What crowds teach us about the internet
Photo: Chris Linnett
I explored the idea of how powerful crowd dynamics can be, more deeply through The Wisdom and/or Madness of Crowds explorable, which is an interactive simulation that lets you experiment with how people influence each other in a network. What stood out most is that crowds are not naturally smart or misinformed, but they become one or the other depending on how they are structured.
In the simulation, small changes made a huge difference. When individuals had some independence and weren’t overly influenced by their neighbors, the crowd was more likely to reach accurate conclusions. But when conformity increased or everyone became too tightly connected, the group quickly fell into patterns of copying rather than thinking. What surprised me most was how fast things could go wrong. Even when most individuals started close to the correct answer, high conformity caused the entire group to drift away from the truth. It made it clear that being connected is not enough, but how we are connected matters.
This connects to the ideas in Cormier’s blog post on the pro-social web, where he argues that the internet is something we actively build through our participation. His call for a more “pro-social” web really resonated with me because it shifts responsibility away from platforms and toward people and especially educators and learners. To me, “pro-social” in learning spaces means creating environments that encourage thoughtful engagement, respect different perspectives, and support real understanding instead of surface-level participation. It’s not just about being kind but it’s also about designing spaces that make meaningful learning more likely.
When I think about learning environments I’ve experienced, I can see both the “wisdom” and the “madness” of crowds. In classroom discussions, for example, students often hesitate to share ideas that differ from what has already been said. Once a few people speak, others tend to follow similar points, which limits diversity of thought. This is similar to high conformity in the simulation. In online discussion boards, the structure can also influence certain behaviors. If students are required to post before seeing others’ responses, there is usually more variety in ideas. But if everyone reads each other’s posts first, responses can start to feel repetitive.
Social media learning spaces show this even more. Algorithms tend to amplify popular ideas, which can create echo chambers where certain perspectives dominate. This reduces the kind of diversity that the simulation showed is necessary for crowds to be wise. I’ve also seen collaborative spaces like group projects or shared documents where people build on each other’s ideas in meaningful ways. These environments tend to work best when there is a balance between individual contribution and group interaction.
Reflecting on my own role, I realize that being part of a digital learning space comes with responsibility. Whether I am contributing to a discussion, designing a resource, or participating in an online community, my actions do help shape the environment. If I only respond quickly without thinking, I contribute to weaker and less meaningful engagement. But if I take time to reflect, bring in new perspectives, and engage thoughtfully with others, I help create a more pro-social space.
The resources and spaces I participate in should not just deliver information, but they should also encourage the kind of interaction that leads to deeper learning. That might mean designing activities that require independent thinking before collaboration, or creating opportunities for students to bring in diverse viewpoints.
Both the simulation and Cormier’s ideas point to the same conclusion: learning communities don’t just happen, but they are shaped by participation and reflection. If we want better outcomes, we need to be more intentional about how we build and engage in these spaces.
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