For many, AI conjures up images of Hal from 2001: A Space Odyssey. A good idea in theory, a dystopian nightmare in practice. But despite our apocalyptic fears, AI is strangely marketed as a recruiter’s new best friend. In fact, I can’t help but wonder that if they’d named it Augmented Intelligence and not Artificial Intelligence it would have been widely adopted already.

Alas, plenty of recruitment software companies like to shout about their “cutting-edge AI” and “machine learning algorithms” – something that us mere mortals will never understand – and it seems to work: 96% of senior HR professionals believe that AI can highly leverage talent acquisition and retention.

But what exactly is it? And what implications does using AI in recruitment have for your company? In this post, we will be deconstructing the term “Artificial Intelligence” and looking at the benefits (and limitations) of AI recruiting in 2020.

What sort of AI is used in recruiting?

First off, it’s important to know that AI is a general term that covers several types of machine learning. Technopedia succinctly defines AI as “the creation of intelligent machines that work and react like humans”.

Basically, AI is machine learning that mimics human intelligence such as decision-making, visual and speech recognition and translation.

But how does it work? Put very simply, AI is made up of complex algorithms that analyse large amounts of data, find patterns and then make determinations based on prediction. What’s more, these algorithms don’t need constant tweaking by human coders, they improve themselves based on evolving data!

The large quantities of applicant data gathered in the recruitment process is a natural resource for AI. Especially if you have a high turnover of staff or volume of applicants for a specific role. For example, most applicant tracking systems track candidates through the recruitment process. Then attempt to match their skills to job roles. But this is just the beginning. Read on to see all the different ways you can implement elements of AI in your recruitment process.

How to use AI in recruiting

Candidate sourcing

AI can save a lot of time by automatically scouring the web for social media profiles, publications and other search engine results that may provide insight into which candidates will be both suitable for and receptive to new opportunities.

When AI is used in walled platforms such as job boards and social media sites that’s fine. However many third-party tools now claim to do this from outside of platforms using “publicly available data”. There are question marks over the legality and morality of using these tools with many people arguing that it breaches personal data rights.

Scheduling interviews

Scheduling interviews is a simple but time-consuming task that most people would be glad to offload to AI. You can purchase clever tools like Calendly, Doodle or X.ai outside of your ATS, but hopefully, your ATS has an interview scheduling feature already built-in.

Candidate screening

Research suggests that up to 75% of CVs are under-qualified. Sifting through them is time-consuming. Having an algorithm to pre-select only the most suited candidates will save you time to more rigorously evaluate those with the right skills and qualifications. 

You can use AI in different ways here. It can use data from unsolicited information; such as social media profiles or facial movements on video calls to identify suitability. We’d recommend avoiding these types of solutions unless you want a lawsuit to come your way.

Or you can use it to identify job suitability from pre-authorised, job-relevant data such as resumes or pre-hire assessment scores. For more information on candidate screening tools check out our guide to pre-hire assessments.

Candidate re-discovery

Did you have suitable applicants in your last cycle that didn’t get the job? Candidate rediscovery is particularly useful for people who recruit at scale or employ seasonal workers. AI can be used to analyse your talent pool and make recommendations on who might be available when you’re next looking to hire. AI-powered Talent CRMs or ATSs can send timely updates, and alert you to candidate behaviour on social media sites such as LinkedIn.

Diversity hiring

Unconscious bias is unavoidable in hiring, however, you can reduce it by using fair and objectively scored pre-hire assessments instead of manual CV reviews. The role of AI isn’t significant in reducing bias; in fact, many AI solutions can perpetuate biases if they are trained on pre-existing “biased” hiring data. 

White-box, transparent assessment solutions, like ThriveMap can provide you with an audit trail of how each candidate was scored against the job-relevant attributes you identified in your ideal candidate profiles. Black-box AI solutions can’t provide this transparency which can lead to candidates taking out legal action against you.

Replicating “human” contact

One of the functions of AI in recruiting is that it can react in real-time to language. Some companies have used this technological development to create “chatbots”; the little chat bubbles that appear on many career pages asking applicants if they need help. Many chatbot providers claim that applicants are more likely to complete an application if they have a chatbot to guide them through the process. There has however been some public backlash on chatbots being used to dehumanise the hiring process.

Interview analysis

Recent advances in AI technology include the ability to analyse facial expressions, spoken language and body language of applicants. This is particularly relevant given the increased dependency on virtual interviews and the more general movement towards remote hiring. This is a relatively new technology and isn’t commonly adopted in hiring because of legitimate concerns about cultural differences and context not being picked up in the algorithms, but it’s definitely one to keep an eye on.

The limitations of AI

It requires lots of data

The amount of data needed for an algorithm to assess a candidate’s suitability for even a single job role is huge. Before employing AI in your recruitment process, you should consider the diversity of your job roles and the volume of applicants. Candidate selection algorithms will have a better payoff if you’re regularly hiring a lot of people for the same position.

It’s not totally unbiased

While AI may help to remove unconscious human bias from your recruitment process, it’s not a silver bullet. Because machine learning algorithms work by finding pre-existing patterns from analysing biometric data from existing employees, it’s possible that the AI may unknowingly mimic any existing biases. AI finds patterns, not causes. At the end of the day, you’ll also need real human intelligence to make sure your hiring is truly fair and inclusive.

It can make mistakes

One of the biggest appeals of AI is that it removes the possibility of human error… almost. There’s always a chance of error in the data that the algorithm uses to find patterns, learn and improve. If this happens then it can be very difficult to correct the error after the AI has already “learned” from it.

Candidate scepticism

Ever since AI’s implementation into business, there have been fears that robots will take over our jobs; think of self-checkouts and driverless trains. While the reality is that more jobs are created than are lost with advances in technology, this fear of AI definitely hampers the rate of its implementation. This fear extends to candidates who may want to know why they have not been selected for an interview. Again, white-box candidate screening solutions like ThriveMap can help here by providing companies with a transparent selection process where others can’t.

Is it actually “artificial intelligence”?

The futuristic, sci-fi connotations of artificial intelligence mean it’s become something of a buzzword in recruiting, when in fact very little of the technology and software used is really artificial intelligence. Matt Alder, of the excellent Recruiting Future podcast, says “we don’t actually have any genuine AI in recruiting.” This isn’t to say that software that matches applicants to jobs isn’t useful. Just that it isn’t necessarily AI. 

So beware of recruiters and software companies that sell their services on their “cutting-edge AI”. Because it’s likely that the marketing is ahead of the science.

In closing…

It’s all too easy to misunderstand the role of AI in recruiting. It’s worth taking a look at what tools are best for your business before implementing AI into your process. 

If you’re a volume recruiter looking to reduce your time-to-hire, automation is definitely a good option for you. However, rather than getting caught up on the solution you need, think deeply about the problem instead. 

AI is not a silver bullet that can fix all your problems. At the end of the day, recruitment is about people, and (at least at the moment) we can’t rely on technology to do it all for us.