Overall, developers seeking to build dialog systems on PaLM 2 should continue to invest in application-speciﬁc
mitigation methods. While we see major reductions in toxic degeneration from dialog prompting over language
modeling alone, prompted dialog systems built from PaLM 2 continue to produce toxic language harms, and to exhibit
patterns of bias in how those harms vary by language and queries related to identity terms. Importantly, these biases are
not uniformly consistent across languages and identity terms, and we see biases related to gender despite these being
explicitly targeted within the dialog prompt. These ﬁndings highlight the need for disaggregated analysis and further
research into intersectionality in harms and biases in pre-trained language models (Crenshaw, 1989; Blodgett et al.,
2020; Ruder et al., 2022), and for additional research into effective mitigation methods for dialog uses (Thoppilan et al.,
2022).
PaLM 2 Technical Report