AGENTIC-SYSTEMSJuly 9, 20261 min read1 views

Measuring Intelligence Beyond Human Scale

As AI capabilities surpass human limits, traditional benchmarks fail. This paper proposes a new paradigm of relative measurement where AI models generate challenges to evaluate each other, creating a scalable, adversarial rating system.

Computer Science > Artificial Intelligence

Title:Measuring Intelligence Beyond Human Scale

View PDFAbstract:How can we measure intelligence beyond human capability?

Human-authored benchmarks saturate, and above human capability, examiners may not know which tasks are both hard and verifiable. We argue that this difficulty is inherent to absolute-scale evaluation and propose a new paradigm based on relative measurement in which models generate public challenges that separate other systems. Aggregating these outcomes yields an adversarial psychometric rating system that can scale with the systems being measured. We describe practical protocols that reduce incentives for private-information attacks, support judge-free adjudication, and naturally scale with agent capabilities. We instantiate the framework across verifiable and open-ended, non-verifiable domains, illustrating how model-generated evaluation can continue to measure systems beyond the human frontier.

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Source: arXiv cs.AI Recent

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