Making better decisions in groups

Abstract

We review the literature to identify common problems of decision-making in individuals and groups. We are guided by a Bayesian framework to explain the interplay between past experience and new evidence, and the problem of exploring the space of hypotheses about all the possible states that the world could be in and all the possible actions that one could take. There are strong biases, hidden from awareness, that enter into these psychological processes. While biases increase the efficiency of information processing, they often do not lead to the most appropriate action. We highlight the advantages of group decision-making in overcoming biases and searching the hypothesis space for good models of the world and good solutions to problems. Diversity of group members can facilitate these achievements, but diverse groups also face their own problems. We discuss means of managing these pitfalls and make some recommendations on how to make better group decisions.

Rescuing Collective Wisdom when the Average Group Opinion Is Wrong

“…Using the abovementioned example of school children who all learned about mushrooms from a common textbook, we can conclude that in such a scenario, the group essentially behaves as a single person and no independent cancelation of errors takes place (Bang and Frith, 2017). But the influence of opinion dependencies is sometimes even more destructive.…”

“…Pairs of variables that show a mutual relation to each other are frequently studied using their correlations (though there are other forms of dependencies not captured by correlations). Correlations can impede the emergence of collective intelligence (Bang and Frith, 2017). Thus, in the social sciences, much effort has been devoted to methodologies aimed at eliminating correlations and encouraging independence (Janis, 1972;Myers and Lamm, 1976;Kahneman, 2011), but we will review situations where correlations boost group performance as well.…”

“…As an example, consider the case of a crowd IQ test (Bachrach et al, 2012), where many people fill out the same IQ test in parallel. Here, a machine learning method known as a graphical model is applied to the problem of collective decision-making.…”

The Active Inference Approach to Ecological Perception: General Information Dynamics for Natural and Artificial Embodied Cognition

“…Agents with this specification would interactively probe and learn the apparent regularities of their world. At the same time, with sufficient complexity, they would have the capacity to critically evaluate their own generalizations from past environmental exposure, to identify when forms of bias are detrimental, and to engage in meaningfully value-laden self-corrective recalibration (while of course this provides no guarantees, even for humans; see, e.g., Bang and Frith, 2017;Holroyd et al, 2017).…”

Decision making in perceived devastating brain injury: a call to explore the impact of cognitive biases

“…Scrutinizing the decision making process with insights gained from cognitive psychology allows us to better understand and minimize the impact of systematic biases that may lead us to more proactively argue for WLST. The first step in the right direction is being aware of the neuropsychological driving forces of decision making at the 18 . This kind of approach was elegantly illustrated in the recent article by Braxton and colleagues outlining cognitive biases leading to an overinvestment in futile therapeutics at the end of life in the ICU setting 19 .…”