The Impact of Cognitive Style Diversity on Implicit Learning in Teams

Strengthening a culture of research dissemination: A narrative report of research day at King Faisal Hospital Rwanda, a tertiary-level teaching hospital in Rwanda

BACKGROUND

There are significant gaps in research output and authorship in low- and middle-income countries. Research dissemination events have the potential to help bridge this gap through knowledge transfer, institutional collaboration, and stakeholder engagement. These events may also have an impact on both clinical service delivery and policy development. King Faisal Hospital Rwanda (KFH) is a tertiary-level teaching hospital located in Kigali, Rwanda. To strengthen its research dissemination, KFH conducted an inaugural Research Day (RD) to disseminate its research activities, recognize staff and student researchers at KFH, define a research agenda for the hospital, and promote a culture of research both at KFH and in Rwanda.

METHODS

RD was coordinated by an interdisciplinary committee of clinical and non-clinical staff at KFH. Researchers were encouraged to disseminate their research across all disciplines. Abstracts were blind reviewed using a weighted rubric and ranked by overall score. Top researchers were also awarded and recognized for their work, and equity and inclusion was at the forefront of RD programming.

RESULTS

RD had over 100 attendees from KFH and other public, private, and academic institutions. Forty-seven abstracts were submitted from the call for abstracts, with the highest proportion studying cancer (17.02%) and sexual and reproductive health (10.64%). Thirty-seven researchers submitted abstracts, and most of the principal investigators were medical doctors (35.14%), allied health professionals (27.03%), and nurses and midwives (16.22%). Furthermore, 30% of principal investigators were female, with the highest proportion of them being nurses and midwives (36.36%).

CONCLUSION

RD is an effective way to disseminate research in a hospital setting. RD has the potential to strengthen the institution's research agenda, engage the community in ongoing projects, and provide content-area support to researchers. Equity and inclusion should be at the forefront of research dissemination, including gender equity, authorship representation, and the inclusion of interdisciplinary health professionals. Stakeholder engagement can also be utilized to strengthen institutional research collaboration for greater impact.

Interaction among participants in a collective intelligence experiment: an emotional approach

Introduction

The construct of collective intelligence assumes that groups have a better capacity than individuals to deal with complex, poorly defined problems. The digital domain allows us to analyze this premise under circumstances different from those in the physical environment: we can gather an elevated number of participants and generate a large quantity of data.

Methods

This study adopted an emotional perspective to analyze the interactions among 794 adolescents dealing with a sexting case on an online interaction platform designed to generate group answers resulting from a certain degree of achieved consensus.

Results

Our results show that emotional responses evolve over time in several phases of interaction. From the onset, the emotional dimension predicts how individual responses will evolve, particularly in the final consensus phase.

Discussion

Responses gradually become more emotionally complex; participants tend to identify themselves with the victim in the test case while increasingly rejecting the aggressors.

Maintaining Transient Diversity Is a General Principle for Improving Collective Problem Solving

Humans regularly solve complex problems in cooperative teams. A wide range of mechanisms have been identified that improve the quality of solutions achieved by those teams on reaching consensus. We argue that many of these mechanisms work via increasing the transient diversity of solutions while the group attempts to reach a consensus. These mechanisms can operate at the level of individual psychology (e.g., behavioral inertia), interpersonal communication (e.g., transmission noise), or group structure (e.g., sparse social networks). Transient diversity can be increased by widening the search space of possible solutions or by slowing the diffusion of information and delaying consensus. All of these mechanisms increase the quality of the solution at the cost of increased time to reach it. We review specific mechanisms that facilitate transient diversity and synthesize evidence from both empirical studies and diverse formal models-including multiarmed bandits, NK landscapes, cumulative-innovation models, and evolutionary-transmission models. Apparent exceptions to this principle occur primarily when problems are sufficiently simple that they can be solved by mere trial and error or when the incentives of team members are insufficiently aligned. This work has implications for our understanding of collective intelligence, problem solving, innovation, and cumulative cultural evolution.

