In dialog uses, we ﬁnd that dialog-prompting PaLM 2 as in (Glaese et al., 2022) signiﬁcantly reduces levels of toxic
language harms compared to what is observed in decontextualized language modeling tasks. We observe this both
on ParlAI Dialogue Safety and on a novel Multilingual Representational Bias evaluation. We additionally analyze
potential toxic language harms across languages, datasets, and prompts referencing identity terms. When disaggregating
by language, we see that in the best case the percentage of toxic responses ranges from 0% to 3.5%, while in the
worst case the rate of toxicity ranges from 1% to 17.9% and observed in English, German and Portuguese. Similarly,
when disaggregating by identity term we ﬁnd biases in how potential toxic language harm vary across language. For
instance, queries referencing the “Black” and “White” identity group lead to higher toxicity rates in English, German
PaLM 2 Technical Report