People instinctively prefer simplicity. This preference is evident across countless situations in life, and recent research in cognitive psychology from the University of Waterloo has scientifically verified this intuition. Centered around the question “Why are we satisfied with simple explanations?”, the researchers conducted seven experiments involving 2,820 participants. Consistently, the participants showed a strong preference for simple explanations and efficient action strategies.

The results reveal a fundamental principle embedded in human cognition. A simple explanation is not only easier to understand—it assumes a *trustworthy cause*. In other words, people prefer explanations based on familiar, repeatable causes over rare, complex, or unpredictable ones. This preference stems from the comfort that predictability brings when making decisions and anticipating outcomes.

One of the study’s most striking insights is that the human brain uses similar standards when evaluating both explanations and goal-oriented actions. The simpler the explanation and the more common the cause it contains, the more “reasonable” it appears to people. Similarly, the simpler and more replicable the path to a goal, the more “efficient” it is perceived to be.

This goes beyond mere information processing. It reflects what’s known as *cognitive economy*—our brain’s tendency to conserve mental energy while interpreting, deciding, and acting. Simplicity in explanation conserves cognitive resources; efficiency in action accelerates results. Together, these preferences form part of an evolutionary toolkit that continues to guide our behavior today.

A crucial point from the study is that simplicity alone isn’t enough. What people truly prefer are explanations that are both *simple and reliable*. For example, when explaining a phenomenon, participants trusted familiar, frequently occurring causes over rare or complex ones. This suggests that people don’t just want the briefest explanation—they want one grounded in *predictability and reproducibility*.

The same applies to goal achievement. Rather than using intricate tools or special procedures, participants gravitated toward methods that were general and easy to implement. This preference is deeply connected to the human drive for efficiency—achieving more with fewer resources.

These findings extend far beyond psychology. They offer practical lessons for management, leadership, decision-making, marketing, and education. Leaders, for instance, are more persuasive when they present changes or strategies using intuitive, simple principles rather than complicated frameworks. Simple explanations build trust and activate our innate preference for actionable clarity.

Likewise, when executives define company goals and implementation plans, focusing on a few core metrics rather than complex KPIs tends to increase employee engagement and deliver better outcomes. Simplicity boosts execution, and execution drives results.

So, is a simple explanation always better? Not necessarily. While simplicity is a powerful preference, it can sometimes oversimplify reality and obscure critical variables. Attempting to reduce a complex phenomenon to one or two causes can lead to misinterpretation.

For example, attributing a financial crisis solely to one policy failure, or blaming an organization’s dysfunction on a single leader, may feel satisfying but rarely captures the full truth. Simplicity must be bounded by *explanatory sufficiency*, and anything beyond that belongs in the realm of critical reflection.

This research also holds important implications for artificial intelligence (AI). AI seeks to emulate human cognition, and the preference for simple explanations directly affects how users interact with algorithmic systems. For AI outcomes to be trusted, they must be communicated in a *clear and reliable* way, not as opaque mathematical abstractions.

As demand for Explainable AI (XAI) grows, this research offers crucial insights into how systems should be designed to enhance user trust. AI must provide explanations that are simple—but not misleading. Balancing simplicity with truthfulness is a central design challenge in the age of intelligent systems.

Simplicity is a cornerstone of effective teaching and communication. Educators are more successful when they use analogies and simple concepts instead of jargon-heavy language. Likewise, in public messaging, governments and institutions gain greater understanding and cooperation when they communicate through concise, clear messages.

However, simplicity can also be abused. Politicians or interest groups may distort truth through overly simplistic narratives—“The economy collapsed because of one leader” or “This crisis was caused by outsiders.” These claims may sound intuitive but often lack nuance or accuracy. Simplicity should aid comprehension, not serve as a tool for manipulation.

As confirmed by the University of Waterloo study, humans are wired to prefer simple explanations and efficient strategies. This is both a product of evolutionary adaptation and a habit of modern reasoning. Yet simplicity should be viewed as a *means*, not an *end*. Explanations should be clear without compromising truth; actions should be efficient without losing ethical grounding.

Ultimately, simplicity is the default mode of human thinking. And how consciously and strategically we use that default may determine our intellectual resilience in an age of complexity and information overload.

(Resource - COGNITIVE PSYCHOLOGY, November 2024, Vol. 154, “Doing things efficiently: Testing an 

Account of Why Simple Explanations are Satisfying,” by Claudia G. Sehl, et al.  © Elsevier B.V.  all rights reserve)