AI systems as Common Good for Communities
Imagine an AI system that authentically embodies the collective intelligence, history and aspirations of a small community, whether online or offline. A system that can quickly synthesise data from multiple sources, also understanding the unique culture, challenges and strengths that arise from the creators of such data.
In this article I will explore how a “community AI” would be a living extension of the group’s identity by analyzing hyper-local data, facilitating dialogue among members, and helping synthesize tailored solutions aligned with shared goals.
AI as a Common Good
Can AI be thought of as a common good?
OpenAI, originally founded with the goal of building a transformative and accessible technology for humanity as a non-profit, shifted to a for-profit structure to address funding needs.
This change, however, reportedly caused tensions and a public dispute with the former co-founder Elon Musk regarding the organization’s direction and the balance between public benefit and potential profit. These events highlights how challenging it is to develop AI systems at scale as a potential common good.
However, the notion of AI as a common good takes on a different dimension within the context of a small community. While building an AI which aims for general intelligence applicable across diverse contexts, building AI for a community focuses on tailoring functionality and goals to meet the specific needs and values of its members.
Imagine integrating an open-source large language model with the collective identity, history, and wisdom of a specific group of people and using that as the starting context for developing AI powered tools.
This specialized approach may seem less grandiose than the pursuit of generalized AI capabilities, but it can have a profound positive impact by directly enhancing the lives and collective experience of the community it serves. It allows harnessing the power of AI in a more focused and contextualized manner, aligning the technology with the distinct characteristics and use cases of a particular group.
Rather than a one-size-fits-all approach, a community-centric AI development caters directly to the unique needs, values, and objectives of a small group of people, the AI can be purposefully designed as an empowering tool to uplift communal welfare at a smaller scale.
Ultimately, AI’s role as a common good manifests through its ability to be consciously shaped in service of people’s real-world contexts and shared interests.
Embodying the Hivemind
In my previous article about creative hives, I explained how interactions within a group collectively shape a shared cultural sphere.
When a community builds an AI system that taps into the collective intelligence, history, and aspirations of the members, can we think about the shared cultural sphere as a digital soul? What would be the implications of embodying the collective intelligence of a community through a technological simulacrum?
The creation of such an AI system would surely involve the integration of multiple components to enable the collection, analysis, and application of data generated within the community itself. Additionally, an interface that allows the group to easily interact with the system would also be necessary to enable the participation of less technical people and speed up human-machine interactions.
To visualize this with a concrete example, let’s imagine an AI system that analyzes local energy consumption patterns across households and businesses in the community. By ingesting data from smart meters, utility bills, and public census information, it could pinpoint inefficiencies, forecast demand, and map out sources like residential solar installations.
Utilizing the data from these sources, the system could then make customized recommendations in a local public forum based on the community’s specific geography, climate patterns and infrastructure. Through conversational interfaces and visualization tools tailored to the specific use cases of the community, it may suggest optimized heating/cooling schedules, opportunities for energy co-ops, ideal sites for sustainable micro-grids, or programs to assist low-income members in accessing renewable sources.
This example can be extended to any type of community problem that involves local data streams and information exchange.
As community members discuss proposals and community issues, the conversational component of the system could dynamically update the data based on the discourse — incorporating critiques, new ideas, and nuanced context only locals would know, because they have the best knowledge of the context they are immersed in.
Once alignments in the decision making emerge, cross-functional implementation teams could get to work deploying the agreed-upon initiatives.
Additionally, through periodic governance forums and decision-making events, the community can directly shape the AI’s foundational dataset and priority areas. Proposals are debated, principles are updated, and refinements to the AI’s core knowledge models are implemented based on the collective choices of stakeholder groups.
This bidirectional exchange between the system and community members allows the AI to calibrate and refine its understanding, always learning and evolving alongside the community it serves.
In the example, this synergistic interplay between AI systems and human citizens enables something previously unseen: an artificial collective consciousness that arises from the collective experience of the group; or a technology-enabled hivemind.
By coalescing fragmented insights and data from various sources into an integrated purposeful system, the community AI can illuminate paths forward that individual perspectives may have missed, as it distills understanding by revealing holistic patterns amidst complexity.
Roots of Community AI
Being a member of a community, where your contributions can affect the collective intelligence of the group in such a tangible way generates a new layer of participatory creativity and problem solving, emphasising each member’s role in shaping technological outcomes that benefit all members.
To achieve a system that is capable of representing the community, it is important to make sure that the foundational data is based on an agreed set of patterns that are representative of the community’s context and ethos.
This means delving into the heart of the community itself by exploring various core elements such as:
- Values: What are the fundamental beliefs of the community?
- Objectives: What is the purpose of the community? What are the collective long and short term goals?
- Themes: What are the recurring topics in conversations, forums, and local media? What values and concerns bind the community together?
- Artefacts: What stories do people share? What art, music, and traditions express their identity? What are the challenges and solutions reflected in local inventions and adaptations?
- Interactions: How do people collaborate, learn, and support each other? What tools are used to communicate and coordinate themselves? What are the patterns of communication and decision-making?
The process of collecting raw data and insights from the community means gathering an empathetic understanding of the community’s unique spirit.
