HireVue announces acquisition of Modern Hire

Learn More

Candidates: Are you interviewing and need support?

Bias in Hiring: Practical Steps to Reduce Bias (Part Four of Four)

In a perfect world, bias of any type wouldn’t enter the hiring process. We’re not there yet, but recent advances in artificial intelligence have given us a significant boost. AI can identify patterns in data and control for bias at levels much higher than ever before. With science-based selection tools, hiring decision-makers can focus on data when evaluating candidates instead of “gut” feelings.

AI alone, however, is not a magic pill. AI must be used in an ethical context, rooted in research, with continuously updated algorithms. Data drives AI so accurate data – and copious amounts of it – creates a solid foundation for every process that depends on AI. For example, Modern Hire’s predictive analytics are built on over 500 million data points, tens of millions of candidate interactions, and almost two decades of rigorous, data-driven research and practice.

A comprehensive, A-Z hiring platform

Too often, HR hiring software is a “bolt-on,” a stand-alone program added to a suite of products. AI used in this context is dangerous. Imagine if AI was only used in screening resumes but not in assessments or interviews. You’ve controlled for bias in one area, but it can quickly pop up in another. To ensure fairness and reduce bias as much as possible, a robust hiring platform must cover every step in the hiring process: screening, assessment, interviewing, and evaluation. A comprehensive solution reduces bias at every stage and provides more robust legal protection for the organization.

Trust and use the data for better selection

Everyone trusts their feelings and is sure they’re unbiased. But that’s rarely the case. So, HR needs to educate hiring teams about the importance of data in reducing bias. Even more, they need to convince hiring teams that this data will enable them to make more decisive candidate decisions with better outcomes.

With an end-to-end hiring platform that incorporates scientifically validated tools at every step, hiring teams can have reliable candidate data that moves the process faster and more confidently informs decisions.

The “Four Es”

HR hiring teams face the four most common challenges of balancing efficiency, effectiveness, ethics, and engagement, or the “Four Es.” Historically, there have always been tradeoffs. If you want more efficiency – faster processing of early candidate data, for example –you might lose some effectiveness, that is, capturing the best candidates. But it doesn’t have to be this way. HR practitioners and hiring decision-makers need an all-in-one technology that is efficient, effective, ethical, and engaging for everyone. What would this look like?

Efficient. AI-enabled text interviewing, for example, helps recruiters screen at high volume, sifting through many applications and bringing the best to the top. Pre-hire assessments enable recruiters to sort candidates based on their scores instantly, focus their efforts on best-fit candidates and advance them through the process quickly. Candidate self-scheduling tools, on-demand interviews, and automated workflows reduce manual and administrative tasks, freeing time to focus on quickly getting the best candidates on board.

Effective. A consistent and standardized process increases the likelihood that best-fit candidates are chosen by recruiters and hiring managers. This means that all hiring activities must be based on criteria directly proven to predict success on the job. For example,

  • A quick and engaging text-based assessment designed to predict a candidate’s likelihood to stay on the job.
  • An interview question library that provides questions that target specific job-related behaviors and situations, filtered by competency, job family, and job level.
  • AI capabilities that allow candidate interview responses to be machine scored as accurately or more accurately than by expert human raters.
  • A Virtual Job Tryout that gives candidates a real feel for the job, resulting in better fit, job performance and retention.

Ethical. Fair and transparent hiring software is more likely to identify the best candidates. For instance, consistent interview questions based on the factors known to predict job success, like competencies, skills, and experience, ensure a fair process regardless of who conducts the interview. Science-backed AI tools, like automated interview scoring, ensure an evaluation process that only focuses on job-relevant content. Ethical hiring technology must also be transparent. This means informing candidates that AI is being used, how it works and given the choice to opt-out. It also means showing HCM leaders how the software works, the research behind it ,and the ongoing work to keep it true to its purpose.

Engaging. In the past few years, creating a positive candidate experience has gotten a lot of attention. Especially in today’s competitive labor market, job seekers asses the employer from the get-go. They want a simple, convenient process that respects their time, like mobile applications that handle screening, assessing, interviewing, and job simulations. Your hiring technology should reflect your brand, culture, and values. Ideally, candidates will become a fan of your brand even if they don’t get a job offer.

At Modern Hire, we combine the predictive power of assessment, interview technology, advanced analytics, and AI into an all-in-one, enterprise-ready solution. In the process, you as an employer receive a whole-person view of your candidates, with data that better reflects the complex nature of on-the-job performance. The result is a fairer, more efficient hiring process that provides a better candidate experience and better outcomes.