A taxonomy of AI experiments

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Authors: Aleksandr Alekseev, Christina Strobel
Cited by: 0

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.

Fields of Study & Subjects

Artificial Intelligence Applications Ethics and Social Impacts of AI Computational and Text Analysis Methods

Publication details

Journal / source
University of Regensburg Publication Server (University of Regensburg)
Publication date
1 January 2026
Language
EN