Understanding Collective Intelligence: Investigating the Role of Collective Memory, Attention, and Reasoning Processes

As society has come to rely on groups and technology to address many of its most challenging problems, there is a growing need to understand how technology-enabled, distributed, and dynamic collectives can be designed to solve a wide range of problems over time in the face of complex and changing environmental conditions-an ability we define as "collective intelligence." We describe recent research on the Transaction Systems Model of Collective Intelligence (TSM-CI) that integrates literature from diverse areas of psychology to conceptualize the underpinnings of collective intelligence. The TSM-CI articulates the development and mutual adaptation of transactive memory, transactive attention, and transactive reasoning systems that together support the emergence and maintenance of collective intelligence. We also review related research on computational indicators of transactive-system functioning based on collaborative process behaviors that enable agent-based teammates to diagnose and potentially intervene to address developing issues. We conclude by discussing future directions in developing the TSM-CI to support research on developing collective human-machine intelligence and to identify ways to design technology to enhance it.

Cognitive versatility and adaptation to fluid participation in hospital emergency department teams

Role-based frameworks have long been the cornerstone of organizational coordination, providing clarity in role expectations among team members. However, the rise of "fluid participation"-a constant shift in team composition and skill sets-poses new challenges to traditional coordination mechanisms. In particular, with fluid participation, a team's roles can oscillate between disconnected and intersecting, or between lacking and having overlap in the capabilities and expectations of different roles. This study investigates the possibility that a disconnected set of roles creates a structural constraint on the flexible coordination needed to perform in volatile contexts, as well as the mitigating role of cognitive versatility in a team's strategically-central member. Utilizing a sample of 342 teams from a hospital Emergency Department, we find that teams with a disconnected role set are less effective than teams with an intersecting role set as demonstrated by longer patient stays and increased handoffs during shift changes. Importantly, the presence of a cognitively versatile attending physician mitigates these negative outcomes, enhancing overall team effectiveness. Our findings remain robust even after accounting for other variables like team expertise and familiarity. This research extends the Carnegie School's seminal work on fluid participation by integrating insights from psychology and organizational behavior, thereby identifying key individual attributes that can bolster team coordination in dynamic settings.

When and how is team cognitive diversity beneficial? An examination of Chaxu climate

The workforce is becoming increasingly heterogeneous in terms of age, gender, race/ethnicity, education, values, cognition, and culture. Thus, team diversity management is regarded as an important development strategy that organizations can use to gain advantages. However, in the diversity literature, empirical studies investigating the effects of cognitive diversity on creativity have not yielded conclusive findings. This has called into question the importance of team cognitive diversity. To address this, we investigate when and how team cognitive diversity fosters individual creativity. Drawing on the categorization-elaboration model (CEM) and literature on Chaxu climate, we develop a multilevel mediated moderation model in which the team Chaxu climate is treated as the moderator and team knowledge sharing is treated as the mediator. Using two-wave paired data collected from 46 teams and 368 members, we find that Chaxu climate mitigates the positive effect of team cognitive diversity on team knowledge sharing. In turn, team knowledge sharing mediates the interaction effect between team cognitive diversity and Chaxu climate on individual creativity. Our study facilitates a shift from an automatic-oriented lens to a contingent-oriented lens by identifying a new contingent factor and advances research on the underlying mechanisms by identifying a new process factor. Ultimately, this study enriches our knowledge on the function of cognitive diversity in the field of business strategy.

Bridging the gap: unleashing the power of non-core departments through interdepartmental collaboration

Traditional research on firm performance has predominantly emphasized the role of key departments, often underestimating the potential contributions of non-core departments. This study redresses this oversight by investigating the impact of non-core departments on firm performance. Utilizing a comprehensive 20-year dataset from Chinese A-listed firms and employing the endogenous growth model, we scrutinize the influence of non-core departments on enterprise productivity and organizational growth. Our findings underscore that non-core departments significantly enhance firm performance. Furthermore, we observe a negative coefficient of the interaction term, implying the presence of diminishing returns to scale when amalgamating department diversity with firm knowledge. This suggests that while both department diversity and firm knowledge independently contribute positively to firm performance, their conjoined effect does not necessarily induce a proportionally amplified impact. Moreover, we found that factors such as the company's equity structure, market environment, and the age and education level of executives may moderate the impact of departmental diversity on firm performance. This study enriches the literature by spotlighting the potential of non-core departments in propelling firm success and underlines the imperative for strategies that cultivate interdepartmental collaboration. The implications of these findings propose that firms can leverage the potential of non-core departments for sustainable growth, offering a fresh perspective for future research in organizational development.

