In employee selection, assessments refer to any systematic method of obtaining information about applicants to draw inferences about their traits. Assessment types used for employment decisions include proficiency tests of knowledge/skill/abilities, work samples, personality inventories, etc.
The most common method, however, is the job interview. The prime purpose of job interviews is to predict whether or not a candidate will be a good fit and a strong performer.
However, the increasing democratization of information over the past couple of decades has presented new challenges to the sustainable and valid use of these tools.
Extensive research also shows that well-designed and professionally-validated assessments, such as Talent Select AI, help safeguard us from our own biases by providing a scientific, consistent, and neutral lens into candidates’ potential fit with the role.
Most hiring practices that include an assessment require candidates to proceed through multiple steps before receiving a job offer. The assessment is one step, while the interview is another.
Using Talent Select AI’s innovative approach, companies can now combine interviews and assessments into a single, concise step, saving time, resources, and cost and streamlining the candidate experience.
In our latest White Paper, The Future of Hiring: Understanding Candidate Assessments, Marc Fogel, Director of Product, IO Psychology, discusses the fundamentals of hiring assessments – including the problems with many traditional assessments – and breaks down Talent Select AI’s validated patent-pending approach to providing more complete candidate assessments, right from your standard job interview.
"Talent Select AI is committed to rigorous ongoing validation of our tools so we can continue to ensure accuracy, reliability, validity, and legal defensibility of our assessment. ” Fogel explains. "With the recent executive order on AI use and pending AI legislation on the books in more than 15 states, it's vital that organizations prioritize transparency and validity when considering any new AI-enabled selection tool. "
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