AI is all the rage, but is it dangerous?

AI is all the rage, but is it dangerous?

AI on the digital map

Artificial Intelligence continues to be a major trend in HR as companies look to improve hiring decisions and efficiency. As a computer scientist and expert on hiring research, I can attest that there are definitely components of hiring that can be improved with AI. One example is using algorithms to automatically remove identifying information from resumes to make identity-blind resume review more efficient. We can also use AI to help companies write better and more inclusive job descriptions that attract a broader pool of qualified applicants. A company concerned with employee turnover could use AI to identify employees who may be likely to leave based on variables like how many managers they’ve had, pay equity, and length of tenure. These are all exciting applications of AI that could make a real difference to a company’s hiring success.

AI and Recruiting

The main place people seem to be interested in using AI in recruiting is in reducing the number of resumes recruiters have to review to get to the best candidate. This makes perfect sense: given how easy it is to apply to a job with one-click these days, recruiters are understandably overwhelmed with the number of resumes they receive.

Unfortunately, there is a huge risk that using AI in the recruiting process is going to increase bias and not reduce it. Why do I sound so pessimistic? Because AI is completely dependent on the training set that is used to generate its predictive results. We’ve already seen how this can go horribly wrong in trying to identify images and create Twitter posts. When it comes to hiring, a critically important function for companies, AI can perpetuate biased patterns and teams that are very similar to existing ones.

Here’s an example where AI does not serve a company well. Let’s say a corporate hiring manager always looks for candidates who went to Ivy League schools. When an algorithm looks for patterns of the employees at the company, it will notice that there are certain schools that are more common among current employees, and it will seek candidates from those schools. However, research has shown that where someone went to school is not predictive of how well they will perform in a job. So, the algorithm has now found a “signal” in the data that is not predictive of how well a potential candidate will actually do the job. In this case, AI is simply feeding recruiters “more of the same,” which may not be what your company needs to achieve future goals.

Using AI in this way won’t be help organizations predict what they need to achieve future goals. AI is essentially “driving in the rearview mirror” – it is based on what has been done in the past. That’s why AI can’t replace recruiters, who have specific knowledge on the best types of people to hire to meet certain skillsets that will move a company forward.

How to spot potential bias in AI

The possibility of bias in AI training sets won’t occur to many algorithms designers, so it is up to the organizations that are deploying these algorithms to ask the right questions about what testing has been done to ensure bias was not trained into the algorithm itself. For example, if you’re considering video software that analyzes nonverbal communication to predict candidate quality or a pre-assessment that claims to predict job performance, ask whether there were observed group differences in the training data. If they can’t tell you, think twice about using it.

You’re still smarter than AI

Use AI to augment your hiring wisely. No amount of AI can replace following best practices in hiring, like identifying key skills and values before sourcing candidates and using structured interviewing. Some AI can help improve these best practices and get you closer to your goals, faster. Just make sure you have your eyes open for potential biases along the way.

Advertisements
Quality Over Quantity: It’s Time to Hire Better | Featured Image

Quality Over Quantity: It’s Time to Hire Better

Quality Over Quantity: It’s Time to Hire Better | Main Image

These days, there is rarely a technology that can’t be mimicked, a service that can’t be purchased, or a system that isn’t for rent. Big organizations mostly use essentially the same services from Microsoft Office to ATS databases. With so much homogeny, what separates successful companies from the rest? The people are the secret sauce. Even with proprietary software or patent-protected techniques, no company can truly thrive without one extremely important element: effective and creative teams.

Despite all our technological advancements, it’s humans who truly make the difference at an organization. In our 21s t century reality – where technology is ubiquitous – talent acquisition professionals become one of the most important departments at a company, because they are responsible for the most important competitive asset: new hires.

Unfortunately, we don’t always realize how important our talent acquisition processes are. In fact, many companies remain focused on the wrong metrics, concentrating on hiring quickly, rather than zeroing in on finding the right candidate.

Some organizations are already making the shift. Where most recruiters are encouraged to fill roles as quickly as possible, forward-thinking organizations are focused on quality, tasking their recruiters to fill the roles with the best possible candidate.

What caused this shift? That’s easy – organizations are realizing that emphasizing speed in hiring sacrifices quality. And filling a role quickly with the wrong person is extremely costly to an organization.

For the organizations not yet making the shift and slower to realize they are doing it wrong, it’s not all bad news. The fact is, best practices around making hiring decisions have been understood by academics for years. And they are not that difficult to implement. There are new and exciting talent-acquisition tools that are enabling companies to reform their practices and overhaul processes to create something much better.

With artificial intelligence (AI) capabilities, technology can play an important role from the get go . For example, it can help someone write a better job description. This first step in the hiring process would then invite a diverse pool of candidates with capabilities that match companies’ needs. Cloud and mobile computing solutions facilitate better communication between recruiters and hiring managers. Nudge technology and access to data allows decision-makers to move away from hiring based purely on gut-decisions and shift to data-driven choices.

Research has identified five hiring best practices that span the talent acquisition process – from writing targeted job descriptions that invite the best candidates to blind resume reviews to conducting structured interviews. These best practices make hiring more effective and yield stronger teams, happier employees, and improve the candidate experience, which reflects on the company at every step. The talent acquisition industry has technology that can facilitate all of these strategies and transform hiring systems to be both more effective and more equitable. What we need now is a change of mindset.

