Resolution criteria

This market will resolve to "Yes" if, by the specified market end date, there is a widely recognized, peer-reviewed scientific consensus or verifiable public demonstration that an artificial intelligence system has achieved "self-repairing" capabilities. For the purposes of this market, "self-repairing" is defined as an AI system autonomously detecting, diagnosing, and correcting errors in its own base code, architecture, or hardware configuration without human intervention.

Resolution will be based on reports from reputable technology news outlets (e.g., Reuters, AP, TechCrunch) or documentation from leading AI research organizations (e.g., OpenAI, Google DeepMind, Anthropic). If no such consensus or demonstration exists by the end date, the market resolves to "No."

Background

The concept of "self-repairing" AI touches on the broader field of autonomous systems and self-healing software. While current AI systems utilize techniques like reinforcement learning to optimize performance and can suggest code fixes to human developers, a fully autonomous "self-repairing" system—capable of modifying its own foundational architecture to fix catastrophic failures without external oversight—remains a theoretical milestone in computer science. Debates in this field often center on the distinction between iterative model training and true autonomous structural self-correction.

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