Collective intelligence – superior performance by groups compared to that of the individuals that compose them – is often achieved via social information use. However, collective intelligence has rarely been studied in terms of social learning. This is partially because social learning strategies (i.e. "when" and "who" to copy) are often hard to observe in a natural group setting. Our main goal in this article is to show that tandem-running recruitment by Temnothorax ants offers a promising model to study the interaction of social learning and collective intelligence. We first review the role of tandem runs in the ecology and collective behavior of these ants, who use them to share information about the locations of valuable resources. A key advantage of Temnothorax ants as a model system is that each instance of information sharing – each tandem run – can be easily observed. Moreover, the specific information transferred can be readily inferred by tracking the history and subsequent behavior of leader and follower. We then propose new investigations into how social learning via tandem runs affects their collective performance. Finally, we discuss how the synthesis of the two fields of social learning and collective intelligence can shed light on the role of feedback from learning in improving collective performance over time.

When the work you do includes more than yourself, you can make contributions through productive or relational value. Productive value refers to contributions you make to create a good or a service. You may have insights about how to sell a product to a new market, how to deliver a service more efficiently, or how to perform a dance more graciously. These ideas and actions enhance the productive value of a task. This is all about delivering great goods and services efficiently and accomplishing tasks with the highest quality. Relational value is about fostering a climate of support and growth among your peers and employees. You add relational value when you behave compassionately, when you encourage your peers to learn, and when you create a psychologically safe place. The more relational value you create in the workplace, the higher the likelihood to generate productive value. Fear, the opposite of psychological safety, imposes a tax on productivity and most certainly kills creativity. We must nurture the capacity to add productive and relational value at the same time. We must encourage the acquisition of technical as well as relational skills.

To provide a framework for understanding the importance of team assembly, we open the chapter with a story about teams of chickens. This leads into a discussion about the “too much talent” effect in a range of arenas. We then discuss the role that diversity plays in scientific teamwork. Studies show that diversity among team members – whether ethnic, international, or institutional – promotes the team’s effectiveness, with ethnic diversity offering the largest boost in impact of the resulting paper. We also define collective intelligence and explore that factors that lead to highly intelligent teams. Finally, by mapping the larger networks team members are involved in, we’ve identified four types of links that influence group effectiveness. By varying the proportion of these types of links within a network, we can see how certain coauthorship patterns will impact a team’s success. Taken together, these results show a strong correlation between a team’s composition and the quality of the work it produces. We end by discussing super-ties, or extremely close working relationships that become scientific partnerships, which yield surprising citation and productivity premiums.

New and emerging environmental issues make policy and practice difficult. A pressing need to respond when knowledge of the problem is limited is added to an already challenging conservation agenda. Horizon-scanning is an evolving approach that draws on diverse information sources to identify early indications of poorly recognised threats and opportunities. There are many ways to conduct horizon scans, ranging from automated techniques that scan online content and mine text to manual methods that systematically consult large groups of people (often experts). These different approaches aim to sort through vast volumes of information to look for signals of change, for example the rise in microplastics or the use of mobile phones to gather data in remote forests. Identifying these new threats and opportunities is the first important step towards further researching and managing them. This chapter reviews different approaches to horizon-scanning, together with ways of encouraging uptake of scanning outputs. It concludes by introducing emerging technologies that will add value to horizon-scanning in the future.

This chapter poses some of the principal questions that will confront the future of intelligence research. Among these questions are (1) What is the role of the brain in intelligence and of intelligence-enhancing drugs upon the brain? (2) Does culture affect what intelligence is or just what it is conceived of as being? (3) What are the genetic bases of intelligence? (4) Can intelligence of individuals be meaningfully increased by environmental interventions? (5) Is high intelligence having negative as well as positive effects on the world, and what is to be done about it? (6) Will artificial intelligence ultimately be dangerous to the world? (7) What effects are social media and the Internet more generally having on both individual and collective intelligence? (8) Why are people who are so intelligent at times so lacking in rational and wise thinking? (9) Are there noncognitive (e.g., emotional, attitudinal, motivational) aspects of intelligence and, if so, what are they? (10) What kinds of environmental factors inadvertently decrease intelligence?

In addition to human, animal, and artificial intelligence, there is another important kind of intelligence on our planet: the collective intelligence of groups of individuals acting collectively in ways that seem intelligent. This chapter analyzes collective intelligence in terms of what tasks are being done, who is doing them, and why and how the tasks are being done. For instance, the chapter shows how groups can have both specialized and general collective intelligence and how the collective intelligence of a group can depend on the task-relevant abilities of group members, their interpersonal abilities, their diversity, and their intrinsic or extrinsic motivations. The chapter also analyzes the factors involved in group-level processes such as deciding, creating, remembering, sensing, learning, and coordinating. Just as studying the neural basis for intelligence links neural processes to cognitive psychology, studying collective intelligence links cognitive psychology to higher-level social, organizational, and economic processes.