Debiasing the crowd: selectively exchanging social information improves collective decision making

Collective decision making is ubiquitous across biological systems. However, biases at the individual level can impair the quality of collective decisions. One prime bias is the human tendency to underestimate quantities. We performed estimation experiments in human groups, in which we re-wired the structure of information exchange, favouring the exchange of estimates closest to an overestimation of the median, expected to approximate the truth. We show that this re-wiring of social information exchange counteracts the underestimation bias and boosts collective decisions compared to random exchange. Underlying this result are a human tendency to herd, to trust large numbers more than small numbers, and to follow disparate social information less. We introduce a model that reproduces all the main empirical results, and predicts conditions for optimising collective decisions. Our results show that leveraging existing knowledge on biases can boost collective decision making, paving the way for combating other cognitive biases threatening collective systems

Daily physical activity patterns in cancer survivors: a pilot study

In cancer survivors physical activity levels are measured primarily with questionnaires. As a result, insight in actual physical activity patterns of cancer survivors is lacking. Activity monitoring with accelerometers revealed that cancer survivors have lower levels of physical activity in the afternoon and early evening. This finding can help to personalize physical activity advice more adequately for these patients

Wise or mad crowds? The cognitive mechanisms underlying information cascades

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.Whether getting vaccinated, buying stocks, or crossing streets, people rarely make decisions alone. Rather, multiple people decide sequentially, setting the stage for information cascades whereby early-deciding individuals can influence others’ choices. To understand how information cascades through social systems, it is essential to capture the dynamics of the decision-making process. We introduce the social drift–diffusion model to capture these dynamics. We tested our model using a sequential choice task. The model was able to recover the dynamics of the social decision-making process, accurately capturing how individuals integrate personal and social information dynamically over time and when their decisions were timed. Our results show the importance of the interrelationships between accuracy, confidence, and response time in shaping the quality of information cascades. The model reveals the importance of capturing the dynamics of decision processes to understand how information cascades in social systems, paving the way for applications in other social systems.German Research Foundation, grant number: KU 3369/1-1Germany’s Excellence Strategy—EXC 2002/1 “Science of Intelligence”—project number 39052313

The effect of boldness on decision-making in barnacle geese is group-size-dependent

In group-living species, decisions made by individuals may result in collective behaviours. A central question in understanding collective behaviours is how individual variation in phenotype affects collective behaviours. However, how the personality of individuals affects collective decisions in groups remains poorly understood. Here, we investigated the role of boldness on the decision-making process in different-sized groups of barnacle geese. Naive barnacle geese, differing in boldness score, were introduced in a labyrinth in groups with either one or three informed demonstrators. The demonstrators possessed information about the route through the labyrinth. In pairs, the probability of choosing a route prior to the informed demonstrator increased with increasing boldness score: bolder individuals decided more often for themselves where to go compared with shyer individuals, whereas shyer individuals waited more often for the demonstrators to decide and followed this information. In groups of four individuals, however, there was no effect of boldness on decision-making, suggesting that individual differences were less important with increasing group size. Our experimental results show that personality is important in collective decisions in pairs of barnacle geese, and suggest that bolder individuals have a greater influence over the outcome of decisions in groups

Harnessing the wisdom of crowds can improve guideline compliance of antibiotic prescribers and support antimicrobial stewardship

open access articleAntibiotic overprescribing is a global challenge contributing to rising levels of antibiotic resistance and mortality. We test a novel approach to antibiotic stewardship. Capitalising on the concept of “wisdom of crowds”, which states that a group’s collective judgement often outperforms the average individual, we test whether pooling treatment durations recommended by different prescribers can improve antibiotic prescribing. Using international survey data from 787 expert antibiotic prescribers, we run computer simulations to test the performance of the wisdom of crowds by comparing three data aggregation rules across different clinical cases and group sizes. We also identify patterns of prescribing bias in recommendations about antibiotic treatment durations to quantify current levels of overprescribing. Our results suggest that pooling the treatment recommendations (using the median) could improve guideline compliance in groups of three or more prescribers. Implications for antibiotic stewardship and the general improvement of medical decision making are discussed. Clinical applicability is likely to be greatest in the context of hospital ward rounds and larger, multidisciplinary team meetings, where complex patient cases are discussed and existing guidelines provide limited guidance

