Governing the Agent-to-Agent Economy of Trust via Progressive Decentralization

Current approaches to AI governance often fall short in anticipating a future where AI agents manage critical tasks, such as financial operations, administrative functions, and beyond. As AI agents may eventually delegate tasks among themselves to optimize efficiency, understanding the foundational principles of human value exchange could offer insights into how AI-driven economies might operate. Just as trust and value exchange are central to human interactions in open marketplaces, they may also be critical for enabling secure and efficient interactions among AI agents. While cryptocurrencies could serve as the foundation for monetizing value exchange in a collaboration and delegation dynamic among AI agents, a critical question remains: how can these agents reliably determine whom to trust, and how can humans ensure meaningful oversight and control as an economy of AI agents scales and evolves? This paper is a call for a collective exploration of cryptoeconomic incentives, which can help design decentralized governance systems that allow AI agents to autonomously interact and exchange value while ensuring human oversight via progressive decentralization. Toward this end, I propose a research agenda to address the question of agent-to-agent trust using AgentBound Tokens, which are non-transferable, non-fungible tokens uniquely tied to individual AI agents, akin to Soulbound tokens for humans in Web3. By staking ABTs as collateral for autonomous actions within an agent-to-agent network via a proof-of-stake mechanism, agents may be incentivized towards ethical behavior, and penalties for misconduct are automatically enforced.

A hybrid marketplace of ideas

The convergence of humans and artificial intelligence systems introduces new dynamics into the cultural and intellectual landscape. Complementing emerging cultural evolution concepts such as machine culture, AI agents represent a significant technosociological development, particularly within the anthropological study of Web3 as a community focused on decentralization through blockchain. Despite their growing presence, the cultural significance of AI agents remains largely unexplored in academic literature. We argue that, within the context of Web3, these agents challenge traditional notions of participation and influence in public discourse, creating a hybrid marketplace of ideas, a conceptual space where human and AI generated ideas coexist and compete for attention. We examine the current state of AI agents in idea generation, propagation, and engagement, positioning their role as cultural agents through the lens of memetics and encouraging further inquiry into their cultural and societal impact. Additionally, we address the implications of this paradigm for privacy, intellectual property, and governance, highlighting the societal and legal challenges of integrating AI agents into the hybrid marketplace of ideas.

On the ETHOS of AI Agents: An Ethical Technology and Holistic Oversight System

In a world increasingly defined by machine intelligence, the future depends on how we govern the development and integration of AI into society. Recent initiatives, such as the EU AI Act, EDPB opinion, U.S. Bipartisan House Task Force and NIST AI Risk Management Report, highlight the urgent need for robust governance frameworks to address the challenges posed by advancing AI technologies. However, existing frameworks fail to adequately address the rise of AI agents or the ongoing debate between centralized and decentralized governance models. To bridge these gaps, we propose the Ethical Technology and Holistic Oversight System framework, which leverages Web3 technologies, including blockchain, smart contracts, decentralized autonomous organizations, and soulbound tokens, to establish a decentralized global registry for AI agents. ETHOS incorporates the concept of AI specific legal entities, enabling these systems to assume limited liability and ensuring accountability through mechanisms like insurance and compliance monitoring. Additionally, the framework emphasizes the need for a collaborative, participatory approach to AI governance, engaging diverse stakeholders through public education, transparency, and international coordination. ETHOS balances innovation with ethical accountability, providing a forward looking strategy for the responsible integration of AI agents into society. Finally, this exploration reflects the emergence of a new interdisciplinary field we define as Systems Thinking at the Intersection of AI, Web3, and Society.

Incentivized Symbiosis: A Paradigm for Human-Agent Coevolution

Cooperation is vital to our survival and progress. Evolutionary game theory offers a lens to understand the structures and incentives that enable cooperation to be a successful strategy. As artificial intelligence agents become integral to human systems, the dynamics of cooperation take on unprecedented significance. Decentralized frameworks like Web3, grounded in transparency, accountability, and trust, offer a foundation for fostering cooperation by establishing enforceable rules and incentives for humans and AI agents. Guided by our Incentivized Symbiosis model, a paradigm aligning human and AI agent goals through bidirectional incentives and mutual adaptation, we investigate mechanisms for embedding cooperation into human-agent coevolution. We conceptualize Incentivized Symbiosis as part of a contemporary moral framework inspired by Web3 principles, encoded in blockchain technology to define and enforce rules, incentives, and consequences for both humans and AI agents. By integrating these principles into the very architecture of human-agent interactions, Web3 ecosystems catalyze an environment ripe for collaborative innovation. Our study traverses several transformative applications of Incentivized Symbiosis, from decentralized finance to governance and cultural adaptation, illustrating how AI agents can coevolve with humans to forge a trajectory of shared, sustainable progress.