Roth Staffing’s specialized teams are experts in staffing and recruiting, and many of our customers are currently asking us how they can best understand and utilize artificial intelligence (AI) in their own hiring practices. AI is a growing and complex force that is having a major impact on every industry. We want to make sure that our clients know the options, opportunities and pitfalls of using this powerful and rapidly evolving technology.
Sourcing & Screening Candidates
Perhaps the most well-known and popular uses of AI in recruiting are the applicant tracking systems (ATS) and candidate relationship management (CRM) software systems that can automate many important and time-consuming hiring-related tasks. From attracting candidates and building relationships with them to sourcing and screening for open roles, ATS and CRM systems have changed how recruiting is done.
In addition to finding the right candidates for a role based on the recruiter’s criteria, AI systems can rank candidates and even predict their potential for success. The emerging technology of “predictive analytics” uses data and statistics to predict how well a candidate will do in a given role.
LinkedIn explains that “by analyzing various data points, such as resumes, social media profiles, past job performance, skills, and assessments, recruiters can gain valuable insights into a candidate’s potential fit within an organization.” Predictive analytics can also assess the skills needed for a role and identify any gaps in the candidate pool, which can allow recruiters to adjust job descriptions or develop necessary training.
AI technology can also be used for processes like candidate background checks, reference checks, skills assessments, automated communication with candidates, some interview steps, scheduling and more. With human oversight and the inclusion of critical keywords, AI can also handle the writing (and re-writing) of job postings, a notoriously time-consuming process for any hiring manager. These functions can free up time for recruiters and hiring managers to focus on the “people” side of their roles.
While there are many benefits to using these systems, recruiters must weigh the expense of the services and the multiple options from which to choose. Every system has a different candidate pool, varying greatly by size. By committing to one system, you could be missing out on another audience.
Fairness & Transparency with AI
One of the main benefits of using AI in recruiting can also be one of its weaknesses. When software screens candidates’ resumes, you get a data-driven look at the pool and a presumably objective look at an individual’s qualifications for the open role. Even the most fair-minded human comes to the hiring process with inherent biases about what skills they think are most important or many other factors. When you leave that to software to determine, however, the result should be as fair as possible to all applicants.
This objectivity is a plus for organizations looking to diversify, as the focus on diversity, equity and inclusion (DEI) initiatives continues to be a major priority for companies as well as job seekers considering their next career move.
However, as “objective” as a machine can be, it can also learn bias based on what information it has been fed. If AI is trained to be discriminatory in any way – even if unintentionally – the algorithm will perpetuate that bias.
In one well-publicized case, a dominant online retailer built an AI system for recruiting, but it showed bias against women. Developers found out that it discriminated because the system had “learned” what to look for by using men’s resumes, creating an algorithm that threw out resumes that didn’t look similar to what it was trained to favor. The company stopped the program, but this example and many others demonstrate the importance of careful, ongoing analysis and updating of AI systems to ensure fairness.
Another pitfall of using AI in recruiting is the lack of transparency and oversight. LinkedIn notes, “The opaque nature of many AI algorithms further fuels ethical concerns. Recruiters and candidates often have no understanding of how an algorithm arrives at its decisions, creating a lack of transparency and accountability. This secrecy raises questions about fairness and makes it hard to identify and address potential biases.”
Candidates have no way of knowing the criteria for which they’re being selected (or rejected). This may further frustrate a candidate who already must customize their resume or application by guessing which keywords to include so that they make it to the next stage of the hiring process. All of us have heard stories of extremely qualified candidates not making it past the initial screen, likely due to a too-restrictive algorithm.
The Human Touch Still Matters
As intelligent as machines have become, they’re not infallible. Even the most refined algorithms can result in a poor hiring decision, which is why hiring should never be a 100-percent automated process. Recruiters and hiring managers must make decisions about the best systems for their unique hiring needs, and then manage those systems carefully to ensure fairness.
Perhaps most importantly, software cannot screen to determine if a candidate is a good fit for your organization’s culture. Only face-to-face meetings and open dialogue can help you understand a candidate’s goals and values. AI is also not ideal for screening for soft skills, like communication, empathy, leadership, critical thinking and teamwork. As leaders’ appreciation and demand for those intangible qualities grows, it will continue to be vital for a human connection between hiring manager and candidate.
Roth Staffing and its specialized business lines understand today’s hiring market can be challenging. We’re here to help with our online resources as well as in-person consultations to discuss your unique challenges. Contact your nearest location for more information.
