Technology is the future of business, and hiring remains an important part of business success.
While AI recruiting has its time-saving qualities, many organizations and HR recruiting teams feel wary about relying completely on its technological advances and algorithms. There is, of course, nothing like the human touch – but the success of AI recruiting actually requires talented and knowledgeable human beings to ensure that its challenges are overcome and that candidates get the best hiring experience.
Why is this important? Well, a candidate gets the first sense of how your brand works by the way they are treated when they are being considered for a position. Companies that are interactive, respectful, and willing to consider the candidates’ needs are often ranked higher and garner more interest than those that do not practice these basic tenets of hiring. Remember, it’s not just you hiring a candidate – a candidate is also hiring you and considering you for the next step in their career.
AI recruiting software allows for a better hiring experience on both the candidate’s and the hiring team’s ends, as long as challenges are identified, trouble-shot, and overcome in order to maintain efficiency on every level of hiring, and so that the ROI of the AI software is clear.
Challenges of AI recruiting
While AI is often marketed as being free from non-human biases and problems, the fact is that it is a computer that has a primary purpose of learning. Here are some of the challenges that HR teams can face when it comes to AI recruiting and algorithms:
- AI requires a lot of data – with the current worry about how organizations and companies use data, this can be a red flag for candidates who want to keep their personal data private. Another issue is that the software may require hundreds to thousands of resumes to screen for one single role in order to be able to offer the best choices for filling it.
- AI can be become biased – while it isn’t made to mimic human biases, AI recruiting programs can learn bias, even though it ignores information like age, gender, and race. This is because it’s trained to find patterns in previous behavior. Therefore, if your recruiting team is already biased, even if it’s unconscious, the algorithm can be trained to pick up on these biases and apply them to future candidate screening.
- Technology can break – and this is often why HR teams are skeptical of AI recruiting. If the technology suddenly starts screening based on wrong indicators, or the system goes down, automation doesn’t save time, it adds time. Add to that a healthy fear of new technology and programs that “fix what isn’t broken”, and you might have team members who are wary of using this new technology, even if it may make their lives easier, because they aren’t convinced the software can do as good of a job as they can at their work.
Luckily, there are ways to solve these challenges and get your team on board. In the end, it’s about selling the technology to your team and training them properly. The next section will explain the best ways to work around these challenges in AI recruiting software.
How to overcome challenges in AI recruiting and deliver the best experience to candidates
AI recruiting is based on algorithms that are trained to spot patterns, especially when it comes to large chunks of information. To do this, it requires the buy-in of a lot of data, because keyword spotting, sentence structure, skills – the screening must view a lot of data in order to find patterns in it. This can be an issue, especially with today’s world that’s wary of giving up a lot of private information, fearing that it won’t be safe or used properly.
You can get around this by being upfront about data collection. Following the rules and regulations governing data collection in your region is the first step. Posting clear messaging around data collection is a good way to let candidates know exactly what their data would be used for and how it counts in the hiring process. Most people want to stay informed – this is a good way to inform them and still attract the top-level candidates you want. Letting candidates know that public data sources may also be used is transparent, and reminds them that their public information is, in fact, public.
While AI technology is made without bias, having human administrators of the software can help cut down on biases within hiring that the software may learn. If you are finding that you’re interviewing the same candidates with the same race, gender, and age markers, it may be that your software is specifically prizing those candidates over others. Having a robust, diverse hiring policy can help eliminate these biases and attract candidates with a vibrant set of skills who may not fit the “mold” of who you usually hire. For example, many companies these days are heavily promoting diversity recruiting. However, recruiters are sometimes unaware that their “voice” can heavily affect how candidates see the business and the job, attracting those that may not fit the profile of who the organization is looking for.. Tools such as Textmetrics are able to assist in eliminating gender bias job descriptions by detecting male and female-centric wordings and giving its users „neutral“ suggestions, making the text friendlier to all potential candidates. While candidates must be a good fit for the organization, it’s important to remember that diverse hiring actually makes your organization better, and can bring new creativity and skills to the role.
A good and clear training program on the software will eliminate any fear when it comes to new software or changes within a job process. While there will always be team members who will worry about change, showing them how their jobs can be better and more efficient is a great way to sell them on the new technology that AI recruiting brings. AI is only as good as its human operators – empowering your team members to learn and become experts on the software will also eliminate downtime and inefficiencies caused by broken software or lack of knowledge.
Whether or not you believe in the ability of technology to judge the best candidate for the job, it is undeniable that AI recruiting saves time and creates better, more efficient hiring practices.