A leadership model supporting maturation of high-performance translational teams

Despite understanding its impact on organizational effectiveness, practical guidance on how to train translational team (TT) leaders is lacking. Previously, we developed an evolutionary learning model of TT maturation consisting of three goal-directed phases: (1). team assembly (Formation); (2). conducting research (Knowledge Generation); and (3). dissemination and implementation (Translation). At each phase, the team acquires group-level knowledge, skills, and attitudes (KSAs) that enhance its performance. Noting that the majority of team-emergent KSAs are promoted by leadership behaviors, we examine the SciTS literature to identify the relevant behaviors for each phase. We propose that effective team leadership evolves from a hierarchical, transformational model early in team Formation to a shared, functional leadership model during Translation. We synthesized an integrated model of TT leadership, mapping a generic "functional leadership" taxonomy to relevant leadership behaviors linked to TT performance, creating an evidence-informed Leadership and Skills Enhancement for Research (LASER) training program. Empirical studies indicate that leadership behaviors are stable across time; to enhance leadership skills, ongoing reflection, evaluation, and practice are needed. We provide a comprehensive multi-level evaluation framework for tracking the growth of TT leadership skills. This work provides a framework for assessing and training relevant leadership behaviors for high-performance TTs.

Data, measurement and empirical methods in the science of science

The advent of large-scale datasets that trace the workings of science has encouraged researchers from many different disciplinary backgrounds to turn scientific methods into science itself, cultivating a rapidly expanding 'science of science'. This Review considers this growing, multidisciplinary literature through the lens of data, measurement and empirical methods. We discuss the purposes, strengths and limitations of major empirical approaches, seeking to increase understanding of the field's diverse methodologies and expand researchers' toolkits. Overall, new empirical developments provide enormous capacity to test traditional beliefs and conceptual frameworks about science, discover factors associated with scientific productivity, predict scientific outcomes and design policies that facilitate scientific progress.

What's on the horizon for community-based conservation? Emerging threats and opportunities

Community-based conservation can support livelihoods and biodiversity, while reinforcing local and Indigenous values, cultures, and institutions. Its delivery can help address cross-cutting global challenges, such as climate change, conservation, poverty, and food security. Therefore, understanding trends in community-based conservation is pertinent to setting and implementing global goals. We undertook a horizon scan to prioritize 15 emerging threats and opportunities expected to impact the future effectiveness of community-based conservation. Topics relate to global biodiversity policy; human rights; shifting human geography; inclusion, diversity, equity, and access; conservation finance and income; and economic reforms. Our findings offer guidance on strengthening community-based conservation to achieve global environmental and development goals.

The Role of Adaptation in Collective Human-AI Teaming

This paper explores a framework for defining artificial intelligence (AI) that adapts to individuals within a group, and discusses the technical challenges for collaborative AI systems that must work with different human partners. Collaborative AI is not one-size-fits-all, and thus AI systems must tune their output based on each human partner's needs and abilities. For example, when communicating with a partner, an AI should consider how prepared their partner is to receive and correctly interpret the information they are receiving. Forgoing such individual considerations may adversely impact the partner's mental state and proficiency. On the other hand, successfully adapting to each person's (or team member's) behavior and abilities can yield performance benefits for the human-AI team. Under this framework, an AI teammate adapts to human partners by first learning components of the human's decision-making process and then updating its own behaviors to positively influence the ongoing collaboration. This paper explains the role of this AI adaptation formalism in dyadic human-AI interactions and examines its application through a case study in a simulated navigation domain.

Evolutionary emergence of collective intelligence in large groups of students

The emergence of collective intelligence has been studied in much greater detail in small groups than in larger ones. Nevertheless, in groups of several hundreds or thousands of members, it is well-known that the social environment exerts a considerable influence on individual behavior. A few recent papers have dealt with some aspects of large group situations, but have not provided an in-depth analysis of the role of interactions among the members of a group in the creation of ideas, as well as the group's overall performance. In this study, we report an experiment where a large set of individuals, i.e., 789 high-school students, cooperated online in real time to solve two different examinations on a specifically designed platform (Thinkhub). Our goal of this paper 6 to describe the specific mechanisms of idea creation we were able to observe and to measure the group's performance as a whole. When we deal with communication networks featuring a large number of interacting entities, it seems natural to model the set as a complex system by resorting to the tools of statistical mechanics. Our experiment shows how an interaction in small groups that increase in size over several phases, leading to a final phase where the students are confronted with the most popular answers of the previous phases, is capable of producing high-quality answers to all examination questions, whereby the last phase plays a crucial role. Our experiment likewise shows that a group's performance in such a task progresses in a linear manner in parallel with the size of the group. Finally, we show that the controlled interaction and dynamics foreseen in the system can reduce the spread of "fake news" within the group.

