 From the perspective of decision-making, unawareness of unawareness is not of much interest. After all, if one is not even aware of the possibility that one is unaware of some state or outcome, then that unawareness cannot play any role in one’s reasoning about what to do. However, decision-theoretic models have been proposed for how a rational person responds to growth in awareness (that is meant to apply even to people who previously were unaware of their unawareness). In particular, economists Karni and Vierø (2013, 2015) have recently extended standard Bayesian conditionalisation to such learning events. Their theory, Reverse Bayesianism, informally says that awareness growth should not affect the ratios of probabilities of the states/outcomes that the agent was aware of before the growth. Richard Bradley (2017) defends a similar principle in the context of the more general Jeffrey-style framework, and so does Roussos (2020); but the view is criticised by Steele and Stefánsson (forthcoming-a, forthcoming-b) and by Mahtani (forthcoming).