Impact Bias
The tendency to overestimate the duration or intensity of the emotional impact of future events.
The tendency to overestimate the duration or intensity of the emotional impact of future events.
The practice of using data analytics and metrics to make informed decisions, focusing on measurable outcomes and efficiency rather than intuition or traditional methods.
The practice of organizing the context in which people make decisions to influence the outcomes, often used to nudge users towards certain behaviors.
A cognitive bias where individuals give stronger weight to payoffs that are closer to the present time compared to those in the future.
The use of data, algorithms, and machine learning to recommend actions that can achieve desired outcomes.
A cognitive bias where individuals underestimate the time, costs, and risks of future actions while overestimating the benefits.
An organization that applies behavioral science to policy and practice to improve public services and outcomes.
A phenomenon where the success or failure of a design or business outcome is influenced by external factors beyond the control of the decision-makers, akin to serendipity.
An inference method used in AI and expert systems where reasoning starts from the goal and works backward to determine the necessary conditions.