How to detect high-performing individuals and groups: Decision similarity predicts accuracy

Distinguishing between high- and low-performing individuals and groups is of prime importance in a wide range of high-stakes contexts. While this is straightforward when accurate records of past performance exist, these records are unavailable in most real-world contexts. Focusing on the class of binary decision problems, we use a combined theoretical and empirical approach to develop and test a approach to this important problem. First, we use a general mathematical argument and numerical simulations to show that the similarity of an individual's decisions to others is a powerful predictor of that individual's decision accuracy. Second, testing this prediction with several large datasets on breast and skin cancer diagnostics, geopolitical forecasting, and a general knowledge task, we find that decision similarity robustly permits the identification of high-performing individuals and groups. Our findings offer a simple, yet broadly applicable, heuristic for improving real-world decision-making systems

Boosting medical diagnostics by pooling independent judgments

Collective intelligence refers to the ability of groups to outperform individual decision makers when solving complex cognitive problems. Despite its potential to revolutionize decision making in a wide range of domains, including medical, economic, and political decision making, at present, little is known about the conditions underlying collective intelligence in real-world contexts. We here focus on two key areas of medical diagnostics, breast and skin cancer detection. Using a simulation study that draws on large real-world datasets, involving more than 140 doctors making more than 20,000 diagnoses, we investigate when combining the independent judgments of multiple doctors outperforms the best doctor in a group. We find that similarity in diagnostic accuracy is a key condition for collective intelligence: Aggregating the independent judgments of doctors outperforms the best doctor in a group whenever the diagnostic accuracy of doctors is relatively similar, but not when doctors' diagnostic accuracy differs too much. This intriguingly simple result is highly robust and holds across different group sizes, performance levels of the best doctor, and collective intelligence rules. The enabling role of similarity, in turn, is explained by its systematic effects on the number of correct and incorrect decisions of the best doctor that are overruled by the collective. By identifying a key factor underlying collective intelligence in two important real-world contexts, our findings pave the way for innovative and more effective approaches to complex real-world decision making, and to the scientific analyses of those approaches

Increased searching and handling effort in tall swards lead to a Type IV functional response in small grazing herbivores

Understanding the functional response of species is important in comprehending the species’ population dynamics and the functioning of multi-species assemblages. A Type II functional response, where instantaneous intake rate increases asymptotically with sward biomass, is thought to be common in grazers. However, at tall, dense swards, food intake might decline due to mechanical limitations or if animals selectively forage on the most nutritious parts of a sward, leading to a Type IV functional response, especially for smaller herbivores. We tested the predictions that bite mass, cropping time, swallowing time and searching time increase, and bite rate decreases with increasing grass biomass for different-sized Canada geese (Branta canadensis) foraging on grass swards. Bite mass indeed showed an increasing asymptotic relationship with grass biomass. At high biomass, difficulties in handling long leaves and in locating bites were responsible for increasing cropping, swallowing, and searching times. Constant bite mass and decreasing bite rate caused the intake rate to decrease at high sward biomass after reaching an optimum, leading to a Type IV functional response. Grazer body mass affected maximum bite mass and intake rate, but did not change the shape of the functional response. As grass nutrient contents are usually highest in short swards, this Type IV functional response in geese leads to an intake rate that is maximised in these swards. The lower grass biomass at which intake rate was maximised allows resource partitioning between different-sized grazers. We argue that this Type IV functional response is of more importance than previously thought

The impact of egg incubation temperature on the personality of oviparous reptiles

Personality traits, defined as differences in the behavior of individual animals of the same species that are consistent over time and context, such as ‘boldness,’ have been shown to be both heritable and be influenced by external factors, such as predation pressure. Currently, we know very little about the role that early environmental factors have upon personality. Thus, we investigated the impact of incubation temperature upon the boldness on an oviparous reptile, the bearded dragon (Pogona vitticeps). Eggs, from one clutch, were incubated at two different average temperatures within the normal range. After hatching the lizards were raised under the same environmental conditions. Novel object and novel environment tests were used to assess personality. Each test was repeated in both the short term and the long term. The results revealed that incubation temperature did impact upon ‘boldness’ but only in the short term and suggests that, rather than influencing personality, incubation temperature may have an effect on the development of behavioral of oviparous reptiles at different stages across ontogeny