Sustainable Communities in the Knowledge Era
Old development models delivered things to communities and then often witnessed their abandonment shortly thereafter. To understand sustainability, let’s begin by examining knowledge networks and their sustainability characteristics.
Sustainability integrates into its context. It becomes part of the community system. Most inputs are designed to be privately owned or are government run. Knowledge networks, on the other hand, are inherently collective. We can learn about sustainability by contrasting industrial product with knowledge networks.
It’s hard to build system-wide sustainability into products because of the economics of products. To be viable in a marketplace, products need to minimize costs while attempting to push market appeal. Once sold, the transactions between seller and customer are, essentially, finished. Industries have strategies for their own survival, but those strategies do not include sustaining collective communities.
In Knowledge Networks.
In contrast, knowledge networks are a system. People join because they are attracted to the network itself – Google, Twitter, Facebook, other social media. The network expands according to its appeal. Demand keeps expanding. Because ideas continually grow, the network has to adapt and incorporate innovations to stay on par with new competition. The relationship between the company and the users continues to grow and gets stronger. They are interconnected. Only through continuous interplay with their collective users can knowledge networks survive. They don’t have to advertise or sell. They have inherent appeal and growth.Monthly Active Facebook Users 2008-2019 in millions
Characteristics of Sustainability
The examples I’ve used are commercial knowledge networks. But the design can be adapted to build community knowledge networks. Here are the components.
The community must be involved early. The community holds knowledge about their social, political, cultural and economic environment. Whatever is being put in place, the community knows this environment and knows what will work. Only the community can place new processes, products and ideas within the living, functional environment of the community. It can establish the rules, practices, leadership, groups and policies that will make it work.
This is a continuous learning process. Networks may begin by people getting together as groups. Communities ought to be engaged, so that the learning can occur. Eventually, many communities should be networked. Information from the communities form the network and build AI. The project can use this adapt to changing circumstances.
Gone are the days when only one sector can likely be effectively involved in a sustainable project. A project changes the policy environment, requires support for services involving NGOs, needs technical goods and services from commercial enterprises, and requires the guidance of researchers from a university. The project design should contain an inherent benefit for each partner. Knowledge networks can reap monetary gains but also read other benefits – learning, growing networks, influence, research, insights, stability, opportunities, new products, markets, or contacts.
Knowledge networks grow in strength as they expand. This benefits all partners – especially the communities. The strength of knowledge gained about an issue increases exponentially as more communities are added. Partner rewards are increased. Networks cannot begin large (network, learning, AI and, sustainability constraints – grist for a separate blog), but they can grow rather quickly.
Easily overlooked are the global and outside forces that constantly change the environment for the community. Many of these pressures are invisible because they do not seemingly set policy or economic, social or political environment in an obvious way. But they are very real. Global financial conditions change exchange rates, energy environments, and costs of raw materials. Climate change affects internal migration, poverty levels, social and political stability. Shifting industrial production to digital networks affects how we learn, who learns and who gets employed. The influences of these outside pressures imply that adaptation is a key component to sustainability.
Adapting in a Knowledge Network
An obvious response to these pressures might be to learn to respond to them. Less rainfall? Sink wells (boreholes). A better way is to learn constantly from the context. Understand the environment and use creativity, innovation, collective problem solving, and critical thinking to work through possibilities. Once many communities are networked and begin to talk with each other, they can compare their issues and compare their stories. The power of networks allow them to identify new solutions. Further, some kinds of analysis of these stories can be employed to find patterns of how communities adapted and under which circumstances. Even under these seemingly simple circumstances, artificial intelligence can be employed.
What might have started out as a simple project should now have expanded. Even if it was a project for rural development, adding just a few simple steps, adds tremendous power by understanding the ability of sustainable systems derived from knowledge enterprises:
- People want to belong to systems that engage them, where they are part of relevant networks from which they learn, build networks, increase opportunities and gain insights.
- Take a multi-sector approach and build into the economic framework a reason for each entity to continue their work. Monetary rewards may not be necessary. Look for knowledge rewards.
- Build into your learning system ways to adapt to outside environmental changes. They are there and often are the very essence of what threatens communities. Communities can be resilient, but they can use your help.
- Your network has the power to help your communities. Expand your community network to include other communities so you can analyze the patterns and trends. Think AI – the system can learn from itself.
This is sustainability in a knowledge era.