Image created with Midjourney. Prompt: 2d minimal style illustration of a sea of silhouettes representing the majority, one vibrant, highlighted figure stands out, symbolizing the base-rate neglect bias
We often make judgments based on stereotypes or representative information, overlooking the broader context. This tendency, known as base-rate neglect, can lead to flawed decisions and bias. In the realm of digital software creation, this cognitive bias can significantly impact the design, functionality, and overall user experience of the products we create.
Base-rate neglect is a cognitive bias where people ignore or understate the base rates of particular events when making decisions. Instead, they rely on specific, representative information, even when it's less probable. For instance, if told "A young man was stabbed," many might think of a Russian immigrant rather than a middle-class German, even though there are far more of the latter. Here, the base rate—the larger population of middle-class Germans—is neglected in favor of a less likely but more representative scenario1.
Imagine a medical test for a rare disease that affects 1% of the population. The test is 99% accurate. If you test positive, your first instinct might be to panic. However, considering the base rate, you should remember that it's more likely to be a false positive since the disease is rare.
After a high-profile airplane crash, many people may be reluctant to fly, believing it to be unsafe. This reaction neglects the base rate—the fact that millions of flights occur safely each year, making flying one of the safest modes of transportation.
People often think of successful tech startups as overnight successes. However, this neglects the base rate—most startups fail, and those that succeed often do so after years of hard work and multiple iterations.
In digital software creation, base-rate neglect can manifest in various ways.
Designers may focus on creating visually appealing interfaces without considering the base rate of users who prioritize functionality over aesthetics. For example, an elaborate design might impress a few users but could confuse the majority who prefer simpler, more intuitive interfaces.
When testing new features, developers might pay more attention to the vocal minority's feedback, neglecting the silent majority's preferences. This can result in designing software that doesn't meet the needs of the majority of users.
When launching a new software product, companies might overlook the base rate of potential users in their target market who are comfortable with existing solutions. This can lead to overestimating the demand for the new product and underestimating the resistance to change.