As a step toward direct AI-driven governance, NEAR Protocol is creating "AI delegates." Token holders can delegate their voting power not to a person, but to an AI whose logic and values they agree with. This tests a model where AI can represent constituents' interests more directly and consistently than human politicians.
AI provides a structural advantage to those in power by automating government systems. This allows leaders to bypass the traditional unwieldiness of human bureaucracy, making it trivial for an executive to change AI parameters and instantly exert their will across all levels of government, thereby concentrating power.
As AI evolves from single-task tools to autonomous agents, the human role transforms. Instead of simply using AI, professionals will need to manage and oversee multiple AI agents, ensuring their actions are safe, ethical, and aligned with business goals, acting as a critical control layer.
AI is not solely a tool for the powerful; it can also level the playing field. Grassroots political campaigns and labor organizers can use AI to access capabilities—like personalized mass communication and safety reporting apps—that were previously only affordable for well-funded, established entities.
The primary interface for managing AI agents won't be simple chat, but sophisticated IDE-like environments for all knowledge workers. This paradigm of "macro delegation, micro-steering" will create new software categories like the "accountant IDE" or "lawyer IDE" for orchestrating complex AI work.
AI's integration into democracy isn't happening through top-down mandates but via individual actors like city councilors and judges. They can use AI tools for tasks like drafting bills or interpreting laws without seeking permission, leading to rapid, unregulated adoption in areas with low public visibility.
As AI capabilities accelerate toward an "oracle that trends to a god," its actions will have serious consequences. A blockchain-based trust layer can provide verifiable, unchangeable records of AI interactions, establishing guardrails and a clear line of fault when things go wrong.
Instead of hard-coding brittle moral rules, a more robust alignment approach is to build AIs that can learn to 'care'. This 'organic alignment' emerges from relationships and valuing others, similar to how a child is raised. The goal is to create a good teammate that acts well because it wants to, not because it is forced to.
Block's CTO believes the key to building complex applications with AI isn't a single, powerful model. Instead, he predicts a future of "swarm intelligence"—where hundreds of smaller, cheaper, open-source agents work collaboratively, with their collective capability surpassing any individual large model.
For AI agents to be truly autonomous and valuable, they must participate in the economy. Traditional finance is built for humans. Crypto provides the missing infrastructure: internet-native money, a way for AI to have a verifiable identity, and a trustless system for proving provenance, making it the essential economic network for AI.
The future of AI is not just humans talking to AI, but a world where personal agents communicate directly with business agents (e.g., your agent negotiating a loan with a bank's agent). This will necessitate new communication protocols and guardrails, creating a societal transformation comparable to the early internet.