How To Make Group Decisions Quickly – Advice For Web3 From Birds

How can large groups of people – thousands or millions – arrive at consensus quickly in the absence of a central authority? Conventional wisdom says that they cannot. Moreover, in many countries around the world, the chasm between people with different values is widening, making voluntary consensus even less likely. This reality is why we have elected or appointed leaders to make decisions on our behalf.

Why This Matters Now More Than Ever: The Impact on Web3

This solution, however efficient, may not work with the next generation of web technologies, collectively known as Web3. Decentralized entities will employ blockchain and smart contracts to democratize internet business, empowering consumers and employees in a way that is lacking from our current Web2 businesses. Take Uber as an example. Riders and drivers give the company their information – real-time location, payment info, etc. – which Uber stores and uses to connect riders to drivers. If Uber decides to change its strategy, alter a policy, or add a new service, it does not seek opinions or approval from its customers or employees. Its senior leadership team weighs the alternatives and makes a decision.

Compare that to Drife, a start-up in India that also offers ride-hailing services, but using decentralized Web3 technologies. Its policies allow customers to have a voice in the decisions of the platform. Will this democratization be empowering or debilitating to the future of the company?

Theoretical Underpinnings and Goals: Towards a Theory of Dynamic Collective Action

This question – how can large groups make decisions quickly – lies at the intersection of two existing fields of academic study. On the one hand, theories of Collective Action describe the necessary conditions under which people can agree on goals and actions without a central authority. As the size of the group and the complexity of the problem increase, the likelihood for consensus diminishes. On the other hand, theories of Dynamic Capabilities describe how leaders must sense changes in the market, seize new opportunities, and transform their businesses to continue to thrive. What this research seeks to find is a new theory of Dynamic Collective Action. Joining me in this quest is Annie Pflaum, a researcher in California who is contributing her bibliographic and analytical skills, along with a huge dollop of curiosity. This article is the first output of our work, and will hopefully blossom into several academic publications.

Lessons from Birds: Murmurations

The field of biomimicry examines instances from the natural world to find solutions to human problems. This approach is both fruitful in general and personally compelling for both Annie and me, as we endeavor to spend as much time in the wild outdoors as possible.

While there are hundreds of different models for leadership across different animal species, many rely on hierarchies to imbue a subset of the group with authority to make decisions. One vivid exception occurs with swallows (of the Latin family Hirundinidae) and starlings (Sturnidae).

These birds form enormous groups called murmurations – so named because of the eery sound of thousands of beating wings as the entire flock swerves and ripples. Even though there is no leader, the birds exhibit remarkable cohesion and coordination during flight. In flocks of up to 6 million animals, they swiftly make split second decisions at both the individual and collective level to avoid internal collisions and protect themselves against predators.

Two simple rules govern their choreography. First, each bird has an interest to migrate towards the center of the group, farther from the possibility of predation by a hawk on the fringes. (It’s also possible that the size of the group scares off predators.) Since the flock’s center point is always changing, the formation of the birds is dynamic, constantly shifting into new shapes and speeds. Second, each bird tracks only its seven nearest neighbors in order to avoid a collision. This mix of global ambition (get to the center) and local action (do not bump into those seven) are both driven by self-interest and still lead to swift, coordinated action without any leadership.

With some creativity, these two rules can be applied to Web3 entities. To honor the first rule of murmurations, Web3 entities could require participants to make a deposit into the entity’s capital pool. Even if the entity distributes profits that far exceed the size of the deposit, the entity could retain this original stake to incent participants to support the entity’s long-term survival.

One way to implement a murmuration’s second rule is to publish frequent updates for each participant on the actions of those other participants who act in a similar manner. In other words, for a decentralized ride hailing entity like Drife, the company could report to each driver the anonymized statistics for nearby drivers with typical patterns. Such a report might show the average time waiting for a ride, going to a pick-up point, and transporting fare-paying passengers for those people in a specific neighborhood who work similar hours during similar times of the week (for example, weekdays during the morning commute).

If the ride hailing entity proposes a change of policy, drivers might be more likely to quickly find and support a consensus if they have this long-term stake in the entity and an understanding of the implications of the proposal on them and drivers like them.

Additional Research: Empirical Testing

Our next step in this search for a theory of Dynamic Collective Action involves the collection and analysis of data from a popular decentralized entity that relies on multi-layered rules to conduct large-scale voting. We hope to not only test the hypotheses for Web3 governance that emerge from swallow murmurations, but also determine if other methods and structures of collective governance operate more efficiently and effectively.

While we are focused on entities that emerge from blockchain, smart contracts, and artificial intelligence, a theory of Dynamic Collective Action might also illuminate ways to get millions of people to quickly agree to solutions for even more pressing issues like climate change and cultural division.

Stay tuned.