The Iceberg Model is a systems thinking tool that helps uncover the root causes of problems by looking beyond immediate, visible events. It uses the metaphor of an iceberg to illustrate that events (the tip) are driven by deeper layers that are hidden below the surface.
The Swiss Cheese Model helps explain why accidents happen, often despite all our best intentions. It occurs when multiple small flaws line up perfectly to create a large failure. What appears to be a sudden disaster is usually the result of many small imperfections quietly lining up.
The AI Oracle Effect occurs when teams treat AI-generated output as inherently correct, authoritative, or strategically sound. AI stops being a tool and starts being treated like prophecy. Instead of questioning, validating, or contextualizing the output, the team begins deferring to it. Research becomes a prompt. Recommendations become decisions. The system becomes the oracle. And the room gets surprisingly quiet.
The Cobra Effect describes situations where the metric improves but the experience does not. Nascent product teams often craft incentives with the noblest of intentions: faster growth, happier users, quarterly bonuses; yet sometimes the universe responds not with improvement but with a sharp increase in the very problem they hoped to solve.
Story by Michael Gaigg, Group UI Engineer Manager & UX/UI Tech Center Lead at Esri I recall working on a rather complex, spatially-driven enterprise app, a multi-million dollar engagement. Throughout…
Hick’s Law describes how the time it takes a user to decide increases with the number (and complexity) of choices presented. In UX, it’s a reminder that cluttered interfaces and excessive options slow users down and create cognitive overload.
Recency bias is the tendency for people to weigh the most recent information or experience more heavily than earlier ones, sometimes even disproportionately. In UX, it means users’ judgments and memories of your product are often dominated by what happened last, not by the full journey.
Primacy bias describes how people tend to remember and be influenced more by the first items in a sequence than by those that come later. In UX, it shows up when users disproportionately notice, choose, or recall the first option presented to them, sometimes regardless of whether it’s the best.
Anchoring bias happens when people rely too heavily on the first piece of information they see, the “anchor”, when making decisions. In UX, it shows up when users’ perceptions, expectations, or actions are influenced by an initial number, label, or example, even if it’s arbitrary or irrelevant.
Confirmation bias is the tendency to favor information that confirms what we already believe, while ignoring or discounting evidence that challenges our assumptions. In UX, it shows up when teams interpret user feedback, analytics, or test results through the lens of their preconceived ideas, leading to poor decisions and missed opportunities.