For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies. However, whether XAI researchers consider potential cultural differences in human explanatory needs remains unexplored. We highlight psychological research that found significant differences in human explanations between many people from Western, commonly individualist countries and people from non-Western, often collectivist countries. We argue that XAI research currently overlooks these variations and that (...) many popular XAI designs implicitly and problematically assume that Western explanatory needs are shared cross-culturally. Additionally, we systematically reviewed over 200 XAI user studies and found that most studies did not consider relevant cultural variations, sampled only Western populations, but drew conclusions about human-XAI interactions more generally. We also analyzed over 30 literature reviews of XAI studies. Most reviews did not mention cultural differences in explanatory needs or flag overly broad cross-cultural extrapolations of XAI user study results. Combined, our analyses provide evidence of a cultural bias toward Western populations in XAI research, highlighting an important knowledge gap regarding how culturally diverse users may respond to widely used XAI systems that future work can and should address. (shrink)

Scientists may sometimes generalize from their samples to broader populations when they have not yet sufficiently supported this generalization. Do such hasty generalizations also occur in experimental philosophy? To check, we analyzed 171 experimental philosophy studies published between 2017 and 2023. We found that most studies tested only Western populations but generalized beyond them without justification. There was also no evidence that studies with broader conclusions had larger, more diverse samples, but they nonetheless had higher citation impact. Our analyses reveal (...) important methodological limitations of many experimental philosophy studies and suggest that philosophical training may not protect against hasty generalizations. (shrink)

Propositional attitude generics such as “Experts think early humans ate grass” report an epistemic state (e.g., think, believe, say) that is generalised to a wider community (e.g., Experts, Scientists, Academics). These generics are often used in place of quantified claims (e.g., “Some experts think…”) but three pre-registered experiments (N = 4891) indicate that this lexical choice risks misrepresenting the true degree of scientific consensus. Relative to “Some experts think…” the generic “Experts think…” was more likely to be understood as “All (...) Experts” or “Possibly all Experts” and less likely to invite the scalar inference “Not all Experts.” Consistent with this, the choice to use generic language became increasingly likely as expert consensus approached unanimity. Propositional attitude generics can imply a high degree of consensus and keep open the possibility of universal agreement. To avoid overgeneralisation, they should be used with caution where the objective degree of consensus is unknown. (shrink)