What does it really mean for a selection method to be valid?

In organizational psychology, validity is not about popularity, intuition, or professional-looking reports. It is about one thing: predicting future job performance.

In the age of AI-generated CVs, optimized applications, and interview coaching chatbots, predictive validity matters more than ever. This article explores the first principle of the VALID framework and explains why performance—not impressions—should be the starting point of every selection process.

What does it really mean for a selection process to be reliable?

In organizational psychology, reliability is not about good intentions or professional judgment. It is about obtaining stable and consistent results across evaluators, situations, and time. In the age of AI-assisted applications and interview preparation, reliable selection methods have become more important than ever. This article explores the second principle of the VALID framework and explains why consistency is essential for fair and defensible hiring decisions.

What happens when a selection process collects plenty of information but still cannot support a decision?

A selection process becomes logical when it transforms complex assessments into comparable and defensible decisions. In the age of AI, the challenge is no longer collecting more data—it is combining data in a meaningful way. This article explores the third principle of the VALID framework and explains why Selection Plans, scoring models, and percentiles are essential for scientific hiring decisions.

Is recruitment a cost—or an investment?

In organizational psychology, selection is not simply an operational expense. It is a probabilistic investment designed to increase the likelihood of future performance. In the age of AI-enhanced recruitment, the economic consequences of hiring decisions have become more significant than ever. This article explores the fourth principle of the VALID framework and explains why predictive validity, utility analysis, and ROI should be part of every serious hiring strategy.

What happens when a selection process generates information but still cannot support a decision?

A selection process becomes differentiating when it can clearly distinguish between candidates and explain why one candidate is a better fit than another. In the age of AI-enhanced applications and increasingly sophisticated self-presentation, differentiation has become more important than ever. This article explores the final principle of the VALID framework and explains why percentiles, comparison models, and structured decision systems are essential for transparent and defensible hiring decisions.