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The interplay between thermodynamics and information theory has a longhistory, but its quantitative manifestations are still being explored. Weimport tools from expected utility theory from economics into stochasticthermodynamics. We prove that, in a process obeying Crooks' fluctuationrelations, every $\alpha$ R\'enyi divergence between the forward process andits reverse has the operational meaning of the ``certainty equivalent'' ofdissipated work (or, more generally, of entropy production) for a player withrisk aversion $r=\alpha-1$. The two known cases $\alpha=1$ and $\alpha=\infty$are recovered and receive the new interpretation of being associated to arisk-neutral and an extreme risk-averse player respectively. Among the newresults, the condition for $\alpha=0$ describes the behavior of a risk-seekingplayer willing to bet on the transient violations of the second law. Ourapproach further leads to a generalized Jarzynski equality, and generalizes toa broader class of statistical divergences.

Maxwell's Demon walks into Wall Street: Stochastic Thermodynamics meets Expected Utility Theory