Cognitive fallacies are examples of breakdowns in human reasoning in which observers make irrational decisions as evaluated by Bayesian probability calculus. These examples were used for arguing that human reasoning does not operate by the rules of probabilistic computation, in contrast with the surging trend of studies demonstrating that at the level of perceptual decisions, human behavior can be described well by probabilistic models. While multiple studies pointed out flaws in the investigations of cognitive fallacies, a comprehensive and quantitative treatment of the topic is missing. We provide such a treatment by placing perceptual decision making into a new framework and linking it to the problem of the “Base-rate fallacy” (BRF), one of the most celebrated cognitive fallacies. In BRF, individuals participating in vignette studies apparently do not consider the base-rate probabilities of events (priors) when making judgmental decisions. We created a standard 2-AFC perceptual decision making paradigm (N=23) where observers decided which of two shapes embedded in noise was presented in the trial, added one moment in the trial sequence (change point, CP) where significant change occurred to the conditions of the trials and measured behavior in trials well after the CP. We uncovered that humans’ decision making under such conditions shows a far more complex but still probabilistic behavior than reported before. Generalizing this process, we found that keeping the process identical except for changing higher-level noise characteristics of the setup at the CP, humans flip between interpretations of the input relying vs. not relying on assumed differences in the base rates, perfectly mimicking the BRF. In conclusion, instead of being evidence for the lack of probabilistic treatment of the input, cognitive fallacies might be indicators of the same internal model based on probabilistic computations seamlessly transitioning into a particular unconscious interpretation of the current situation.