Collectively jumping to conclusions: Social information amplifies the tendency to gather insufficient data.

Abstract

False beliefs can spread within societies even when they are costly and when individuals share access to the same objective reality. Research on the cultural evolution of misbeliefs has demonstrated that a social context can explain what people think, but not whether it also explains how people think. We shift the focus from the diffusion of false beliefs to the diffusion of suboptimal belief-formation strategies, and identify a novel mechanism whereby misbeliefs arise and spread. We show that, when individual decision-makers have access to the datagathering behaviour of others, the tendency to make decisions on the basis of insufficient evidence is amplified, increasing the rate of incorrect, costly decisions. We argue that this mechanism fills a gap in current explanations of problematic, widespread misbeliefs such as climate change denial.

‘So Help Me God’? Does oath swearing in courtroom scenarios impact trial outcomes?

“…On the one hand, juries may evince “wisdom” (Galton, 1907; Surowiecki, 2005), such that the collective context nullifies individual biases. On the other hand, it could be that the collective jury context actually amplifies individual biases (Lynch & Haney, 2009; Sulik et al, 2021). For the sake of argument, we assume that deliberation has no systematic effect, and we treat trial verdicts as rendered by single jurors rather than by juries of twelve.…”

A systematic review of empirical studies on advice-based decisions in behavioral and organizational research.

“…Last, more research is needed on how advice is integrated with information from other sources and on how advice availability affects the solicitation and utilization of information from other sources. The few studies in our sample that speak to these important questions suggest that decision makers may not process advice exactly like they process information from other sources (e.g., ignoring redundancies between advice and other types of information, Collins et al, 2011 ‡; or accounting for their advisor's intentions in interpreting the information, Trouche et al, 2018 †), a finding that is echoed by recent research that suggests that people may differentiate between socially acquired information and information obtained from other (nonsocial) sources (Sulik et al, 2021;Winet et al, 2022). In the same vein, research on advice-based decisions must also position itself with respect to the growing literature on how people utilize algorithmic advice and recommendation systems (e.g., Logg et al, 2019;Nolan et al, 2016;, where social concerns may play a different and perhaps lesser role.…”

Expanding Nature’s storytelling: extended reality and debiasing strategies for an eco-agency

“…Taking into account aggregation dynamics, we know individual psychological processes can become group-level phenomena (Sulik et al, 2021). Be it systematic or inconsistent, cognitive biases always create error, often shared errors (Kahneman et al, 2021).…”

“…The environmental narrative has been mostly directed to the cognitive component of our attitudes, which has proven to be insufficient (Stoknes, 2014). Considering the developments of the Internet of Things 1 (IoT), artificial intelligence (AI), and driving from studies on public participation and environmental monitoring (Gouveia et al, 2004), climate communication strategies (Stoknes, 2014) and approaches to psychological biases (Botzen et al, 2021;Kahneman et al, 1982Kahneman et al, , 2021Korteling et al, 2021;Sulik et al, 2021) also over public policies (Lechanoine & Gangi, 2020), our research aims at attempting a more directi.e., less mediateddiscourse, by using ecosystem data and extended reality (XR) 2 technologies.…”