Gambler’s Fallacy Definition
Gambler’s Fallacy, known as the Monte Carlo fallacy as well, is the wrong idea that random events in the past have any effect on future outcomes. A very common explanation for this line of thinking is that people tend to think that when something happens so many times, the opposite of it is about to happen.
The idea has been closely linked to gambling, for instance, believing that after a roulette wheel has landed on red several times black must be the next winner. Nevertheless, it is a misconception that applies to a large extent to the decision-making process and the perception of randomness as well.
Gambler’s Fallacy in software and UX
The gambler’s fallacy can be seen in software development and UX design when users or teams take prior patterns as the base for their decision instead of real chances. The following are some of the instances where this has happened:
- Users are anticipating the provision of certain content based on the past interactions
- Teams think that bug patterns would “balance out” without drawing out adequate testing
- Predicting user behavior through anecdotal rather than statistical evidence
By acknowledging the gambler’s fallacy, designers, developers, and product managers are able to shun biased convictions, depend on data-driven insights, and the like. Moreover, they will also be able to determine better the interface design, testing strategies, and user experiences.