Thirty years ago, psychometric tests were primarily a pen-and-paper exercise. Then personal computers shoved them aside. Now we’re seeing a new crop of emerging technologies changing the way we think about assessment, particularly on mobile devices.
A recent poll of global talent leaders by Aon’s Assessment Solutions found that employers recognize that AI offers major opportunities to improve the hiring process. When asked about the biggest areas of potential for AI, for example, 46% cited providing better information for decision making, 24% cited speeding up the hiring process, 19% cited mitigating human bias and 10% cited lowering the cost of assessment and selection.
Identifying and Developing Talent Through AI-Driven Assessment
By using predictive analytics, companies can also assess the expected impact of technology on the current roles within an organization.
Assessments that use AI and predictive analytics can help you rapidly identify high-potential team members and develop their leadership skills. Incorporating AI into assessments forces employers to specify what high performance looks like and to use those specifications to identify potential high performers.
By using predictive analytics, companies can also assess the expected impact of technology on the current roles within an organization. With sufficient runway, employees whose jobs will be automated can be trained to do new, higher-impact jobs and become an internal talent pool.
These shifts might cause panic for many people, but at Aon we view this differently. We’re seeing the beginnings of a fundamental shift in the way humans create value at work, and it’s one in which the people still matter more than the technology. Done well, AI allows talent professionals to pull the right data at the right time, empowering them to focus on the human side of their jobs. Furthermore, AI enhances the work of human employees by identifying and developing top performers within an organization.
Mitigating Human Bias
AI algorithms and predictive analytics can give companies the objectivity they need to recruit better, more diverse talent.
Human bias in hiring is difficult to eliminate. Employees can go through rigorous training, but humans will still bring bias and inconsistencies into their decisions. By looking for a narrow list of traits in candidates, such as attending certain universities or past employment at particular firms, recruiters often base their decisions on biases and perceptions of fit. But when you use AI in the interview process, you can remove those biases and extraneous factors that occur in an interview setting.
For employers, the main advantage of using AI to mitigate human bias in hiring decisions is that AI algorithms can be trained to identify personality- or competency-based constructs with very little bias. Those constructs can then be implemented in a consistent fashion across all candidates. Individual interviewers would be unable to apply a personality- or competency-based construct across all candidates with the same consistency.
By using machine intelligence to compare people’s profiles and behavior competencies with job specifications and organizational demands, businesses can consider a much bigger pool of talent, reduce bias and make more objective hiring decisions.
Lowering the Cost of Assessment and Selection
Talent assessment typically requires a huge investment of human capital to get right. Sorting through resumes, conducting and rating an interview, and making hiring decisions all take time. But employers can use AI to reduce the human capital needed, such as offering asynchronous interviews where the review and rating of candidates’ responses can be performed by machines, creating process efficiencies and freeing up time for recruiters to spend on other tasks.
All of these efficiencies and reduced human capital needs lower the cost of assessment and improve hiring outcomes. In addition, unstructured recruiter screenings early in the process generally don’t do an effective job of identifying top candidates. Moving these early screenings to AI improves the efficiency of the process, lowers costs and leads to better hiring outcomes.
However, there are some organizations where using AI in hiring may not be appropriate, even given the cost savings. For example, for industries where candidates may not be very tech-savvy, it may be difficult to create a candidate-centric experience with AI. Doing an internal check of your organization to assess whether AI makes sense is a helpful step to ensure you will benefit from any cost savings.
Making AI Assessments That Work for People
Creating a mobile-first design is crucial. AI assessments should be consistent and accessible. Since smartphones have become central to our lifestyles, mobile delivery has become a must-have for talent assessments as well, particularly in high-volume recruitment situations. They are a more inclusive alternative to assessments that can only be taken on a laptop or computer.
AI is a massive boon to talent assessment, but it has to be designed for people. AI works for an organization and its employees, not to replace but to augment the human workforce.
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