Credible commitment devices have been a popular approach for robust multi-agent coordination. However, existing commitment mechanisms face limitations like privacy, integrity, and susceptibility to mediator or user strategic behavior. It is unclear if the cooperative AI techniques we study are robust to real-world incentives and attack vectors. However, decentralized commitment devices that utilize cryptography have been deployed in the wild, and numerous studies have shown their ability to coordinate algorithmic agents facing adversarial opponents with significant economic incentives, currently in the order of several million to billions of dollars. In this paper, we use examples in the decentralization and, in particular, Maximal Extractable Value (MEV) (arXiv:1904.05234) literature to illustrate the potential security issues in cooperative AI. We call for expanded research into decentralized commitments to advance cooperative AI capabilities for secure coordination in open environments and empirical testing frameworks to evaluate multi-agent coordination ability given real-world commitment constraints.

翻译：可信承诺装置一直是实现鲁棒多智能体协调的常用方法。然而，现有的承诺机制存在隐私性、完整性等方面的局限性，且易受中介或用户策略行为的影响。目前尚不清楚我们所研究的协作式人工智能技术是否能够抵御现实世界中的激励因素和攻击手段。然而，利用密码学的去中心化承诺装置已在现实环境中得到部署，大量研究表明它们能够协调算法智能体对抗具有显著经济激励（目前规模从数百万到数十亿美元不等）的对抗性对手。本文通过去中心化领域，特别是最大可提取价值（MEV，arXiv:1904.05234）文献中的实例，阐明了协作式人工智能中潜在的安全问题。我们呼吁扩展对去中心化承诺的研究，以提升协作式人工智能在开放环境中实现安全协调的能力，并建立实证测试框架，在考虑现实承诺约束的条件下评估多智能体协调能力。