arXiv:2603.17212v2 Announce Type: replace-cross Abstract: When organizations delegate text generation tasks to AI providers via pay-for-performance contracts, expected payments rise when evaluation is noisy. As evaluation methods become more elaborate, the economic benefits of decreased noise are often overshadowed by increased evaluation costs. In this work, we introduce adaptive contracts for AI delegation, which allow detailed evaluation to be performed selectively after observing an initial coarse signal in order to conserve resources. We make three sets of contributions: First, we provide
The increasing sophistication and cost of AI models, coupled with varied evaluation methods, necessitate more efficient economic frameworks for AI delegation.
Adaptive contracts could significantly reduce the operational costs and improve the economic viability of delegating complex AI tasks, making advanced AI more accessible and scalable.
The economic model for outsourcing AI work shifts from fixed-cost or purely performance-based systems to dynamic, resource-optimizing contracts.
- · AI service providers
- · Organizations delegating AI tasks
- · AI evaluation tool developers
- · AI providers with inefficient cost structures
- · Organizations overpaying for AI evaluation
More cost-effective delegation of AI tasks will lead to wider adoption of specialized AI services.
Increased adoption of AI services could accelerate the development of more complex and specialized AI agent capabilities.
The reduced cost barrier for AI deployment may democratize access to advanced AI functionalities, potentially leading to new business models and market disruptions across various sectors.
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Read at arXiv cs.LG