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A taxonomy of AI experiments

Author

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  • Alekseev, Aleksandr
  • Strobel, Christina

Abstract

We introduce a taxonomy of artificial intelligence (AI) experiments. Our taxonomy produces four types of AI experiments: conceptual AI experiments, stylized AI experiments, quasi-natural AI experiments, and natural AI experiments. At the core of our taxonomy is the sophistication of AI used, which we evaluate using a simple and robust proxy test of whether AI is developed exclusively for a research study. We discuss the advantages, disadvantages, and best use cases for each type and illustrate the use of each type in various examples. We provide a guide on how to choose the type of AI experiment that best fits a given research question.

Suggested Citation

  • Alekseev, Aleksandr & Strobel, Christina, 2026. "A taxonomy of AI experiments," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 121(C).
    • Handle: RePEc:eee:soceco:v:121:y:2026:i:c:s2214804326000170
    DOI: 10.1016/j.socec.2026.102525
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    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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