Incentivized Symbiosis: A Paradigm for Human-Agent Coevolution

TL;DR

This paper tackles the problem of sustaining cooperation between humans and autonomous AI agents by proposing Incentivized Symbiosis, a social contract encoded in Web3 that aligns incentives through tokenized rewards, credentialing via Soulbound Tokens, and smart-contract governance. It argues that integrating human–AI coevolution with decentralized frameworks—encompassing DeFi use cases, DAO governance, the creator economy, and SSI—can foster trust, transparency, and mutual adaptation. The approach combines evolutionary game theory, contract theory, and trust-management concepts to design bi-directional incentives that guide agent behaviors toward socially desirable outcomes. The work highlights practical implications for DeFi, governance, culture, and identity management, while acknowledging regulatory and ethical challenges and calling for empirical validation and real-world deployments to assess value and impact.

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. The convergence of human-agent teaming, contract theory, and decentralized frameworks like Web3, grounded in transparency, accountability, and trust, offers a foundation for fostering cooperation by establishing enforceable rules and incentives for humans and AI agents. We conceptualize Incentivized Symbiosis as a social contract between humans and AI, inspired by Web3 principles and encoded in blockchain technology, to define and enforce rules, incentives, and consequences for both parties. By exploring this paradigm, we aim to catalyze new research at the intersection of systems thinking in AI, Web3, and society, fostering innovative pathways for cooperative human-agent coevolution.