How can Web3 incentivize human-AI cooperation?
Incentivized Symbiosis: A Paradigm for Human-Agent Coevolution
December 11, 2024
https://arxiv.org/pdf/2412.06855This paper proposes "Incentivized Symbiosis," a framework for human-AI coevolution within Web3 ecosystems. It uses game theory principles and bi-directional incentives, encoded via blockchain and tokens, to encourage cooperation and mutual benefit between humans and AI agents. This framework aims to address challenges in decentralized finance, governance, creative industries, and self-sovereign identity.
Key points for LLM-based multi-agent systems:
- Decentralized architectures (Web3): Leveraging blockchain for transparency, trust, and accountability in multi-agent interactions.
- Tokenized incentive mechanisms: Using tokens to reward beneficial AI agent behaviors (accuracy, efficiency) and human contributions (data, feedback), aligning incentives within the ecosystem.
- Adaptability and learning: AI agents using reinforcement learning and contextual reasoning to adapt to user needs and the decentralized environment, potentially incorporating anthropomorphic decision-making.
- Governance and collaboration: AI agents acting as mediators, assisting in governance processes, and supporting community decision-making in DAOs.
- Cultural co-evolution: Exploring the role of AI agents in shaping and being shaped by human culture within decentralized creative platforms and entertainment ecosystems. Includes discussion of iNFTs, generative AI, and blockchain gaming.
- Self-sovereign Identity (SSI): AI agents enhancing SSI by automating identity management, verification, and credentialing (e.g., via SBTs) within a trustless framework.