(Head et al., 2023) and (Reid, 2023) raise concerns about bias and the importance of equity in AI applications for evaluation, which have led to questions about the validity of AI-generated findings (Azzam, 2023). The way the AI sees the world, the salient features it identifies, the words it uses to identify them, and its understanding of causation are certainly wrapped up in a hegemonic worldview (Bender et al., 2021). Those groups most likely to be disadvantaged by this worldview are approximately the same who have least say in how these technologies are developed and employed.

AI is developing quickly: new models and techniques become available every month. However, we believe that any tools which genuinely add to knowledge should use procedures which are broken down into workflows consisting of simple individual steps so that humans can understand and check what is happening.