Decision making research examines how people choose between options, and why choices often deviate from perfect rationality. A key finding is that people rely on heuristics, or mental shortcuts, that are efficient but bias-prone. For example, the availability heuristic leads us to judge the probability of events by how easily examples come to mind, which can distort risk perception. The representativeness heuristic makes us focus on similarity to a stereotype rather than actual base rates, producing systematic errors in probabilistic reasoning.

Prospect theory shows that people evaluate outcomes relative to a reference point, not in absolute terms, and are typically loss averse: losses feel more painful than equivalent gains feel pleasant. This leads to risk averse behavior when facing potential gains and risk seeking behavior when trying to avoid losses. Framing effects demonstrate that logically equivalent descriptions can push people toward different choices, simply by emphasizing gains or losses.

Dual process models propose two interacting systems. One is fast, automatic, intuitive and often emotionally driven. The other is slower, analytical and resource demanding. Everyday decisions often default to the fast system, while the slow system is recruited when stakes are high, conflicts arise, or we deliberately reflect.

Context and emotion strongly shape decisions. Time pressure, fatigue and stress push people toward simpler, more heuristic based choices. Social influences and norms also guide what options seem acceptable. Research further explores how training, feedback and decision aids can partially counter biases, helping people approach more consistent and goal aligned decisions in domains such as health, finance and public policy.