The widespread use of AI services has raised concerns for its environmental sustainability, towards which recent studies have identified carbon emissions of AI inference as the major contributor. This paper introduces a framework for designing AI inference incentives based on the users' valuation for inference quality and latency, together with their environmental consciousness, while accounting for the tradeoff between carbon emissions and the two QoE parameters. Our approach can accommodate different tradeoffs, that depend on the size and complexity of the AI models and the allocation of resources to serve inference requests. The incentives can be offered through a practical two-tier service subscription that offers users a discount in exchange for reduced carbon emissions. The discounted service option gives the AI provider the flexibility to serve some percentage of inference requests at a lower quality and higher latency during periods of high carbon intensity.

翻译：人工智能服务的广泛应用引发了对其环境可持续性的担忧，近期研究指出AI推理产生的碳排放是主要贡献因素。本文提出一个框架，基于用户对推理质量与延迟的评估及其环保意识，设计AI推理激励机制，同时兼顾碳排放与两个QoE参数之间的权衡关系。我们的方法可适应不同权衡场景，这些场景取决于AI模型的规模与复杂度，以及用于服务推理请求的资源分配。该激励可通过实用的两级服务订阅模式实现，为用户提供折扣以换取碳排放量的降低。折扣服务选项赋予AI提供商灵活性，使其在碳强度较高时期，能以较低质量和较高延迟服务部分推理请求。