Harmony assistant using rewire4/29/2023 ![]() ![]() ![]() The argument being, if someone is creative at something, it might draw more attention to the creative person, resulting in an increased centrality and visibility. proposed a spiraling model, capturing the cyclical relationship between creativity and network position, where one fosters the other. When it comes to creativity, the dynamic nature of social networks has received rather little research attention. ![]() This dynamic characteristic affords opportunities in human populations that static networks cannot: for example, dynamic networks promote cooperation, collective intelligence, and speaking skills, among others. Given an objective, they can choose to make or break ties to update the connectivity patterns around them, often in response to the behaviour, performance, prestige, age, gender, popularity, self-similarity and other cues of the social partners. Human interactions are structured in social networks, where people have control over who they interact with. However, a key element missing from most prior literature is the dynamic characteristic of real social networks. For instance, relationship strength, position and external ties of people are known to influence creative performance. Researchers have examined the effects of various network attributes on creativity. Adopting a social network lens helps us better understand the mechanisms, bottlenecks and opportunities for maximizing creative outcomes at-scale. A graphic designer can find creative inspiration from peer-interactions in online networks like Reddit, Behance or Twitter. Discussions in an academic network of researchers, faculty members and students can stimulate ideas for novel explorations. For instance, the development of an innovative product such as an aircraft or a computer operating system is only made possible by an interacting network of creative problem solvers, who benefit from each other’s expertise. This motivation for creativity-at-scale leads to the exploration of social networks of creative collaborators. Thus, enhancing the creative abilities of collaborating humans has become one of the aspirational challenges today. Again, many of the critical and challenging tasks of the human civilization require humans to collaborate with others, where they need to perform creatively at both individual and collective levels. ![]() The need for manual labour in predictable and repetitive work is declining, while the demand is soaring for expertise in creative tasks, problem-solving and other social-cognitive avenues of soft-skills. Approximately 51 % of the tasks done in the US economy can be automated, and for each robot on the factory floor, some six jobs are lost. These innovations, however, have serious implications on our future workforce. Recent advances in robotics, AI and machine learning are increasingly focused on mimicking or even surpassing human capabilities. Our findings may help design large-scale interventions to improve the creative aptitude of people interacting in a social network. We formulate an agent-based simulation model to capture these intuitions in a tractable manner, and experiment with corner cases of various simulation parameters to assess the generality of the findings. While exposure to high-performing peers is associated with better creative performances of the followers, we see a counter-effect that choosing to follow the same peers introduces semantic similarities in the followers’ ideas. We unearth both opportunities and bottlenecks afforded by such self-organization. We find that network connections gradually adapt to individual creative performances, as the participants predominantly seek to follow high-performing peers for creative inspirations. We run six trials ( N = 288) of a web-based experiment involving divergent ideation tasks. In this paper, we explore how the dynamic (self-organizing) nature of social networks impacts the fostering of creative ideas. Creativity is viewed as one of the most important skills in the context of future-of-work. ![]()
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