Online communities present fertile ground to experiment with cultivating these community AI symbiotes due to the active, fast-paced nature of their interactions, which enable fast decision-making and action and the presence of content archives which make historical data easily accessible. The meta-structures for coordination within virtual communities, can also facilitate lean participatory processes which are key to experiment with AI capabilities and alignment, which is something nearly impossible to achieve by big corporations due to the pressure from institutional bodies and mass media.
If done correctively, what would emerge is a communal partner capable of reflecting the community’s needs, aspirations, collective knowledge, culture, and context, supporting its members in the best way possible.
Interacting with this AI and having a say in the way it evolves, can have substantial rewards that can facilitate people asking questions, sharing ideas, solving shared problems and preserving heritage. The tool becomes an organic part of the community’s journey, guiding, learning and growing alongside its human counterparts.
Fostering Participatory Creativity, Problem-Solving and Governance
We have discussed how building a community AI can lead to individual contributions directly influencing a collective intelligence which comes from the rapid synthesis of multiple data sources. This can potentially introduce a novel dimension of participatory creativity and problem-solving, which underscores the pivotal role of community members in steering technological advancements to benefit everyone involved.
Through a collaborative effort, AI transcends its traditional role as a mere facilitator of tasks, becoming a canvas for communal expression, innovation, and decision-making. The shared endeavour of shaping AI in this manner not only amplifies the community’s voice but also solidifies its values and priorities.
Crucially, this community-centric approach circumvents one of the major challenges faced when developing general AI: the alignment problem. Creating an artificial general intelligence that coheres with the immensely diverse values, viewpoints and moral frameworks across all of humanity is quite problematic. By focusing AI development at the community scale, alignment becomes considerably more achievable, since the consensus between the participants on crucial matters and patterns of behaviour can be reached much more easily.
A community’s shared culture, identity, and lived experiences provide a solid foundation to steer the AI’s priorities and decision-making. This, coupled with participation in the AI’s “training,” community members can iteratively refine and validate whether the system’s outputs align with their collective principles. This participatory governance model empowers communities to guide AI as a fitting extension of their ethics, culture and ambitions.
Moreover, collective intelligence harnessed through this approach acts as a focused lens for creative problem-solving and innovation. Drawing from the diversity of perspectives, skills, and context-specific knowledge within the community, the AI can cross-pollinate ideas and synthesize novel solutions tailored to local challenges. Members’ roles shift from passive consumers of technology to active co-creators shaping intelligent systems to uplift their shared future.
In essence, building AI embedded in community intelligence enables a recursive, cybernetic effect within the cultural and teleological spheres. As the AI’s capabilities grow through collective inputs, its capacity to augment human problem-solving and unlock enriching experiences aligning with the group’s needs and aspirations also expands.
This process works in a perpetual cycle: the AI does not merely receive; it also shapes the community in return. Through this cybernetic loop, the AI’s analytical powers and synthesized insights can reveal new perspectives, spark insights, and catalyze conversations that wouldn’t have emerged otherwise. This spurs the community’s evolution, prompting members to re-examine assumptions, update shared knowledge, and refine collective values and goals. The transformed community then provides a new stream of data to further tune the AI’s framework.
In this symbiotic manner, the technological and social systems mutually co-evolve and elevate each other’s potential. The community’s “digital soul” becomes an ever-evolving, self-correcting manifestation of its living culture and consciousness. This recursive reinforcement between human and artificial intelligence forges a tightening alignment that allows both to remain dynamically relevant and optimized for their specific circumstances.
Closing Thoughts
The vision outlined above portrays an optimistic yet achievable future in which the ethical development and inclusive governance of AI technology manage to coalesce with communities’ goodwill and participatory commitment. I admit that for this positive scenario to fully blossom we need a fortuitous interplay of technological capabilities, civic engagement, and a focus on benefiting the common good, which is not trivial to achieve.
That said, should the right variables fall into place, the path toward nurturing AI as a common good flows directly through communities activating technologies deeply attuned to their shared culture and lived contexts. Honoring the plurality of human experiences by decentralizing AI capabilities is an opportunity to cooperatively tackle global challenges through a multitude of solutions that are tailored to local environments.
Top-down approaches promoting universal, one-size-fits-all AI development miss the richness of cultural diversity and hyper-local needs. In contrast, grassroots models facilitate a future where the transformative potential of AI proactively aligns with and amplifies the unique voices of every community.
Ultimately, how this community-cultivated AI manifests and is deployed matters just as much as its underlying intelligence and collective intention. The AI could take the form of an interactive avatar, a virtual assistant with a distinct persona, or be integrated into dedicated community portals and apps.
Whatever the interface, giving it an identity that resonates with the population it represents will be key for fostering a recursive, cybernetic relationship: we create technologies to enhance our capabilities, but those very technologies invariably shape us in return. As communities mold these AI systems to reflect their ideals, the insights and interactions with their “hiveminds” will progressively influence how they perceive themselves and the world around them.
This symbiotic feedback loop between human and artificial intelligence has the power to be mutualistic — expanding the horizons for both biological and synthetic forms of intelligence.