As an industry, let’s forget the incomplete idea that talent acquisition is only about filling an open position. It’s about strategically finding creative and effective team members that fit the company culture and will drive the business forward. As new markets emerge, and old sectors are rapidly transformed, it’s the employees, the human element, who contribute to a company’s success and it’s competitive differentiation.

Instead of pressuring talent acquisition professionals to be faster, or to collect more resumes, true improvement will come from creating processes that prioritize hiring best practices and finding the right hire. This change in focus from the fast hire to the right hire will succeed only if it is organization-wide and reinforced at every level, from senior leadership team and executive suite to the hiring manager and recruiters.

The data is there: the hiring process is broken. We have the tools and the strategies to change. It’s time to start changing our priorities and focusing on the metrics that really matter. It’s time to hire better.

About the Author:

Laura Mather, Founder and CEO, Talent Sonar

Laura Mather, CEO and Founder of Talent Sonar, is an expert on hiring, AI, and the future of work. Her innovative technology, Talent Sonar, is the only comprehensive hiring platform to improve hiring at every step from incorporating values into the hiring process to conducting blind resume review and structured interviewing. She was honored as one of Fast Company’s Most Creative People in Business and as one of Fortune’s Most Powerful Women Entrepreneurs. She is a featured speaker at Fortune’s Most Powerful Women Next Generation Summit, HR West, and Ad Week, among others.


If you want to share this article the reference to Laura Mather and The HR Tech Weekly® is obligatory.

Leveraging the Best of AI for Outstanding Hiring Results

Leveraging the Best of AI for Outstanding Hiring Results

Written by Laura Mather, Founder and CEO at Unitive, Inc. (Talent Sonar).

Laura Mather, Founder and CEO at Unitive, Inc. (Talent Sonar)

Every hiring team is asking the same question: is this candidate the right person for the job? This should be a fairly simple question to answer, but after the resume review and the interview are over, it’s become pretty clear that humans don’t always have the best intuition. Although we sometimes do get it right, sometimes just isn’t enough. Bad hires are hugely expensive for any organization of any size. Tony Hsieh, the CEO Zappos has estimated that bad hires cost the company “well over $1 million.” The US Department of Labor has estimated that a bad hire can cost a company at least 30 percent of that employee’s first-year earnings.

While many companies are feeling pressure to scale and expand quickly, no company can afford to absorb these losses, especially when you factor in the time and energy your current employees will expend hiring and training them.

Ineffective hiring techniques hurt your chances of finding great hires in numerous ways. Not only will you miss great applicants, or let qualified candidates get lost in the shuffle, bad hiring techniques can also translate into bad candidate experiences, meaning that you may be losing great candidates to competitors just because your hiring process was tedious or confusing.

LinkedIn Talent Solutions found that a shocking 83 percent of applicants said a negative interview experience changed their opinion about a role or a company they had once thought of positively. Not only can a bad experience influence a candidate but a good experience can have an even stronger reaction: 87 percent of respondents to LinkedIn said that a good interview experience improved their opinion of a company they had previously doubted.

When an unstructured and unreliable hiring process leaves candidates feeling confused, frustrated, or even disappointed, this can damage both our hiring outcomes and your company’s reputation. One study found that 72 percent of candidates who had a poor hiring experience shared that experience publicly on sites like Glassdoor.

So how can you leverage the best in people analytics to create a hiring system that consistently yields great hires while also maintaining a positive candidate experience? The answer lies in the careful calibration of human intuition and machine learning. While our “gut instincts” are often wrong, good HR teams are able to combine those human reactions with great data and software that guide hiring decisions but don’t dictate them.

For companies of any size, in any sector, the key to consistently successful hiring isn’t automation alone: it’s structure throughout the process and alignment at every level of the team from executives to managers and recruiters. Software can help combine these crucial components, ensuring teams are guided by the same principles and priorities so that candidates have uniform, positive experiences. Software can also stitch machine learning and AI tools into every step so they become an intuitive part of the process, instead of a cumbersome addition.

Although AI has mostly been used during resume review, this technology can and should be expanded to rest of the process, guiding how managers draft job descriptions so that they are accurate, communicate the most important aspects of the position, and will appeal to a wide range of candidates, ensuring your applicants represent the full pool of potential talent that can succeed in this role.

AI can also help continually guide HR teams back to the qualities and capacities that matter most to this position. That can mean helping interviewers create questions that are relevant, behavior-based, and consistent with other interviewers so that every candidate has a consistent experience. It can also mean scoring candidates so that HR teams can see, without a doubt, which applicants are qualified and why.

Whether you are a Fortune 100 powerhouse or a nimble and growing startup, whether you are looking for a C-Suite executive or a daring creative, your needs remain the same: find great candidates with proven abilities to succeed and convince them to work for you and not your competitor. While the objectives are clear, the task is herculean. With the structure, support, and guidance of AI hiring technologies, HR professionals are finally fully empowered to create meaningful interviews, build positive relationships with candidates, and make great decisions and find the perfect hire every time.


If you want to share this article the reference to Laura Mather and The HR Tech Weekly® is obligatory.