Author: Jarrad Hope, Co-founder of Logos
As AI rapidly expands, humanity finds itself in an ideological stalemate regarding the management of this new technology. We either choose to allow governments and corporations to dominate the training and use of AI, formulating policies that control our lives, or we call for the establishment of new governance models based on transparency, regeneration, and public interest.
Network states—digital communities that utilize blockchain to form borderless societies—offer significant improvements for coordinating AI with human welfare. As technology continues to advance the scope of digital enhancement, it is crucial to establish a new category of AI development management focused on serving people rather than power.
Today's generative AI is trained on narrow datasets and governed by centralized participants (such as xAI and OpenAI), with limited public accountability. Training large language models on limited datasets can lead to the reinforcement of biases, failing to reflect diverse perspectives and undermining fairness initiatives. For example, Grok faced backlash from this social media giant after producing extremist responses to certain prompts following an update.
Network states can address this issue by establishing organizations that grant governance rights to communities, allowing for new approaches to training and democratizing AI. Shifting the foundational philosophy towards consensus, ownership, privacy, and community will mitigate the prominent negative implications in the current AI discourse. Decentralized communities within network states will define their goals and datasets, training AI models that align with their needs.
Influential decentralized autonomous organizations (DAOs) can help democratize AI by focusing on using blockchain technology for social good. They can collectively fund open-source AI tools, promote inclusive data collection, and provide ongoing public oversight. This approach shifts governance from gatekeeping to management, ensuring that AI development benefits all of humanity. Shared responsibility will ensure that the needs of the most vulnerable populations are included and foster greater stakeholder recognition of AI's advantages.
Over 60% of the world's leading AI development is concentrated in one state in the U.S.—California—reflecting a high concentration of influence. This imbalance is not only geographical but also political and economic. For instance, xAI was sued for powering its data center with gas turbines in Memphis, Tennessee. This is a clear example of local governments and citizens being at odds over environmental regulation. Without checks and balances, this power can extract value from society while externalizing harm. This harm is exacerbated by AI's demand for high energy outputs, leading to disproportionate ecological impacts on specific communities.
Network states offer an alternative: decentralized communities unbound by borders, where digital citizens co-create AI governance frameworks. The influential DAOs embedded in these systems allow participants to propose, vote on, and implement safeguards and incentive mechanisms, transforming AI from a tool of control into an infrastructure for public resources. Expanding AI's representativeness will inform how best to leverage this technology for positive social impact.
Most AI systems today operate in algorithmic black boxes, producing real-world effects without defined human input or oversight. From biased hiring algorithms to opaque medical triage systems, people are increasingly affected by automated decisions without a voice in how those decisions are made.
Network states disrupt this model by allowing on-chain governance and transparent public records. People can see how rules are made, participate in their formation, and opt out if they disagree.
Influential DAOs build this vision by mitigating harm and incentivizing the provision of public goods. They invest in the long-term sustainability of fair, auditable systems, creating open and transparent development for communities, and may invite external parties to opt in and contribute funding or other resources.
Traditional nation-states struggle to adequately regulate AI due to outdated digital backgrounds of legislators, fragmented policies, and over-reliance on traditional tech leadership. Network states are building models from the ground up, using blockchain-native tools, decentralized coordination, and programmable governance. Influential DAOs—goal-driven open public digital communities—can usher in a new era of AI development. These communities can adjust incentive mechanisms by combining decentralized blockchain and governance with generative and agent-based AI, creating participatory, representative, and regenerative AI.
AI should be viewed as a public good, not merely as a tool for efficiency. New governance systems must be open, transparent, and community-led to achieve this, fostering intelligent and equitable innovation and development planning. We can begin building these systems today by embracing the inclusive, technical, and philosophical aspects of network states and influential DAOs. Prioritizing investment in infrastructure that supports digital sovereignty and collective care is crucial for designing an AI future that benefits people, not just profits.
Author: Jarrad Hope, Co-founder of Logos.
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Original: “Opinion: Decentralized Communities Can Fix AI Bias”
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