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Animals foraging in groups can either search for food themselves (producing) or search for the food discoveries of other individuals (scrounging). Tactic use in producer -scrounger games is partly flexible but individuals tend to show consistency in tactic use under different conditions suggesting that personality might play a role in tactic use in producer -scrounger games. Here we studied the use of producing and scrounging tactics by bold and shy barnacle geese (Branta leucopsis), where boldness is a personality trait known to be repeatable over time in this species. We defined individuals as bold, shy or intermediate based on two novel object tests. We scored the frequency of finding food patches (the outcome of investing in producing) and joining patches (the outcome of investing in scrounging) by bold and shy individuals and their feeding time. Shy individuals had a higher frequency of joining than bold individuals, demonstrating for the first time that personality is associated with tactic use in a producer-scrounger game. Bold individuals tended to spend more time feeding than shy individuals. Our results highlight the importance of including individual behavioural variation in models of producer-scrounger games.

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.collective intelligence | groups | medical diagnostics | dermatology | mammography C ollective intelligence, that is, the ability of groups to outperform individual decision makers when solving complex cognitive problems, is a powerful approach for boosting decision accuracy (1-7). However, despite its potential to boost accuracy in a wide range of contexts, including lie detection, political forecasting, investment decisions, and medical decision making (8-14), little is known about the conditions that underlie the emergence of collective intelligence in real-world domains. Which features of decision makers and decision contexts favor the emergence of collective intelligence? Which decision-making rules permit this potential to be harnessed? We here provide answers to these important questions in the domain of medical diagnostics.Our work builds on recent findings on combining decisions, a research paradigm known as "two heads better than one" (15)(16)(17)(18)(19)(20). In their seminal study, Bahrami et al. (15) showed that two individuals permitted to communicate freely while engaging in a visual perception task, achieved better results than the better of the two did alone. Koriat (17) subsequently demonstrated that this collective intelligence effect also emerges in the absence of communication when the "maximum-confidence slating algorithm" (hereafter called confidence rule) is used and th...

The use of social information is known to affect various important aspects of an individual's ecology, such as foraging, dispersal and space use and is generally assumed to be entirely flexible and context dependent. However, the potential link between personality differences and social information use has received little attention. In this study, we studied whether use of social information was related to personality, using barnacle geese, Branta leucopsis, where boldness is a personality trait known to be consistent over time. We found that the use of social information decreased with increasing boldness score of the individuals. Individuals had lower feeding times when they did not follow the social information and this effect was unrelated to boldness score. When manipulating social information, thereby making it incorrect, individuals irrespective of their boldness score, learned that it was incorrect and ignored it. Our results show that social information use depends on the personality type of an individual, which calls for incorporation of these personality-related differences in studies of spatial distribution of animals in which social information use plays a role.

The istiophorid family of billfishes is characterized by an extended rostrum or 'bill'. While various functions (e.g. foraging and hydrodynamic benefits) have been proposed for this structure, until now no study has directly investigated the mechanisms by which billfishes use their rostrum to feed on prey. Here, we present the first unequivocal evidence of how the bill is used by Atlantic sailfish (Istiophorus albicans) to attack schooling sardines in the open ocean. Using high-speed video-analysis, we show that (i) sailfish manage to insert their bill into sardine schools without eliciting an evasive response and (ii) subsequently use their bill to either tap on individual prey targets or to slash through the school with powerful lateral motions characterized by one of the highest accelerations ever recorded in an aquatic vertebrate. Our results demonstrate that the combination of stealth and rapid motion make the sailfish bill an extremely effective feeding adaptation for capturing schooling prey.

While collective intelligence (CI) is a powerful approach to increase decision accuracy, few attempts have been made to unlock its potential in medical decision-making. Here we investigated the performance of three well-known collective intelligence rules (“majority”, “quorum”, and “weighted quorum”) when applied to mammography screening. For any particular mammogram, these rules aggregate the independent assessments of multiple radiologists into a single decision (recall the patient for additional workup or not). We found that, compared to single radiologists, any of these CI-rules both increases true positives (i.e., recalls of patients with cancer) and decreases false positives (i.e., recalls of patients without cancer), thereby overcoming one of the fundamental limitations to decision accuracy that individual radiologists face. Importantly, we find that all CI-rules systematically outperform even the best-performing individual radiologist in the respective group. Our findings demonstrate that CI can be employed to improve mammography screening; similarly, CI may have the potential to improve medical decision-making in a much wider range of contexts, including many areas of diagnostic imaging and, more generally, diagnostic decisions that are based on the subjective interpretation of evidence.

In a wide range of contexts, including predator avoidance, medical decisionmaking and security screening, decision accuracy is fundamentally constrained by the trade-off between true and false positives. Increased true positives are possible only at the cost of increased false positives; conversely, decreased false positives are associated with decreased true positives. We use an integrated theoretical and experimental approach to show that a group of decision-makers can overcome this basic limitation. Using a mathematical model, we show that a simple quorum decision rule enables individuals in groups to simultaneously increase true positives and decrease false positives. The results from a predator-detection experiment that we performed with humans are in line with these predictions: (i) after observing the choices of the other group members, individuals both increase true positives and decrease false positives, (ii) this effect gets stronger as group size increases, (iii) individuals use a quorum threshold set between the average true-and false-positive rates of the other group members, and (iv) individuals adjust their quorum adaptively to the performance of the group. Our results have broad implications for our understanding of the ecology and evolution of group-living animals and lend themselves for applications in the human domain such as the design of improved screening methods in medical, forensic, security and business applications.