How large language models can reshape collective intelligence.

Collective intelligence underpins the success of groups, organizations, markets and societies. Through distributed cognition and coordination, collectives can achieve outcomes that exceed the capabilities of individuals-even experts-resulting in improved accuracy and novel capabilities. Often, collective intelligence is supported by information technology, such as online prediction markets that elicit the 'wisdom of crowds', online forums that structure collective deliberation or digital platforms that crowdsource knowledge from the public.

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.

Diversity of contributions is not efficient but is essential for science.

Dominant paradigms in science foster integration of research findings, but at what cost? Forcing convergence requires centralizing decision-making authority, and risks reducing the diversity of methods and contributors, both of which are essential for the breakthrough ideas that advance science.

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.

Fostering Collective Intelligence in Human-AI Collaboration: Laying the Groundwork for COHUMAIN.

Artificial Intelligence (AI) powered machines are increasingly mediating our work and many of our managerial, economic, and cultural interactions. While technology enhances individual capability in many ways, how do we know that the sociotechnical system as a whole, consisting of a complex web of hundreds of human-machine interactions, is exhibiting collective intelligence? Research on human-machine interactions has been conducted within different disciplinary silos, resulting in social science models that underestimate technology and vice versa. Bringing together these different perspectives and methods at this juncture is critical.

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

[This corrects the article DOI: 10.1371/journal.pone.

COHUMAIN: Building the Socio-Cognitive Architecture of Collective Human-Machine Intelligence.

In recent years, we have experienced rapid development of advanced technology, machine learning, and artificial intelligence (AI), intended to interact with and augment the abilities of humans in practically every area of life. With the rapid growth of new capabilities, such as those enabled by generative AI (e.g.

The benefits of cognitive style versatility for collaborative work.

A growing body of the literature shows the influence of cognitive styles, which capture the ways individuals share, encode, and process information, and their implications for collaboration. We build on this literature to investigate the special contributions of individuals with cognitive style versatility, or facility in more than one cognitive style, for improving teams' collaborative performance. In two studies, including a total of 452 participants in 132 teams, we observe that the presence of cognitively versatile individuals has direct (Study 1) and indirect (Study 2) effects on team performance.

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.

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.

Visualized Automatic Feedback in Virtual Teams.

Management of effort is one of the biggest challenges in any team, and is particularly difficult in distributed teams, where behavior is relatively invisible to teammates. Awareness systems, which provide real-time visual feedback about team members' behavior, may serve as an effective intervention tool for mitigating various sources of process-loss in teams, including team effort. However, most of the research on visualization tools has been focusing on team communication and learning, and their impact on team effort and consequently team performance has been hardly studied.

The Impact of Cognitive Style Diversity on Implicit Learning in Teams.

Organizations are increasingly looking for ways to reap the benefits of cognitive diversity for problem solving. A major unanswered question concerns the implications of cognitive diversity for longer-term outcomes such as team learning, with its broader effects on organizational learning and productivity. We study how cognitive style diversity in teams-or diversity in the way that team members encode, organize and process information-indirectly influences team learning through collective intelligence, or the general ability of a team to work together across a wide array of tasks.

Teamwork in Health Care: Maximizing Collective Intelligence via Inclusive Collaboration and Open Communication.

Teams offer the potential to achieve more than any person could achieve working alone; yet, particularly in teams that span professional boundaries, it is critical to capitalize on the variety of knowledge, skills, and abilities available. This article reviews research from the field of organizational behavior to shed light on what makes for a collectively intelligent team. In doing so, we highlight the importance of moving beyond simply including smart people on a team to thinking about how those people can effectively coordinate and collaborate.

Reading the Mind in the Eyes or reading between the lines? Theory of Mind predicts collective intelligence equally well online and face-to-face.

Recent research with face-to-face groups found that a measure of general group effectiveness (called "collective intelligence") predicted a group's performance on a wide range of different tasks. The same research also found that collective intelligence was correlated with the individual group members' ability to reason about the mental states of others (an ability called "Theory of Mind" or "ToM"). Since ToM was measured in this work by a test that requires participants to "read" the mental states of others from looking at their eyes (the "Reading the Mind in the Eyes" test), it is uncertain whether the same results would emerge in online groups where these visual cues are not available.

Evidence for a collective intelligence factor in the performance of human groups.

Psychologists have repeatedly shown that a single statistical factor--often called "general intelligence"--emerges from the correlations among people's performance on a wide variety of cognitive tasks. But no one has systematically examined whether a similar kind of "collective intelligence" exists for groups of people. In two studies with 699 people, working in groups of two to five, we find converging evidence of a general collective intelligence factor that explains a group's performance on a wide variety of tasks.

Using brain-based measures to compose teams: how individual capabilities and team collaboration strategies jointly shape performance.

Advances in understanding neural processes open the possibility of using brain-based measures to compose collaborative work teams. Neuroimaging studies have shown that individual differences in patterns of brain activity can predict differences in performance of specific tasks. We extended this finding by examining performance not simply by a single brain, but by pairs of brains.