竞争市场中，企业应聚焦自身优势误差维度提升，而非盲目追求整体准确率。
Pricing AI Model Accuracy
- 企业应投资于自身误差更优的领域（如误报或漏报）
- 提升优势维度误差可增利润，投入劣势维度则亏损
- 适合关注模型商业化与市场竞争策略的研究者
本文研究了企业竞争提供高精度AI模型的市场，消费者对模型准确率有异质偏好。构建消费者-企业双头垄断模型，分析竞争如何影响企业改进模型准确率的动机。每家企业致力于最小化模型误差，但该选择常非最优。反直觉地发现，在竞争市场中，提升整体准确率并不必然带来更高利润。企业最优策略是进一步投资于自身具有竞争优势的误差维度。通过将模型误差分解为假阳性率和假阴性率，企业可通过投资降低各维度误差。结果表明：在优势维度投资可显著提升利润，在劣势维度投资则导致利润下降。盈利性投资虽损害消费者利益，却能提升整体社会福利。
原文摘要 · Abstract (English)
This paper examines the market for AI models in which firms compete to provide accurate model predictions and consumers exhibit heterogeneous preferences for model accuracy. We develop a consumer-firm duopoly model to analyze how competition affects firms' incentives to improve model accuracy. Each firm aims to minimize its model's error, but this choice can often be suboptimal. Counterintuitively, we find that in a competitive market, firms that improve overall accuracy do not necessarily improve their profits. Rather, each firm's optimal decision is to invest further on the error dimension where it has a competitive advantage. By decomposing model errors into false positive and false negative rates, firms can reduce errors in each dimension through investments. Firms are strictly better off investing on their superior dimension and strictly worse off with investments on their inferior dimension. Profitable investments adversely affect consumers but increase overall welfare.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。