Cognitive diversity, creativity and team effectiveness: the mediations of inclusion and knowledge sharing

Purpose

This study aims to determine how cognitive diversity at the workplace influences team creativity. In this regard, the authors examined knowledge sharing and team-focused inclusion through which team members’ cognitive diversity was expected to elevate their positive work outcomes.

Design/methodology/approach

A quantitative method is used to accumulate the data. The authors surveyed workers and their respective managers at a single China-based food company. The supervisors rated the outcome variables (creativity and team effectiveness) regarding their employees, whereas employees were asked to rate the cognitive diversity, inclusion and knowledge sharing within the workgroup. The final valid sample size (n = 391) consisted of 137 workgroups with an adequate response rate (62.3%).

Findings

Cognitive diversity is related to team effectiveness but not creativity. The research found that cognitive diversity can increase creativity only through enhanced inclusion and knowledge sharing. Inclusion, likewise, explained the impact of cognitive diversity on effectiveness.

Originality/value

The originality of the current research lies in its contemporary exploration of inclusion and cognitive diversity and their pathways to team creativity and effectiveness. The social capital theory was applied to explain the proposed relationships.

Harnessing the benefits of diversity to address socio-environmental governance challenges

Solving complex problems, from biodiversity conservation to reducing inequality, requires large scale collective action among diverse stakeholders to achieve a common goal. Research relevant to meeting this challenge must model the interaction of stakeholders with diverse cognitive capabilities and the complexity of the problem faced by stakeholders to predict the success of collective action in various contexts. Here, we build a model from first principles of cognitive abilities, diversity, and socio-environmental complexity to identify the sets of conditions under which groups most effectively engage in collective action to solve governance problems. We then fit the model to small groups, U.S. states, and countries. Our model illustrates the fundamental importance of understanding the interaction between cognitive abilities, diversity, and the complexity of socio-environmental challenges faced by stakeholders today. Our results shed light on the ability of groups to solve complex problems and open new avenues of research into the interrelationship between cognition, institutions, and the environments in which they co-evolve.

Collective intelligence and knowledge exploration: an introduction

Collective intelligence and Knowledge Exploration (CI and KE) have been adopted to solve many problems. They are particularly used by companies as a support for innovation to efficiently obtain usable results. CI is usually defined as a group ability to perform consistently well across a wide variety of tasks, and it has to be combined with KD to ensure processes optimization, efficient management process, participative management, leadership, continuous teamwork, and so on. The importance of innovation grows the same way as the importance of mixing CI and KE, ensuring the successful exploitation of knowledge. Here, we present a quick review of current knowledge-oriented CI developments and applications. It aims at showing some observations about what's currently missing. Our editorial presents some recent interesting studies that we have gathered after a tight selection process. It also concludes by proposing avenue challenges to continue pushing CI and KE research forward, particularly regarding knowledge exploration.

Bayesian modeling of human-AI complementarity

With the increase in artificial intelligence in real-world applications, there is interest in building hybrid systems that take both human and machine predictions into account. Previous work has shown the benefits of separately combining the predictions of diverse machine classifiers or groups of people. Using a Bayesian modeling framework, we extend these results by systematically investigating the factors that influence the performance of hybrid combinations of human and machine classifiers while taking into account the unique ways human and algorithmic confidence is expressed.

Artificial intelligence (AI) and machine learning models are being increasingly deployed in real-world applications. In many of these applications, there is strong motivation to develop hybrid systems in which humans and AI algorithms can work together, leveraging their complementary strengths and weaknesses. We develop a Bayesian framework for combining the predictions and different types of confidence scores from humans and machines. The framework allows us to investigate the factors that influence complementarity, where a hybrid combination of human and machine predictions leads to better performance than combinations of human or machine predictions alone. We apply this framework to a large-scale dataset where humans and a variety of convolutional neural networks perform the same challenging image classification task. We show empirically and theoretically that complementarity can be achieved even if the human and machine classifiers perform at different accuracy levels as long as these accuracy differences fall within a bound determined by the latent correlation between human and machine classifier confidence scores. In addition, we demonstrate that hybrid human–machine performance can be improved by differentiating between the errors that humans and machine classifiers make across different class labels. Finally, our results show that eliciting and including human confidence ratings improve hybrid performance in the Bayesian combination model. Our approach is applicable to a wide variety of classification problems involving human and machine algorithms.

