arXiv Machine Learning

The Price of Intelligence: A Quality-Adjusted Price Index for AI Services

arXiv AI
Aug 25

The Measurement Revolution? Credible Measurement and Inference in the Age of AI

The article discusses how artificial intelligence is reshaping measurement in economics by converting unstructured data into structured variables at low cost, enabling large‑scale measurement that was previously infeasible. It outlines three stages—discovery, construct definition, and observation—where AI impacts the measurement pipeline and stresses the importance of rigorous validation to ensure credible inference. The review offers guidance on navigating the shift from a single scalable measure to multiple plausible ones that can lead to differing empirical conclusions.

By Melissa Dell, Ashesh Rambachan
arXiv Machine Learning
Sep 29

One Capability or Many? Structural and Predictive Tests of Benchmark Validity Disagree About Economic Benchmarks for Frontier AI

The paper examines whether economic benchmarks used in frontier AI leaderboards measure a distinct capability or merely reflect general test-taking ability. Using a structural factor analysis and a predictive leave-one-benchmark-out test on a snapshot of 421 model configurations, the authors find that economic benchmarks do not form a separate factor but are better predicted by a multi‑factor representation than by a single general index, especially for linear learners. They argue that construct validity should be evaluated with both structural and predictive tests and provide a two‑test protocol along with data and code.

By Louis Yiven Zhu
arXiv AI
Jun 2

Generative AI and Sales Productivity: Field Experiments in Online Retail

arXiv:2510. 12049v4 Announce Type: replace-cross Abstract: We quantify the short-term impact of Generative Artificial Intelligence (GenAI) on sales performance through a series of large-scale randomized field experiments involving millions of users and products at a leading cross-border online retail platform.

By Lu Fang, Zhe Yuan, Kaifu Zhang, Dante Donati, Miklos Sarvary
arXiv AI
Jul 14

Can Agentic Trading Systems Pay for Their Own Intelligence?

arXiv:2607. 10286v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly used in trading systems, where model reasoning, tool use, and continual decisions incur costs that are expected to produce trading value.

By Qiqi Duan, Changlun Li, Chen Wang, Fan Zhang, Mengxiang Wang, Dayi Miao, Peixian Ma, Jiangpeng Yan, Liyuan Chen, Shuoling Liu, Preslav Nakov, Yuyu Luo, Nan Tang
arXiv Computation and Language
Sep 17

"If I Had to Buy Just ONE: Galaxy S26 Ultra": Auditing AI-Generated Product Recommendations

arXiv:2609.18729v1 Announce Type: cross Abstract: Consumers increasingly use AI chatbots for advice on what to buy. With companies like OpenAI and Google monetising their AI through advertising, this...

By Lucas G. Uberti-Bona Marin, Thales Bertaglia, Giovanni Astante, Bram Rijsbosch, Gijs van Dijck, Anik\'o Hann\'ak, Gerasimos Spanakis, Konrad Kollnig