leadership event, AI divided opinion. This article will highlight some of the key challenges and considerations.

AI is not going away, but how can it be used in a more mindful way to attract and retain the best talent.

The Concerns

Concerns range from the rise of AI-powered auto-apply tools that enable applicants to apply to hundreds of roles simultaneously, to interview co-pilots that assist candidates during interviews with real-time answers to challenging questions, potentially catching employer panels off guard.

Lastly, there’s the notion that AI will radically shrink Talent Acquisition teams by automating manual tasks and resource-intensive processes. But, before we even think about AI and the impact of technology to recruitment, it's vital to get the basics right and for talent acquisition teams to review their current technological roadmap, as well as their current recruitment processes and automation available to streamline and optimise the existing candidate experience.

Harver have produced an excellent diagram below:

The Recruitment Conundrum:

1. If your recruitment process is highly mature and optimised, with end-to-end automation and simplification already in place, it's time to consider advancing your journey with AI.
   

2. However, if your process is inconsistent, manual, lacking in technological enablement with value driven data insights, implementing AI is not advisable at this stage.

The challenge for recruitment is further complicated by the allure of AI and the drive to minimise manual tasks, positioning oneself at the forefront of the industry.

Recruitment is often tempted by the promise of nirvana and AI applications that can scan talent pools to identify candidates who fit new positions. AI is designed to streamline the recruiting process by automating repetitive, high-volume tasks, and that is beneficial.

However, in today’s talent scarcity environment, it’s crucial to focus on skills-based hiring and candidate potential to enhance diversity. There is a real risk of algorithms being developed that hire 'mini me' candidates, leading to self-fulfilling prophecies and limiting diversity.

For example, not all data producing technology and AI solutions help you eliminate bias. In fact, if implemented poorly, it can promote bias.

We saw this with the early adopter, Amazon - who decided to shut down its experimental artificial intelligence (AI) recruiting tool after discovering it discriminated against women.

The company created the tool to trawl the web and spot potential candidates, rating them from one to five stars. The algorithm was flawed. "When you ask the question who has been the most successful candidates in the past [...] and the common trait will be somebody that is more likely to be a man and white."

Just as humans may narrow a candidate pool by adhering too strictly to sector-specific requirements, technology and AI can also limit your talent pool if you impose overly niche criteria. It's the same problem that is posed.

The hyperbole continues, with political pressure to adopt AI - being the latest craze and economic opportunity, without it, we risk lagging behind the rest of the world.

Are we serious about implementing AI in recruitment :)

At a recent event with a member of the UK's Science and Technology Select Committee, the question was posed: How will the future of work change? Could autonomous intelligence be paving the way for a four-day work week?

Autonomous Intelligence: A Game Changer?

In recent times, the concept of autonomous intelligence has gained significant attention. Autonomous intelligence refers to AI systems that operate without human intervention, input, or direct supervision. This represents the pinnacle of AI sophistication. Examples of such technology include smart manufacturing robots, self-driving cars, care robots for the elderly, and even twin agents in recruitment handling much of the workload.

With these advancements, we may finally be seeing the four-day work week on the horizon. Will this new reality mean that employers will gain more profits by decreasing labor costs, or will they embrace the four-day schedule?

The Implications of Autonomous Intelligence

According to the World Economic Forum's Future of Jobs Report 2020, 85 million jobs may be displaced by the shift in labor between humans and machines by 2025, while 97 million new roles may emerge.

You might be thinking that it's finally happened: The robots have won. But don't panic just yet. The reality is that AI is reshaping our world, and we need to get on board.

From a hiring perspective, we need to tread carefully when implementing AI in the recruitment process.

While AI can enhance efficiency and reduce costs, it’s crucial to balance these benefits with ethical considerations and ensure that human judgment remains a key component of all hiring decisions. Whilst AI is going through its teething problems, it’s essential for recruiters to ensure that AI is enriched by human judgement. 

Machine learning can produce self-fulfilling prophecies

AI needs to be handled with care in any recruitment process. Any new AI tool implemented should be based on scientifically validated data sources with proven case studies and adverse impact analysis on diversity.

Steps to Avoid Poorly Implemented AI Solutions in Recruitment:

1. Broaden Experience and Skills Screening: Focus on evaluating a wide range of skills and experiences rather than narrow, niche industry specific areas. This approach helps to avoid the risk of algorithms filtering out diverse talent.

2. Leverage Data-Driven Assessments: Utilise AI-powered pre-employment assessment software to make hiring decisions based on an applicant’s actual skills and potential, rather than just their resume or past experience gained in a specific competitor/sector. This data-driven approach provides a more accurate picture of a candidate's abilities and potential. Remember skills have a shelf life of 5 years and potential always wins for the longer term.

3. Adopt Hybrid Processes: While AI and automation are valuable, many companies are opting for hybrid processes that combine online and in-person interactions. The graduate market is moving back to hybrid having spent years in 100% automation. How can wider TA learn from their counterparts across wider TA. This helps to ensure a better candidate experience, as full automation can often lead to dissatisfaction and reduced engagement.

4. Enhance Candidate Experience: A great candidate experience is key to attracting top talent. Ensure that your recruitment process is not solely driven by automation. Providing personal interactions can significantly improve candidate retention and conversion rates.

5. Use Video Interviewing Thoughtfully: Video interviewing solutions can facilitate remote hiring and offer insights into candidates through their body language, speech patterns, and other non-verbal cues. However, be cautious as automated video analysis can sometimes come across as impersonal or intimidating. Make sure that video interviews enhance rather than detract from the candidate experience. In addition, video interviews are now more open to imposter candidates with the rise of AI.

By following these steps, you can avoid common pitfalls associated with poorly implemented AI solutions and create a more effective and inclusive recruitment process.

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