Abstract
Advances in machine learning and artificial intelligence are revolutionizing many aspects of human life, and as Banker et al. (2024) illustrate, generative artificial intelligence may also facilitate hypothesis generation in academic research. But while it is easy to imagine this idea generating some alarm (i.e., hypothesis generation may seem like the most creative, human part of research), their work actually raises an even more important question: Why should we believe that the current (human) method of hypothesis generation is somehow ideal in the first place? This article discusses the implications of their work and outlines how automated content analysis and machine learning can also help researchers determine what hypotheses deserve attention in the first place. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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