Translating Member Ability Into Group Brainstorming Performance: The Role of Collective Intelligence

In investigating how member ability is translated into group brainstorming performance, it was predicted that a group’s collective intelligence (CI) would enable it to capitalize on member ability while maximizing process gains and mitigating process losses. Ninety-nine groups were randomly assigned to complete a short brainstorming task using a hybrid (individual-group work) or collective (only group work) task structure. High CI groups were better than low CI groups at translating member ability into group brainstorming performance. Additionally, this hybrid structure was more beneficial for low CI groups than for high CI groups in generating total ideas.

The Diversity Gap: When Diversity Matters for Knowledge

Can diversity make for better science? Although diversity has ethical and political value, arguments for its epistemic value require a bridge between normative and mechanistic considerations, demonstrating why and how diversity benefits collective intelligence. However, a major hurdle is that the benefits themselves are rather mixed: Quantitative evidence from psychology and behavioral sciences sometimes shows a positive epistemic effect of diversity, but often shows a null effect, or even a negative effect. Here we argue that to make progress with these why and how questions, we need first to rethink when one ought to expect a benefit of cognitive diversity. In doing so, we highlight that the benefits of cognitive diversity are not equally distributed about collective intelligence tasks and are best seen for complex, multistage, creative problem solving, during problem posing and hypothesis generation. Throughout, we additionally outline a series of mechanisms relating diversity and problem complexity, and show how this perspective can inform metascience questions.

Synergistic triad of crisis management: leadership, knowledge management and organizational learning

Purpose

The prevalence of instability and crises in organizational ecosystems seems to be on the increase, with an upward trend in the occurrence of, for example, natural disasters, such as tornadoes in America, bushfires in Australia and the widespread outbreak of diseases, e.g., Covid-19. As contexts of crisis increase in frequency, the ability of organizations to adapt and effectively respond to crises has become a key necessity for organizational survival and continuity. The purpose of this paper is to explore how the repercussions of crises may be curtailed through a multidimensional crisis management approach.

Design/methodology/approach

This paper applies a narrative literature review and concept mapping to synthesize and establish relationships between the literature in the domains of leadership, knowledge management, learning and contexts of crisis. The output of this methodological orientation is the Integrated Crisis Management Framework, presenting a conceptualized overview of the symbiotic and intertwined manner through which leadership, knowledge management and learning contribute towards effective crisis management.

Findings

According to the analysis and the conceptual underpinnings of this paper, in contexts of crisis, leadership is generally responsible for aggregating crisis management strategies and establishing employee motivation. Knowledge management, on the other hand, provides the infrastructure necessary for calculated yet rapid decision-making. Similarly, in times of crisis, learning is a prerequisite for the development of a “learningful” organization, which contributes towards crisis management by serving as the organization's “memory” – where lessons learned from previous crises suffice to guide future crisis response.

Originality/value

The literature in crisis management reveals that existing crisis management models and frameworks generally consider crisis from a unidimensional perspective, neglecting to account for the multifaceted nature of crises, and the numerous attributes necessary to overcome contexts of crisis. To address this gap in the literature, this paper proposes a multidimensional conceptualization of crisis management through combining three core elements, including leadership, learning and knowledge management. The novelty of this paper is an Integrated Crisis Management Framework, and eight empirical propositions, which act as an impetus for future research.

Multiple Team Membership, Performance, and Confidence in Estimation Tasks

Multiple team membership (MTM) is a form of work organization extensively used nowadays to flexibly deploy human resources across multiple simultaneous projects. Individual members bring in their cognitive resources in these multiple teams and at the same time use the resources and competencies developed while working together. We test in an experimental study whether working in MTM as compared to a single team yields more individual performance benefits in estimation tasks. Our results fully support the group-to-individual (G-I) transfer of learning, yet the hypothesized benefits of knowledge variety and broader access to meta-knowledge relevant to the task in MTM as compared to single teams were not supported. In addition, we show that individual estimates improve only when members are part of groups with low or average collective estimation errors, while confidence in individual estimates significantly increases only when the collective confidence in the group estimates is average or high. The study opens valuable venues for using the dynamic model of G-I transfer of learning to explore individual learning in MTM.

