ABSTRACT The Gender Balance Assessment Tool (GBAT) was introduced in 2016 as a shortcut for researchers and instructors who wanted to quickly determine the gender balance of the authors in their bibliographies and syllabi. In the years since then, some journals and departments have encouraged its use. However, technology also has changed significantly during this period, and the emergence of generative AI models have introduced systems with enormous potential to evaluate the demographic balance of syllabi and bibliographies. By leveraging information on the Internet other than names, and by being less constrained in terms of formatting and name recognition, this article shows that generative AI systems are superior to the GBAT, in terms of both their accuracy and their ability to evaluate general demographic balance rather than only gender balance.
Musgrave et al. (Mon,) studied this question.