Acceleration neglect in trend extrapolations

Abstract

Many decisions rely on intuitive predictions based on time series data showing a trend. For instance, the current upward trend in global temperatures might lead to specific predictions about the extent to which global temperatures will rise in the future, and these predictions might be used to inform judgments about the urgency with which climate change must be addressed. However, those predictions often need to be revised to incorporate the effects of unexpected events that might accelerate a trend (i.e., increase its rate of change), such as an unanticipated increase in CO₂ emissions, or decelerate a trend (i.e., decrease its rate of change), such as an unanticipated reduction in CO₂ emissions. In this work, we uncover a new cognitive bias by which people neglect how much a trend can accelerate (vs. decelerate) due to unexpected events. We explain this bias in terms of momentum theory and a naive understanding of physics. These findings have important implications for businesses and policymakers seeking to communicate information about topics such as climate change, stock market prices, or disease prevention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).