Quantifying collective intelligence in human groups

Collective intelligence (CI) is critical to solving many scientific, business, and other problems, but groups often fail to achieve it. Here, we analyze data on group performance from 22 studies, including 5,279 individuals in 1,356 groups. Our results support the conclusion that a robust CI factor characterizes a group's ability to work together across a diverse set of tasks. We further show that CI is predicted by the proportion of women in the group, mediated by average social perceptiveness of group members, and that it predicts performance on various out-of-sample criterion tasks. We also find that, overall, group collaboration process is more important in predicting CI than the skill of individual members.

Innovative Work Behavior—A Key Factor in Business Performance? The Role of Team Cognitive Diversity and Teamwork Climate in This Relationship

The aim of our paper is to examine whether the support of innovative work behavior by management is positively related to business performance and at the same time, whether this relationship is mediated by the teamwork climate and cognitive diversity of teams. Cognitive diversity is defined as differences in knowledge and perspective, which arise from professional diversity and account for its positive effects. A teamwork climate represents staff perceptions of collaboration between personnel. Business performance is defined by the level of sales. Our sample consisted of 211 managers of companies operating in Slovakia, and data collection took place in the form of a questionnaire. The main tool for examining the mechanism of operation of the investigated relationships is mediation using regression analysis and the Sobel test to determine the significance of the indirect effect of mediation variables. The findings point to a significant direct relationship between the innovative work behavior of company employees and business performance. The intensity of this relationship can be partly influenced by promoting cognitive diversity, especially in the area of knowledge and ways of thinking. The significant role of a teamwork climate was not demonstrated in the examined model.

g versus c: comparing individual and collective intelligence across two meta-analyses

Collective intelligence (CI) is said to manifest in a group's domain general mental ability. It can be measured across a battery of group IQ tests and statistically reduced to a latent factor called the "c-factor." Advocates have found the c-factor predicts group performance better than individual IQ. We test this claim by meta-analyzing correlations between the c-factor and nine group performance criterion tasks generated by eight independent samples (N = 857 groups). Results indicated a moderate correlation, r, of .26 (95% CI .10, .40). All but four studies comprising five independent samples (N = 366 groups) failed to control for the intelligence of individual members using individual IQ scores or their statistically reduced equivalent (i.e., the g-factor). A meta-analysis of this subset of studies found the average IQ of the groups' members had little to no correlation with group performance (r = .06, 95% CI -.08, .20). Around 80% of studies did not have enough statistical power to reliably detect correlations between the primary predictor variables and the criterion tasks. Though some of our findings are consistent with claims that a general factor of group performance may exist and relate positively to group performance, limitations suggest alternative explanations cannot be dismissed. We caution against prematurely embracing notions of the c-factor unless it can be independently and robustly replicated and demonstrated to be incrementally valid beyond the g-factor in group performance contexts.

Speaking out of turn: How video conferencing reduces vocal synchrony and collective intelligence

Collective intelligence (CI) is the ability of a group to solve a wide range of problems. Synchrony in nonverbal cues is critically important to the development of CI; however, extant findings are mostly based on studies conducted face-to-face. Given how much collaboration takes place via the internet, does nonverbal synchrony still matter and can it be achieved when collaborators are physically separated? Here, we hypothesize and test the effect of nonverbal synchrony on CI that develops through visual and audio cues in physically-separated teammates. We show that, contrary to popular belief, the presence of visual cues surprisingly has no effect on CI; furthermore, teams without visual cues are more successful in synchronizing their vocal cues and speaking turns, and when they do so, they have higher CI. Our findings show that nonverbal synchrony is important in distributed collaboration and call into question the necessity of video support.

