AI safety and alignment research has predominantly been focused on methods for safeguarding individual AI systems, resting on the assumption of an eventual emergence of a monolithic Artificial General Intelligence (AGI). The alternative AGI emergence hypothesis, where general capability levels are first manifested through coordination in groups of sub-AGI individual agents with complementary skills and affordances, has received far less attention. Here we argue that this patchwork AGI hypothesis needs to be given serious consideration, and should inform the development of corresponding safeguards and mitigations.
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The article discusses the Agent2Agent (A2A) Protocol, an attempt to provide a common language for different AI agents to collaborate without revealing their internal workings. It also compares A2A with the Model Context Protocol (MCP), highlighting their complementary roles in building complex AI systems.
