The Cognitive Challenge of Cumulative Information

• Applicant: Professor Dr. Hans Alves
• Subject Area: Social Psychology, Industrial and Organisational Psychology
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 538466518

People are confronted with an ever-growing amount of information. Digitalization and the rise of the internet provide people access to countless observations and data points. Processing these large amounts of data is a challenge for the human mind, which runs on limited capacity. An effective way to reduce this mental load is to provide people with data aggregates such as averages, totals, or rankings. These relief people from having to integrate many individual observations into summary statistics, which can be a source of biases. Paradoxically, recent research has shown that providing people with multiple aggregated data points over time can itself be a major source for biased impressions, beliefs, judgments, and evaluations. This phenomenon was termed the "Cumulative Redundancy Bias" (CRB; Alves & Mata, 2019). Cumulative observations such as running totals, running averages, or running rankings are highly redundant because the most recent observation entails all previous observations. Following the law of large numbers, perceivers should update their impressions, beliefs, and judgments by replacement, meaning that they should ignore previous cumulative observations and only rely on the most recent one. Recently, we have gathered extensive empirical evidence showing that perceivers systematically fail to ignore previous, redundant cumulative observations. When perceivers observe the performances of two competitors over time, their impressions and future expectations of the competitors’ qualities do not only depend on the result but also on previous standings. The CRB thereby favors leading over trailing competitors. In previous research, my colleagues and I have successfully established the CRB as a robust, and logically unwarranted bias. The main objectives of the present research proposal are to identify the mechanisms underlying the CRB and to substantively extend ist scope. A first work package empirically tests several different information integration rules that may underlie the CRB. Building on a pilot study with promising results, a second work package extends the CRB to one-agent scenarios and investigates emotional and behavioral consequence of the CRB. Addressing possible validity inferences caused by the CRB, a third work package investigates whether the CRB contributes to fraud suspicion in elections and whether it influences scientists’ beliefs in competing hypotheses. Building on further promising pilot data, a fourth working package test the potential real-life impact of the CRB on news reporting following sports competitions. Taken together, the proposed research program promises a better understanding of a general, robust, and puzzling judgment bias and it promises to uncover novel far-reaching implications related to gambling behavior, emotional reactions to gains and losses, news reporting, election fraud suspicion, and scientists’ beliefs in hypotheses.

• DFG Programme: Research Grants
• International Connection: Portugal
• Cooperation Partner: Dr. André Mata