Neurodiversity and the Social Ecology of Mental Functions

In psychiatry, mental dysfunction is typically framed in relation to models that seek to be continuous with physiology or evolutionary biology and that compare individual fitness to a broader functional norm. Proponents of the neurodiversity movement, however, challenge the pathologization of minority cognitive styles and argue that we should reframe neurocognitive diversity as a normal and healthy manifestation of biodiversity. Neurodiversity proponents have thus far drawn on social-relational models of disability to challenge the medical model of disability, but they have not developed an alternative functional analysis to replace conceptions of neurological dysfunction or impairment. Here I clarify and defend the neurodiversity perspective by drawing on ecological functional models that take relational contributions to collectives, and group functioning, into account alongside individual functionality. Using the example of autism as well as recent developments in the study of cognitive diversity, I apply these models to human mental functioning and argue that what I call the ecological model has greater utility for research and practice than the leading psychiatric functional analyses of mental functioning.

Team implicit coordination based on transactive memory systems

Purpose

This study aims to examine how daily communication and transactive memory systems (TMSs) promote implicit team coordination, meaning when team members cooperate smoothly without engaging in explicit communication, in organizations. In TMSs, members share knowledge of who-knows-what with one another.

Design/methodology/approach

A survey was conducted with 216 teams consisting of 1,545 people in three organizations. The relationships among daily communication, TMSs and implicit coordination in the survey data and in team performance were analyzed using multi-level structural equation modeling.

Findings

Results confirmed a significant influence process model in which “daily communication → TMS → implicit coordination → team performance” at the team level. Therefore, as hypothesized, implicit coordination is positively related to team performance and daily communication has a positive relationship with implicit coordination through mediation by TMSs.

Originality/value

This study demonstrated the evidence of the relation between implicit coordination, TMS, team performance in organizational settings by using multi-level structural equation modeling.

Adolescent’s Collective Intelligence: Empirical Evidence in Real and Online Classmates Groups

Humans create teams to be more successful in a large variety of tasks. Groups are characterized by an emergent property called collective intelligence, which leads them to be smarter than single individuals. Previous studies proved that collective intelligence characterizes both real and online environments, focusing on adults’ performances. In this work, we explored which factors promote group success in an offline and online logical task with adolescents. Five hundred and fifty high school students participated in the experiment and faced Raven’s Advanced Progressive Matrices, first by themselves using the computer, then in a group. Groups interactions could have been computer-mediated or face-to-face, and the participants were randomly assigned to one of the two experimental conditions. Results suggest that groups perform better than singles, regardless of the experimental condition. Among adolescents, online groups performance was negatively affected by participants’ average perception of group cohesion, the difficulty of the problem, and the number of communicative exchanges that occur in the interaction. On the contrary, the factors that improve their performances were the average intelligence of the teammates, their levels of neuroticism, and the group heterogeneity in terms of social abilities. This work contributes to the literature with a comprehensive model of collective intelligence among young people.

Social and general intelligence improves collective action in a common pool resource system

On a planet experiencing global environmental change, the governance of natural resources depends on sustained collective action by diverse populations. Engaging in such collective action can only build upon the foundation of human cognition in social-ecological settings. To help understand this foundation, we assess the effect of cognitive abilities on the management of a common pool resource. We present evidence that two functionally distinct cognitive abilities, general and social intelligence, improve the ability of groups to manage a common pool resource. Groups high in both forms of intelligence engage in more effective collective action that is also more consistent, despite social or ecological change. This result provides a foundation for integrating the effects of cognitive abilities with other dimensions of cognitive diversity to explain when groups will and will not sustainably govern natural resources.

Untapped potential of collective intelligence in conservation and environmental decision making

Environmental decisions are often deferred to groups of experts, committees, or panels to develop climate policy, plan protected areas, or negotiate trade-offs for biodiversity conservation. There is, however, surprisingly little empirical research on the performance of group decision making related to the environment. We examined examples from a range of different disciplines, demonstrating the emergence of collective intelligence (CI) in the elicitation of quantitative estimates, crowdsourcing applications, and small-group problem solving. We explored the extent to which similar tools are used in environmental decision making. This revealed important gaps (e.g., a lack of integration of fundamental research in decision-making practice, absence of systematic evaluation frameworks) that obstruct mainstreaming of CI. By making judicious use of interdisciplinary learning opportunities, CI can be harnessed effectively to improve decision making in conservation and environmental management. To elicit reliable quantitative estimates an understanding of cognitive psychology and to optimize crowdsourcing artificial intelligence tools may need to be incorporated. The business literature offers insights into the importance of soft skills and diversity in team effectiveness. Environmental problems set a challenging and rich testing ground for collective-intelligence tools and frameworks. We argue this creates an opportunity for significant advancement in decision-making research and practice.