Cognitive models of political behavior and political decision making have been a staple of research in political science for decades. Recent advances in cognitive psychology and behavioral decision making underscore the utility of models that incorporate memory dynamics for understanding a wide range of political behaviors at the individual level. Four memory systems are relevant; sensory memory, short-term memory, working memory, and long-term memory. Information moves from sensory memory to short-term memory stores, a subset of which is then acted upon by working memory. Working memory manipulates its contents through processes such as reasoning, comprehension, attention, integration, and retrieval of supplementary information from long-term memory. Working memory ultimately holds and processes the thoughts and feelings that are salient to an individual at a given point in time. Memory models of decision making elaborate what cognitions and emotions are likely to enter working memory and how those cognitions and emotions are combined and integrated when making a behavioral decision.
Citizens are continuously inundated with political information. How do citizens process that information for use in decision-making? Political psychologists have generally thought of information processing as proceeding through a series of stages: (1) exposure and attention; (2) comprehension; (3) encoding, interpretation, and elaboration; (4) organization and storage in memory; and (5) retrieval. This processing of information relies heavily on two key structures: working memory and long-term memory. Working memory actively processes incoming information whereas long-term memory is the storage structure of the brain. The most widely accepted organizational scheme for long-term memory is the associative network model. In this model, information stored in long-term memory is organized as a series of connected nodes. Each node in the network represents a concept with links connecting the various concepts. The links between nodes represent beliefs about the connection between concepts. These links facilitate retrieval of information through a process known as spreading activation. Spreading activation moves information from long-term memory to working memory. When cued nodes are retrieved from memory, they activate linked nodes thereby weakly activating further nodes and so forth. Repeatedly activated nodes are the most likely to be retrieved from long-term memory for use in political decision-making. The concept of an associative network model of memory has informed a variety of research avenues, but several areas of inquiry remain underdeveloped. Specifically, many researchers rely on an associative network model of memory without questioning the assumptions and implications of the model. Doing so might further inform our understanding of information processing in the political arena. Further, voters are continuously flooded with political and non-political information; thus, exploring the role that the larger information environment can play in information processing is likely to be a fruitful path for future inquiry. Finally, little attention has been devoted to the various ways a digital information environment alters the way citizens process political information. In particular, the instantaneous and social nature of digital information may short-circuit information processing.
Rüdiger F. Pohl and Edgar Erdfelder
Hindsight bias describes the tendency of persons—after the outcome of an event is known—to overestimate their foresight. For example, following a political election, persons tend to retrospectively adjust their predictions to the actual outcome. These judgment distortions are very robust and have been observed in a variety of domains and tasks. About 50 years of research on hindsight bias have meanwhile brought a wealth of findings and insights. Core research questions are (1) how to explain hindsight bias in terms of underlying processes, (2) whether there are individual differences in susceptibility, (3) how the bias possibly impedes decision-making in applied contexts, such as political decision-making, and (4) how possibly to overcome it. Theoretical approaches suggest that there are distinct components of hindsight bias, and that several, mainly cognitive, mechanisms are responsible for them. Using stochastic models of hindsight bias allows us to estimate the relative proportions of these mechanisms. Depending on the task, motivational factors may also exert their influence. In addition, the strength of hindsight bias appears to be related to some personality traits and also to age. For example, some authors found that hindsight bias tends to increase with the tendency toward favorable self-presentation and to decrease with intelligence. Moreover, lifespan studies have shown that children and older adults show larger hindsight bias than young adults. Hindsight bias has been found in political decision-making (as well as in other applied domains). Surprisingly, attempts to overcome hindsight bias have mainly failed, whereas only a few debiasing techniques show promising results. In sum, one important conclusion is to be continuously aware of the potentially distorting influence of outcome knowledge on the evaluation of our own (or other’s) prior knowledge state.