Abstract: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.
Abstract: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.